BORDER DELAYS AND ECONOMIC IMPACT TO THE FREIGHT SECTOR: AN EXPLORATION OF THE EL PASO PORTS OF ENTRY

Transcription

1 BORDER DELAYS AND ECONOMIC IMPACT TO THE FREIGHT SECTOR: AN EXPLORATION OF THE EL PASO PORTS OF ENTRY by Sharada R. Vadali, Ph.D. Dong Hun Kang, Ph.D. Karen Fierro Project performed by Report No: July 2011 Report prepared by Texas Transportation Institute 4050 Rio Bravo, Suite 151 El Paso, Texas TEXAS TRANSPORTATION INSTITUTE The Texas A&M University System College Station, Texas

2 Table of Contents Page List of Figures... iii List of Tables... iv Disclaimer and Acknowledgments... v Executive Summary... 1 Chapter I: Texas Ports of Entry and Nature of Freight Movements in the El Paso- Juarez Bi-National Region... 3 Introduction... 3 Texas Border Ports of Entry... 3 Trading Partners and Trade through El Paso Border Ports of Entry... 4 Understanding the Nature of Freight Movements in the El Paso-Juarez Bi-National Region and Other Ports Regional Integration Perspectives and Gateway Corridor Types... 9 Chapter II: El Paso Ports of Entry and Borders as Components of Transport Costs and Economic Costs Ports are not Identical Passenger Ports Commercial and Passengers Ports Ports Vary in Terms of Commodity/Trade Profiles Ports Vary in Terms of Transport Corridors They Serve Ports Vary in Terms of How They Move Goods Ports Vary in Terms of final Destinations they Serve/Trading Partners (Truck Trade flow Distributions) Borders as Components of Transport Costs and Links to Logistical Efficiency Factors Causing Delays Prior Literature, Perspectives in Assessing Economic Costs of Delay Types of Economic Costs Chapter III: El Paso Freight Movements Freight Movement Trends El Paso Ports of Entry Proximity of Maquilas to Border Ports of Entry Chapter IV: Perceptions on Border Delays: Evidence from Shippers in the El Paso Juarez Region Shipper Surveys Issues Identified by Shippers Chapter V: Framework to Evaluate Direct Costs of Border Crossing Inefficiencies to Shippers and carriers Framework Components Commodity/Trade Profiles by Direction of Flow Data Needs to Quantify Direct Costs and Definitions of Delay Other Critical Data Elements Chapter VI: Direct Costs Categories Variable Direct Cost Categories: Shipper Variable Direct Cost Category: Carrier Commodity Classifications and Ports of Entry Texas Transportation Institute Page i

3 Shipper Costs Variable Carrier Costs Chapter VII: Model Structure Structure of the Spreadsheet Tool Schematic Data Flows Chapter VIII: Bridge of the Americas Illustration Number of Freight Truck Crossings User Input Values in the Spreadsheet Tool Output Results from the Simulation Results Conclusions References Appendix 1: Bridge of the Americas Details Appendix 2: Commodity Profiles (Ports of Entry) (By Value [2008]) Appendix 3: Interview Instrument Texas Transportation Institute Page ii

4 LIST OF FIGURES Page Figure I-1. Texas-Mexico Border Ports of Entry (Commercial and Passenger)... 3 Figure III-1. Trends in Import Value through El Paso Ports of Entry (with USA and with Texas Alone) Figure III-2. Trends in Import Trade Weight through El Paso Ports of Entry (with Entire USA and with Texas Alone) (Short Tons) Figure III-3. Location Distribution of Juarez Maquiladoras Relative to Border Ports of Entry (Source: 37 Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of Raw Materials/Intermediate Goods and Final Goods (Number Responding) Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number) Figure IV-3. Daily Peaks Identified by Respondents Figure IV-4. Seasonal Peaks Identified by Shippers Figure IV-5. Impacts on Delay on Supply Chains Figure IV-6. Shipper Responses on Ability to Pass Cost Increases Figure V-1. Map of BOTA Crossing Facilities (2009) Figure V-2. Number of RFID Readings at El Paso BOTA Entering and Exiting Points (Weekday BOTA RFID Readings between July and December 2009) Figure V-3. Monthly NB Truck Crossing and RFID Counts at BOTA Figure V-4. Monthly NB Truck Volumes and RFID Average of Crossing Times at BOTA (2009) Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID Data July-December 2009) Figure V-6. Hourly Average of Crossing Times: Comparison by Month (2009) Figure V-7. Average of Crossing Times by Day of Week (July-December, 2009) Figure V-8. Fitted Lognormal Distributions of RFID Observations by Time Periods Figure V-9. Performance Measures from RFID Observations (Weekday Crossing Time by Minute, September 2009) (BOTA) Figure V-10. Crossing Time Distribution (BOTA) and Performance Measures/Statistics (July-September 2009 BOTA) Figure V-11. Various Components of the Framework (by Direction of Flows) Figure VII-1. Structure of the Delay Cost Estimation Tool Figure VII-2. Schematic Data Flow Diagram of the Spreadsheet Tool Figure VII-3. Delay Measures Figure VIII-1. Main Input Screen DCET Figure VIII-2. Sample Screenshots of Output Reports BOTA Illustration Figure VIII-3. Ninety-Five Percent Confidence Interval Cost Estimates BOTA Illustration.. 71 Figure IX-1. BOTA Land Port of Entry: View from the Mexican Side Texas Transportation Institute Page iii

5 LIST OF TABLES Page Table I-1. Truck Volumes through All US-Mexico Ports of Entry (2010)... 8 Table II-1. Summary of Perspectives Adopted in Assessing Economic Costs of Delay Table II-2. Additional Perspectives on Wider Economic Implications and General Port Efficiencies Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and Weight) Table III-2. Northbound Crossing Volumes (Trucks) (El Paso Ports of Entry) and by Loaded or Empty Table III-3. El Paso Ports Import Classification and Value (2010) Table III-4. El Paso Port Export Classification and Value (2010) Table IV-1. Origin/Destination of Commodities Identified by Shippers Table V-1. Fitted Crossing Time Distribution Parameters Table VI-1. Average Imports Cargo Value per Loaded Truck (Northbound Crossings El Paso) Table VI-2. Imports through El Paso Ports (2009) Table VI-3. Commercial Vehicle Values of Time in the United States Table VIII-1. Default Values Bridge of the Americas, El Paso Table XI-1. Commodity Profile Brownsville Exports to Mexico Table XI-2. Commodity Profile Eagle Pass Exports to Mexico (Primarily Agriculture) Table XI-3. Commodity Profile El Paso Exports to Mexico (Primarily Maquila Products) Table XI-4. Commodity Profile Hidalgo Exports to Mexico Table XI-5. Commodity Profile Laredo Exports to Mexico Table XI-6. Commodity Profile Brownsville Imports to United States Table XI-7. Commodity Profile Eagle Pass Imports to United States Table XI-8. Commodity Profile El Paso Imports to United States Table XI-9. Commodity Profile Hidalgo Imports to United States Table XI-10. Commodity Profile Laredo Imports to United States Texas Transportation Institute Page iv

6 DISCLAIMER AND ACKNOWLEDGMENTS This research was performed by the Center for International Intelligent Transportation Research (CIITR), a part of the Texas Transportation Institute. The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The authors acknowledge the funding graciously provided by the Center for International Intelligent Transportation Research, Texas Transportation Institute and the shipper and carriers who shared their views. Texas Transportation Institute Page v

7 EXECUTIVE SUMMARY This research examined trading and commodity profiles of El Paso ports of entry in an attempt to understand economic implications attributable to delays in the border crossing process. Based on an exhaustive literature review, examination of trends, and commodity profiles in the bi-national region (El Paso-Juarez), a generic framework was developed to address economic implications of border-related delays. Since economic costs fall into a large category and can embrace administrative, direct, indirect and induced costs, this report focused only on direct costs alone that are attributable to shippers and carriers, but as part of a larger framework comprising other costs. The innovative elements of this framework are the combination of archived crossing time information from radio frequency tag data along with information on crossing volumes, values and weights to develop an innovative interactive spreadsheet tool called Direct Cost Estimation Tool (DCET). Since a normal border crossing process does involve some time, this research focused on the development of baseline delay measures using statistical benchmarks like minimum crossing time, mean and other measures based on the distribution of crossing times. The other features of the tool are an explicit consideration of reliability of crossing times through the development of buffer time measures which impact inventory costs of shippers. This tool also allows for consideration of a delay metrics reflecting the reliability of the crossing time. These novel elements make this research an advancement over prior work in this area. More specifically, this report makes several advances in two specific areas: Advances in combining near real time delay measures with other data sources to estimate direct variable costs of delay to shippers and carriers. The costs to shippers are largely inventory related and can be broken down into holding costs, costs from damage/perishability/obsolescence and finally, inventory costs from variability in crossing times. The last cost category arises when shipper s buffer time windows are not included as part of trip planning or when planned buffers fall short of the statistically estimated buffer window. The cost to carriers comprises time variable costs and relate to labor costs and vehicle operating costs. Advances in the use of archived innovative data to quantify performance measures communicating delay in the border crossing process for assessing near real time trends. The delay measures include minimum, mean and 95 th percentile crossing times. A buffer time is developed to reflect trip reliability and the time cushion needed to ensure on-time arrival. Additionally, given the levels of uncertainty stemming from a variety of sources, risk analysis via Monte Carlo simulation and sensitivity analysis are integral parts of this tool. The analysis allows 90 percent confidence levels as part of the cost assessment process. Finally, DCET is a highly transparent tool since default parameters and values may be viewed and updated. The methodology for cost assessment adopted in this research is based on the factor cost method that involves identifying the components of vehicle costs, which vary with the amount of elapsed time (mostly wages, interest on capital employed or tied up in inventory on wheels, and licensing fees). It also considers inventory costs. Texas Transportation Institute Page 1

8 The Bridge of the Americas (BOTA) border crossing was adopted as a case example to illustrate the assessment of delay measures and cost implications. This choice of port of entry does not impact the validity of the application in any way. BOTA was selected for illustration because it provides a unique opportunity to draw upon near real time and archived radio frequency identification (RFID) data on bridge crossing times. RFID data for the duration July through September 2009 in the northbound direction from Mexico to the United States were used in this report. The value of high quality of data is important since the economic analysis is highly dependent on primary and secondary data sources to establish defaults and trends. At the front end, high quality crossing time data should allow improved delay performance measures. In regard to economic assessments, the research shows that direct costs of variability can be rather high for those in just-in-time systems and more than twice the cost of wages and other operating costs. In the case of BOTA northbound flows, the total daily costs for shippers and carriers jointly are estimated at $17,452 (delay evaluated relative to the mean) in the year These are direct variable costs to shippers and carriers. The cost per hour per truck for labor and other variable costs (not including other costs) is estimated at $39. The broader economic implications, administrative costs and social costs were not considered in this research. Economic costs and economic implications are important. Policy initiatives impacting delays must consider the balance. Security is critical at the borders, and a variety of other operational strategies may be adopted to manage delays but economic consequences are sometimes nontrivial. Hence, a balance must be struck. Texas Transportation Institute Page 2

9 CHAPTER I: TEXAS PORTS OF ENTRY AND NATURE OF FREIGHT MOVEMENTS IN THE EL PASO-JUAREZ BI-NATIONAL REGION INTRODUCTION This research report is an attempt to develop a quantitative assessment of potential economic impacts to the freight sector from border-related delays and wait times. While border security practices tend to increase wait times in the larger interest of safety and security of the nation, it is equally important to obtain an understanding of the potential implications to the freight sector and passengers from these practices so that appropriate measures may be undertaken at the border regions. This report focuses on the implications to the freight sector in the El Paso region with an aim to develop a quantitative simple and transparent model to ascertain the direct impact on the freight community that could indirectly spillover to the region. Texas Border Ports of Entry Figure I-1 shows the location of Texas border ports of entry. El Paso specifically has four international border ports of entry (POE). Appendix I-A discusses salient aspects of each POE in El Paso. Figure I-1. Texas-Mexico Border Ports of Entry (Commercial and Passenger) (Source: Texas State Comptroller) Texas Transportation Institute Page 3

10 Trading Partners and Trade through El Paso Border Ports of Entry Texas is the United States top trading partner both in terms of value and weight of imports and exports (Figures I-2 and I-3). Of the trade across the US-Mexico border, trade through El Paso ports ranks second in terms of trade value and fifth in terms of trade weight based on Bureau of Transportation Statistics, Transborder Statistics (BTS-TBS) 2009 statistics, and the pattern is similar in World Trade Magazine, 2010, also notes that El Paso ranks fifth in land trade compared to all major US-foreign trade gateways and points out that 25 percent of all US-Mexico trade crosses through the El Paso ports. The BTS data, however, suggests that approximately percent of all US-Mexico trade crosses through the El Paso ports. The largest volume of trade passes through the Laredo ports both by value and weight. This pattern has been holding steady over the past few years, as Figures I-4 and I-5 clearly show. Texas ports jointly process more that 80 percent of the total value of US-Mexico trade compared to other ports. Table I-1 shows the volumes of trucks moving through all US-Mexico ports, with Texas ports covering 67 percent of all commercial freight volumes. Figure I-6 shows Laredo ports servicing the highest volumes of commercial traffic at 50 percent in 2010, followed by El Paso ports at 22 percent. Texas Transportation Institute Page 4

11 - Figure I-2. Top Trading Partners (by Value and Weight 2009) (Source: BTS-TBS) Texas Transportation Institute Page 5

12 Figure I-3. Top Border Port Trading Partners (by Value and Weight 2009) Texas Transportation Institute Page 6

13 Figure I-4. Total Trade Flows for US-Mexico Ports ( ) (Source: Texas Center for Border Enterprise and Economic Development (TCBEED; texascenter.tamiu.edu) Figure I-5. Quarterly Trade Flows for US-Mexico Ports (2008) (Seasonal Peaks) (Source: Texas Center for Border Enterprise and Economic Development (texascenter.tamiu.edu) Texas Transportation Institute Page 7

14 Table I-1. Truck Volumes through All US-Mexico Ports of Entry (2010) Port Name Year Trucks Percentage Percentage AZ:Douglas , % AZ:Lukeville % AZ:Naco , % AZ:Nogales , % AZ:San Luis , % AZ:Sasabe % Arizona total: 7.9% CA:Andrade % CA:Calexico % CA:Calexico East , % CA:Otay Mesa , % CA:San Ysidro % CA:Tecate , % California: 23% NM:Columbus , % New Mexico: NM:Santa Teresa , % 1.8% TX:Brownsville , % TX:Del Rio , % TX:Eagle Pass , % TX:El Paso , % * TX:Fabens % TX:Hidalgo , % TX:Laredo ,585, % TX:Presidio , % TX:Progreso , % TX:Rio Grande City , % TX:Roma , % Texas: 67.3% Total ,742,925 * The highlighted categories show the regions with highest percentage of truck crossing volumes. Texas Transportation Institute Page 8

15 TX:Progreso 1% TX:Presidio 0% TX:Rio Grande City 1% TX:Roma 0% TX:Brownsville 7% TX:Del Rio 2% TX:Eagle Pass 3% TX:El Paso 22% TX:Laredo 50% TX:Hidalgo 14% TX:Fabens 0% Truck Volumes through Texas Ports 2010 Figure I-6. Truck Volumes Serviced through Texas Ports of Entry (2010) Understanding the Nature of Freight Movements in the El Paso-Juarez Bi-National Region and Other Ports Regional Integration Perspectives and Gateway Corridor Types The majority of freight shipped through the El Paso-Ciudad Juarez POE system is maquiladora trade. A maquiladora plant is a manufacturing facility located in Mexico that temporarily imports materials for assembly on a duty-free basis, provided the product is reexported. This arrangement has evolved into a system of transfer stations, distribution centers and warehouses on the United States side of the border, and manufacturing plants in Mexico. Below are two perspectives on ports of entry that are important to consider in any quantitative assessments of potential economic implications of delays. The first viewpoint is one of the patterns of regional integration that exist across border city pairs, including the El Paso-Juarez region. The second viewpoint is one that pertains to the nature of movements across the ports of entry and delay within the context of supply chain processes. Texas Transportation Institute Page 9

16 A Regional Economic Integration Perspective (Hansen, 2001) (1) Hansen notes that border cities appear to specialize in different tasks. Small border cities, such as Nogales in Arizona and Laredo in Texas, are mainly transshipment points in North American trade, while large border cities, such as San Diego, California, and El Paso, Texas, are major manufacturing sites. Smaller U.S. border cities function as intermediaries in U.S.-Mexico trade, providing transportation and distribution services. This specialization pattern may be determined, in part, by geography and preexisting supply networks. Laredo, for instance, is located on Interstate Highway 35, which is the major roadway linking Mexico to the eastern United States. It is perhaps not too surprising that intermediary services on the border expand with Mexican exports to the United States. Hansen also notes that there is anecdotal evidence that maquiladoras are an important source of demand for the output of manufacturing firms in U.S. border cities. Reports in the Twin Plant News, a trade publication that covers U.S. border industry, suggest that a large fraction of manufacturers in El Paso, McAllen, and Brownsville supply maquiladoras in Mexico with parts and components for the assembly of apparel, automotive products, and electronic appliances. These manufacturing activities represent a specific segment of the production process activities closely tied to product assembly. This line of research suggests that POE s can be differentiated along lines of freight activity they support: manufacturing as in El Paso Ports (McAllen and Brownsville) and intermediary goods transshipment as in Laredo. Regional integration suggests that futures for immediate neighbors in border pairs are connected. An impact on export manufacturing south of the border has effects on the economy in the neighboring border city. Degree indicates the strength of that effect. In the case of North America, Mexico s largest trading partner, the degree of integration is gradually increasing and based on access. US-Mexico border trade is currently somewhat less integrated than US-Canada trade. The implication is that cross-border trade, and across border city pairs occurs within regionally integrated systems and border delays must be considered in that specific context. At the least, this theory would suggest that the more regionally integrated the trade, the greater the potential broader economic implications and consequences from trade disruptions for tariff, nontariff barriers and transportation disruptions. However, that said, it remains a changing dynamic. Cambridge Systematics Study (2007) (2) According to a more recent North American Free Trade Agreement (NAFTA) study report by Cambridge Systematics et al. (2007), border POE s in Texas serve as intermediate activity centers in typically much longer distance moves between Mexican and U.S. origins and destinations. Texas gateway communities including their Mexican counterparts typically function in one of two ways in NAFTA supply chains either as a support center for transportation of locally produced manufactured goods or as an intermediate service center for goods transported long distances. El Paso and McAllen are the best examples of the first type of gateway community supporting local manufacturing in the fast-growing maquillage production cities of Ciudad Juarez, Chihuahua, and Reynosa, Tamaulipas, respectively. Laredo and Eagle Pass typify the long-distance service center typology. In most of these cases, warehouses and industrial distribution centers are located on either side of the border. Upon arrival in the border community southbound truck shipments, for example, are typically dropped in industrial parks Texas Transportation Institute Page 10

17 from which they are subsequently transferred across the U.S.-Mexico border by a local drayage carrier to a similar transfer or warehousing or manufacturing facility on the Mexican side. The same is true of northbound moves which are typically dropped off by a Mexican long-haul carrier at a brokerage warehouse in Mexico and then drayed to a similar facility on the U.S. side where a U.S. long-haul carrier retrieves the load and travels northward. Laredo is the best example of this type of move. Manufacturing-based gateway communities such as Ciudad Juarez or Reynosa generate fewer long-haul moves because the manufacturing or distribution activities occur near the border and serve growing urban populations (the Lower Rio Grande Valley and El Paso regions are home to more than 1 million and 750,000 residents, respectively). The report also notes that most long-haul freight that moves through El Paso heads to the West Coast. As it pertains to delays and freight movements, the Cambridge Systematics study points out the following: Trucking companies, brokers, and shippers realize that border congestion is an inevitable part of doing international business. Border delays differ at each port of entry, but are generally longer during peak crossing periods. At the crossings near Reynosa and Juarez, for example, the border delays correspond to production shifts at large border maquilas. Because the border crossing is part of the production supply chain infrastructure, the delays are tolerated and there is not yet enough delay to adversely affect production to the degree manufacturers would be spurred to action. Final assembled products travel north into the United States to a distribution center in the border region or other large Texas City. Southbound raw materials are either shipped directly to Mexican destinations or they are temporarily stored in warehouse facilities north of the border for shipment consolidation. A dray operator is typically used to move the shipment through the border for both northbound movements to US or southbound to Mexico. When maquila facilities are close to the border (Juarez or Reynosa, for example) southbound industrial inputs are transported by dray operators through the border directly to maquiladora facilities. These dray trips average miles in between warehouse/transfer and manufacturing facilities. Long-haul trips (Guadalajara or Puebla, for example) are transferred to Mexican long-haul carriers from dray operators after crossing the border. According to interviewees in the Cambridge study (5), raw materials bound for maquila facilities account for the majority of southbound NAFTA trips, with the remaining shipments comprised of consumer goods and general merchandise destined for interior Mexico. In both cases, shipments typically originate in the Midwest or the Southeast United States. Southbound commodities and assembly inputs originating in the United States commonly include automotive components from the Midwest, electrical components from the East Coast, textiles, aluminum, and steel. From overseas, paper, packaging materials and chemicals, heavy machinery and building materials. Northbound movements from Mexico include finished products include computers, auto parts, appliances, frozen and fresh produce, building materials such as lumber and stone, and a small percentage of handicrafts. Texas Transportation Institute Page 11

18 Both these studies suggest that freight movement patterns are significantly different across POE s. The critical identifiers across POE s are: The type of gateway corridor. Types of commodities traversing the border. The direction of movement with northbound flows comprised of finished goods and southbound toward Mexico characterized by intermediate goods. In regard to El Paso POE, the researchers have noted that: The freight movements support the manufacturing process. The trip lengths associated with border crossing movements are very short-haul movements from the wholesale transfer facilities on either side of the border. Despite part of a longer supply chain originating in different parts of the country, the movements around the border maquilas are typically self-contained. Delays might be tolerated within bounds because of the short-haul trip nature and because of the stage of the production supply chain that is involved in these movements. Kristjansson et al. (2010) (3) In the context of regional integration, Kristjansson et al. evaluate intra-industry trade along two cross-border trade gateways (Cascade Gateway and Great Lakes Corridor) along the US- Canadian border by way of the Grubel Lloyd index. One of their key findings based on the index is that the Great Lakes corridor is more integrated than the Cascade Gateway and much more reliant on truck transportation, making the corridor even more vulnerable to delay related economic costs and uncertainty in crossing times. While it is a well-accepted point that regions are regionally integrated in various degrees, this article shows that individual corridors may themselves vary in levels of intra-industry trade and extent of regional integration. A central thesis emerging from these studies is that levels of regional integration are strongly correlated with extent of economic impact in this case, economic implication from frictions or delays at the border. While individual corridors have not yet been evaluated for levels of regional integration along the US-Mexico border, there is evidence that indicates that United States trade with Mexico is much less regionally integrated than with Canada. Texas Transportation Institute Page 12

19 CHAPTER II: EL PASO PORTS OF ENTRY AND BORDERS AS COMPONENTS OF TRANSPORT COSTS AND ECONOMIC COSTS PORTS ARE NOT IDENTICAL Economic implications of delays and improvements to port infrastructure are all strongly related to what is moved and the nature of those movements. This is especially true for direct, indirect as well as induced effects of border inefficiencies. There are several freight related POE s along the Texas-Mexico border. Along the El Paso portion of the US-Mexico border, a length of approximately 45 miles, there are six ports-of-entry. Of these, only two ports, Bridge of the Americas (BOTA) and Ysleta-Zaragoza, handle commercial freight (Figure II-1). Passenger Ports Santa Teresa is located in Doña Ana County, New Mexico. The port of entry is connected to I-10 via the Pete Domenici Highway. Santa Teresa is a non-tolled facility. Paso Del Norte International Bridge (PDN) handles northbound and southbound automobile and pedestrian traffic. It connects to U.S. 85 via El Paso Street and Santa Fe Street. Stanton Street Bridge lies just east of the Paso Del Norte Bridge. It handles mostly southbound vehicular traffic but has one northbound Dedicated Commuter Lane. Fabens-Casita International Bridge is a small, light-duty bridge constructed in It connects to I-10 via FM 1109, Texas 20, FM 76, and FM 793. Commercial and Passengers Ports Bridge of the Americas is the primary port of entry in the El Paso region, handling more than half of all international crossing traffic (passenger and commercial). Ysleta-Zaragoza (Zaragoza) is located in eastern El Paso. It connects to I-10 via State Highway 375 (North Americas Avenue). This is a tolled crossing and accommodates both passengers and commercial freight. Commercial vehicles are tolled at $3.50 per axle, and pedestrians at $0.50. Northbound tolls are 23 pesos for passenger vehicles, 137 pesos for commercial vehicles (five axles), and 5 pesos for pedestrians. Texas Transportation Institute Page 13

20 Figure II-1. El Paso Border Ports of Entry Ports Vary in Terms of Commodity/Trade Profiles The freight related ports along the border are fundamentally different based on the kinds of freight movements they service. Figures I-4 and I-5 are indications of how ports can vary in terms of the value and weight they serve. For instance, Laredo serves high value cargo and also processes the most cargo by weight. El Paso ports rank second in terms of value moved but fifth in terms of weight. Laredo and El Paso serve high value maquiladora shipments. Laredo also serves a large fraction of non-maquila shipments that were originally under the IMMEX program of Mexico. Appendix 2 provides commodity profiles for some Texas ports of entry for both United States exports to Mexico (southbound flows) and Mexican imports to the United States (northbound flows). A significant portion of trade flows through El Paso ports (both directions, northbound and southbound) are maquila-related and a small percentage (<10 percent is agriculture-based) based on value data from Texas Center for Border Economics and Enterprise Development (TCBEED). The BTS data based on all traded commodities for Currently, however both Programa de Importación Temporal para Producir Artículos de Exportación- PITEX and IMMEX have merged under the broader regulatory category of IMMEX industry programs (which is more broadly known as the maquiladora industry). Texas Transportation Institute Page 14

21 2010 provide similar conclusions both in terms of value and weight. The value and weight profiles for El Paso ports are shown below in Figures II-2 (Total Import Weight Traded 2.9 million in US Short Tons or 2.6 billion Kilograms), II-3 (Total Import Value $27.2 billion), and II-4 (Total Export Value at $21 billion) and provide an indication of the industries being served. In fact, based on the full value and weight profile of all traded commodities, the following broad distribution of commodities appears to traverse through El Paso ports: o Manufacturing (maquila) (primarily intra-industry trade), Manufacturing (non-maquila), small percentage of agriculture, apparel and other products. Measuring and Testing Instruments, 2.1% Plastics and Articles, 3.6% Sugars and Sugar Confectionery, 2.8% Special Classification Provisions, 4.2% Furniture; Lamps and Prefabricated Buildings, 5.3% Ceramic Products, 6.1% Vehicles Other than Railway, 7.2%, 0, 0, 0, 0 Wood and Articles, 1.9% Electrical Machinery; Equipment and Parts, 26.7% Computer-Related Machinery and Parts, 19.3% Figure II-2. El Paso Ports Imports Weight Profile (2010) (US-Mexico Imports Northbound Flows) (Top Ten of 98 Truck Traded Commodities) (Source: BTS-TBS and Weight in US Short Tons) Texas Transportation Institute Page 15

22 Special Classification Provisions, 3.30% Vehicles Other than 1.42% Railway, 5.06% Furniture; Lamps and Prefabricated Buildings, 5.34% Plastics and Articles, Not Knitted or Crocheted Apparel, 1.21% Other Made up Textile Articles, 0.48% Impregnated Fabrics, 0.46% Measuring and Testing Instruments, 8.73% Electrical Machinery; Equipment and Parts, 42.97% Computer-Related Machinery and Parts, 25.89% Figure II-3. El Paso Ports Imports Value Profile (2010) (US-Mexico Imports Northbound Flows) (Top Eleven of 87 Truck Traded Commodities) (Source: BTS-TBS) Paper and Impregnated Fabrics, Paperboard, 2.2% 1.2% Aluminum and Vehicles Other than Articles, 2.1% Railway, 2.7% Articles of Iron and Steel, 2.6% Copper and Articles, 3.2% Measuring and Testing Instruments, 5.1% Plastics and Articles, 7.8% Meat and Edible Offal, 1.2% Dairy Products, 0.9% Electrical Machinery; Equipment and Parts, 36.0% Computer-Related Machinery and Parts, 23.2% Figure II-4. El Paso Ports Exports Value Profile (2010) (Top Eleven of 93 Truck Traded Commodities) (Source: BTS-TBS) Texas Transportation Institute Page 16

23 Ports Vary in Terms of Transport Corridors They Serve Mexico has four major transportation corridors: the Pacific, Chihuahua, Central and Gulf Coast. The El Paso ports serve the Chihuahua corridor that historically has been more significant for maquila trade. The Laredo crossing serves the Central Trade Corridor that is the most significant non-maquila corridor. Ports Vary in Terms of How They Move Goods Transport Components of Supply Chain Processes across Ports of Entry in Texas Transportation components of supply chain processes at work are of equal importance while attempting to understand any direct and broader economic implications from delays. Not all ports are identical in terms of the linkages they serve and/or the types of transport chains that have emerged/evolved in these regions over time. The supply chain for freight entering the U.S. from Mexico is a rather complicated one, because Mexican trucks are currently not permitted by law to operate beyond a 20-mile zone extending from the U.S.-Mexico border. Typically, goods coming from the interior regions of Mexico are shipped to a warehouse near the border, where they are offloaded into a warehouse. These warehouses are often owned by customs brokers or freight forwarders. Once paperwork is submitted for the goods to clear customs, a drayage carrier is notified to pick up the goods so the border crossing process can begin. Once the drayage carrier completes the inspection processes on both sides of the border, it delivers the goods to a warehouse on the U.S. side of the border (located within the 20-mile zone mentioned previously). At this point, the goods are ready to be transported by a U.S. carrier to their ultimate destination within the U.S. Figure II-5 below is a graphical representation of this process and is most representative of the second type of long-distance service center gateway corridor (Laredo, Eagle Pass). In such cases, there are possibilities of a bottleneck in one part of a transport chain to spill over to other parts with a cumulative effect. U.S.-Mexico Trade and Transportation: Corridors, Logistics Practices, and Multimodal Partnerships, LBJ School of Public Affairs, Policy Research Paper 113, Texas Transportation Institute Page 17

24 Figure 0-5. Mexican Import Supply Chain (Shipments Originating in Mexico s Interior) Not all of the shipments transiting through Laredo and Eagle Pass gateways are maquila. A large part of the shipments coming from inner Mexico regions are non-maquila type trade. On the other hand, a large majority of freight shipped through the El Paso-Juarez POE system is maquiladora trade. Figure II-6 below is a graphic representation of maquiladora trade supply chain (in El Paso, Texas.). Essentially, this movement may be considered a self-limiting part of an entire flow. Consequently, economic consequences may also be self- limiting even for a fairly regionally integrated system. This, however, will not be the case for more integrated supply chains or integrated systems, where a shock in one segment could have a ripple effect on other related moves. Texas Transportation Institute Page 18

25 Figure II-6. Maquiladora Supply Chains, El Paso-Juarez Region PORTS VARY IN TERMS OF FINAL DESTINATIONS THEY SERVE/TRADING PARTNERS (TRUCK TRADE FLOW DISTRIBUTIONS) Understanding the extent of trade is an important component of broader economic implications. Figure II-7 indicates that a large percentage of imports from Mexico flowing through El Paso ports remain within Texas (58 percent of total value) and other leading destinations include Michigan (10.5 percent) and California (6 percent of value). A somewhat similar distribution emerges by inbound weight flowing through El Paso ports (Figure II-8). Texas Transportation Institute Page 19

26 Minnesota(USA), 2.8% Ohio(USA), 3.7% California(USA), 6.0% Florida(USA), 1.6% Missouri(USA), 1.9% Pennsylvania(USA), 2.4% Illinois(USA), 2.1% Wisconsin(USA), 1.6% New Jersey(USA), 1.2% Tennessee(USA), 1.1% Michigan(USA), 10.5% Texas(USA), 57.7% Figure II-7. Top 12 of 48 Trading Partners by Import Value 2010 (Truck Inbound Flows- El Paso POE s) (Source: BTS-TBS) Wisconsin(USA), 2.7% Missouri(USA), 2.0% New Mexico(USA), 1.9% Georgia(USA), 1.2% Illinois(USA), 2.0% Massachusetts(USA), 1.2% Minnesota(USA), 2.9% Ohio(USA), 3.0% Pennsylvania(USA), 3.1% Connecticut(USA), 3.5% California(USA), 5.9% Texas(USA), 51.6% Michigan(USA), 9.1% Figure II-8. Top 12 of 48 Trading Partners by Import Weight 2010 (Truck Inbound Flows- El Paso POE s) (Source: BTS-TBS) Texas Transportation Institute Page 20

27 BORDERS AS COMPONENTS OF TRANSPORT COSTS AND LINKS TO LOGISTICAL EFFICIENCY Moving commodities across national borders can add costs (sometimes quite significant) to freight shipments between countries. These additional transportation costs result from several policy aspects including procedural, infrastructural, and political difficulties often encountered in the border clearance process (Anderson and van Wincoop, 2001, Beilock et al., 1996 (4, 5)). 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. It has been noted that as countries enter into trade agreements with each other, trade facilitation measures become important to facilitate smooth flows of goods. Border-related processes are often viewed as a trade facilitation measure (Matisziw, 2005 (6). For a more regionally integrated trade like US-Canadian trade, Anderson and van Wincoop (1) estimate that border-related barriers can be equated to a tariff of 50 percent and that if such barriers are removed, a trade increase of up to 79 percent could result. For freight shipments, issues involved in crossing international borders translate into increased transportation costs. As stated in Fox et al. (2004) (7), and Haralambides et al. (2004) (8), given the shipping/handling fees paid at border crossings, a very small span of road may economically become the geographic equivalent of several hundred miles, especially in the case of supply chain processes characterized by long-haul movements and with links to intermodal transfers. Factors Causing Delays Matisziw (6) provides an excellent discussion on various aspects leading to delays. He notes physical factors such as: design and layout of 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 sometimes, inadequate capacity to process vehicles. Also, noted in this category are topographic conditions surrounding border crossings as in Arizona. Matisziw notes note that these types of physical limitations tend to exacerbate traffic problems and delays. A second factor that is responsible for delays could be a slowdown in one of the various steps involved in the crossing process. Figure II-9 shows the various steps and a breakdown in any stage that can lead to delays. Figure II-10 is a schematic of the crossing process from a 2002 Texas Transportation Institute (TTI) study (Ojah,, 2002) (9). Texas Transportation Institute Page 21

28 Figure II-9. Typical Border Crossing Stages for US-Mexico Border Crossings (Source, Matisziw, 2005) Texas Transportation Institute Page 22

29 Figure II-10. Border Crossing Stages for US-Mexico Border (Source: Ojah et al., TTI Report 2002) A third aspect cited as a contributory factor is procedural aspects. For instance, trucks must pass through security and customs inspections along with processing of documents, which adds to delays. These procedural and security aspects increased after September Matisziw notes that lack of good interagency coordination/cooperation and information sharing increases process times. Other factors cited include capacity related issues like hours of operation in dealing with secondary inspections (Matisziw, 2005 (6); Taylor et al., 2003 (10)), inadequate staffing and a general notion that shipping speed is not critical. Texas Transportation Institute Page 23

30 Prior Literature, Perspectives in Assessing Economic Costs of Delay Based on what has been discussed, economic costs of delays must be motivated within the broader context of regionally integrated trade (which could be corridor-region specific) and supply chains of goods transiting national borders. Much of the literature attempting to focus on economic costs of delay fails to take into account these aspects. Based on a prior literature review report, Table II-1 summarizes the specific context or approach within which economic costs were examined. Texas Transportation Institute Page 24

31 Table II-1. Summary of Perspectives Adopted in Assessing Economic Costs of Delay Authors Approach Costs Region Aspects Considered Ojah et al. (2002) (9) HLB Decision Economics (2006, 2007 Mexicali): Economic Impacts & True North (11-17) HLB (2004) (Detroit Windsor [D-W]) (18) Belzer, 2003 (19, 20) Factor cost/direct costs Social Cost Congestion delays to others in queue. (Focus on effects of coordination to one or more stakeholders) Static/Microeconomic Partial equilibrium perspective Same as HLB 2006, 2007 Direct- Inputs and Environment Delay data, fuel prices, literature, time valuation, pollution costs. Indirect costs output and employment costs (macroeconomic) Indirect costs (macroeconomic) Several Ports along US- Mexico Border Mexicali Detroit- Windsor Factor costs Direct Ambassador Bridge and other bridges Delay is measured as excess over free flow time with travel time data collected from surveys. Use of Highway Design Model to obtain vehicle operating costs. Emission cost monetary values from Wang and Santini's study. Cargo type Directional aspect. Delays treated as a cost increase. Risk analysis. Direct, indirect and induced effect FAST lanes. Use of STRATBENCOST to develop volume and time forecasts for analysis of three bridges at the D-W border. Operating costs for trucks valued at $2.32 per minute and inventory transit costs. RTI International (2007) (21) Taylor et al. (2003) (10) OCC (2004) (22,23) Goodchild et al. (2007) (24) Kristjansson et al. (2010) (3) Fischer, 2010 (Cambridge Systematics) (25) Similar to HLB studies Administrative costs perspective Indirect costs (macroeconomic) Agency costs and other administrative crossing costs from uncertainties and delays (fees, duties) FAST lanes, Nogales, Arizona General Similar to HLB Canadian context Variability in delays No costs Specific Gateways Regional integrationintra-industry trade (Grubel Lloyd Index) (GLI) Vehicle hours traveled (delay) and partial equilibrium methods No costs Indirect costs (macroeconomic) Specific Gateways; Cascade Gateway, Great Lakes Corridor Canadian context Impact of the FAST lanes is the specific analysis goal (FAST lanes introduced in Nogales, in 2006) Carrier costs and manufacturer/shipper costs No economic costs reported. Links delay variability to output elasticity Implications of variations in GLI across corridors to economic costs of delays. No actual cost analysis conducted. Actual estimates of delays not reported. Methodology discussed. Texas Transportation Institute Page 25

32 Table II-2. Additional Perspectives on Wider Economic Implications and General Port Efficiencies Authors Approach Implications Limao and Venables (1999) (26) Hummels (2001) (27) Kent and Fox (2004) (28) 10% increase in transport costs associated with 20% reduction in trade volume. Inventory costs due to transport delays equivalent to 0.8% per day of delay of the value of goods delivered. Effects of port inefficiency on welfare Trade: Indirect benefit Inventory management: Direct cost from uncertainties. Applicable to ports like Laredo that are associated with longer haul moves. Haralambides and Kent (2004) (8) Huang and Whalley (2008) (29) Effects of port inefficiency on welfare Effects of port inefficiency on welfare Applicable to ports like Laredo that are associated with longer haul moves. Added inventory costs directly related to variance of delays. Under certainty, time costs are equal to inventory costs but under uncertainty, inventory costs are much higher. Types of Economic Costs The literature is clear in identifying at least five types of costs, as seen in Tables II-1 and II-2. These include: Direct costs owing to factors often assessed using factor cost methods. Administrative costs stemming from delays to agencies and stakeholders. Taylor et al. adopt this approach. Indirect costs or broader economic costs (partial equilibrium, general equilibrium approaches). Each approach makes implicit assumptions on trade relations between trading partners and on output responses with partial equilibrium methods typically having an upward bias in relaying effects of shocks. Social cost-environmental cost and includes costs stemming from emissions from trucks. Finally, there are further direct costs that accrue from more integrated systems from inventory management in just-in-time systems and costs from multi-modal transfers. Texas Transportation Institute Page 26

33 CHAPTER III: EL PASO FREIGHT MOVEMENTS FREIGHT MOVEMENT TRENDS EL PASO PORTS OF ENTRY El Paso, Texas, is currently the sixth largest city in the state of Texas and the twenty-first largest city in the United States. Ciudad Juarez, El Paso s sister city across the border, is the largest city in the state of Chihuahua and the fifth largest city in all of Mexico. The metropolitan area of Ciudad Juarez and El Paso, Texas, comprises more than 2.2 million people, making it the largest bi-national metropolitan area in the world. The large population is mostly due to the amount of jobs that the local manufacturing industry in the region produces. These manufacturing facilities, often referred to as maquiladoras, not only produce jobs but also produce goods that are ultimately shipped to and from the United States of America in significant volumes. Following the implementation of NAFTA, trade between the United States and Mexico increased substantially. The tables that follow show the trade patterns through El Paso Ports of Entry. The trends reflect trade through all ports of entry in the El Paso Bi-National Region and not of single POE. Table III-1 and Figures III-1 and III-2 indicate the trade trends by value and weight through the El Paso POE s with the entire United States and with Texas alone. With the exception of a dramatic change in weight profile of imports (inbound into the United States) from 2003 through 2007, the patterns of value and weight are generally similar. This could be due to a shift in distribution of composition of goods, or a variety of other considerations. Texas Transportation Institute Page 27

34 Texas Transportation Institute Page 28 Year Trader Partner Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and Weight) Port/District Code Port/District Description Imports Value by Truck (US Short Tons) Imports Weight by Truck (US Short Tons) Trader Imports Value by Truck Imports Weight by Truck (US Short Tons) 1995 USA MEXICO 2402 El Paso - Texas $11,815,007,045 1,453,483 Texas $5,253,472, , USA MEXICO 2402 El Paso - Texas $11,601,370,475 1,938,915 Texas $5,635,791,343 1,050, USA MEXICO 2402 El Paso - Texas $12,342,837,252 1,919,563 Texas $5,655,309, , USA MEXICO 2402 El Paso - Texas $14,609,540,221 2,163,031 Texas $6,253,885, , USA MEXICO 2402 El Paso - Texas $16,822,150,647 2,303,713 Texas $8,026,982,212 1,194, USA MEXICO 2402 El Paso - Texas $19,162,738,608 2,431,439 Texas $9,172,475,227 1,253, USA MEXICO 2402 El Paso - Texas $19,156,612,097 2,444,918 Texas $8,900,508,521 1,169, USA MEXICO 2402 El Paso - Texas $19,762,057,224 2,393,390 Texas $9,620,016,010 1,161, USA MEXICO 2402 El Paso - Texas $19,745,171,951 2,396,149 Texas $9,312,135,706 1,123, USA MEXICO 2402 El Paso - Texas $21,875,628,271 3,618,372 Texas $12,155,269,477 2,279, USA MEXICO 2402 El Paso - Texas $22,216,587,475 3,463,483 Texas $11,246,226,743 2,025, USA MEXICO 2402 El Paso - Texas $23,528,112,532 3,419,745 Texas $11,429,703,442 1,906, USA MEXICO 2402 El Paso - Texas $25,949,296,025 3,054,959 Texas $12,320,195,844 1,742, USA MEXICO 2402 El Paso - Texas $24,803,329,148 2,861,107 Texas $13,251,291,021 1,595, USA MEXICO 2402 El Paso - Texas $21,156,892,085 2,261,460 Texas $11,579,415,114 1,248, USA MEXICO 2402 El Paso - Texas $27,168,727,215 2,878,355 Texas $15,684,759,847 1,485,439 Source; BTS-Transborder Statistics.

35 $30,000,000,000 $25,000,000,000 $20,000,000,000 $15,000,000,000 $10,000,000,000 $5,000,000,000 Imports Value by Truck_Entire USA Imports Value by Truck_Entire Texas Linear ( Imports Value by Truck_Entire USA) Linear ( Imports Value by Truck_Entire Texas) $ Figure III-1. Trends in Import Value through El Paso Ports of Entry (with USA and with Texas Alone) 4,000,000 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000, ,000 Imports Weight by Truck (US Short Tons)_Entire USA Imports Weight by Truck (US Short Tons)_Entire Texas Linear ( Imports Weight by Truck (US Short Tons)_Entire USA) Linear ( Imports Weight by Truck (US Short Tons)_Entire Texas) Figure III-2. Trends in Import Trade Weight through El Paso Ports of Entry (with Entire USA and with Texas Alone) (Short Tons) Texas Transportation Institute Page 29

36 Table III-2. Northbound Crossing Volumes (Trucks) (El Paso Ports of Entry) and by Loaded or Empty Port Year Trucks (Number) Bridge of America (BOTA) Ysleta Loaded Truck Containers (Number) TX:El Paso , , ,000 NA NA Empty Truck Containers (Number) TX:El Paso , , , , ,479 TX:El Paso , , , , ,006 TX:El Paso , , , , ,036 TX:El Paso , , , , ,394 TX:El Paso , , , , ,812 TX:El Paso , , , , ,638 TX:El Paso , , , , ,738 TX:El Paso , , , , ,860 TX:El Paso , , , , ,152 TX:El Paso , , , , ,083 TX:El Paso , , , , ,769 TX:El Paso , , , , ,863 TX:El Paso , , , , ,988 TX:El Paso , , , , ,777 SOURCE: U.S. Department of Transportation (USDOT), Research and Innovative Technology Administration, Bureau of Transportation Statistics, Border Crossing/Entry Data; based on data from U.S. Department of Homeland Security, Customs and Border Protection, Operations Management Report database. The University of Texas at El Paso (University of Texas El Paso) Border Region Modeling Project. The total number of trucks crossing the ports from Juarez shows a steady incremental rise with a dip in 2009 reflective of the recession. The total number is nearly evenly distributed between the Bridge of the Americas and Ysleta Bridge. The splits between loaded and unloaded truck containers show a large percentage of empty trucks transiting the ports. From an economic standpoint, empty trucks are reflective of a pickup/delivery system and need to be treated differently relative to loaded carriers. Texas Transportation Institute Page 30

37 Table III-3. El Paso Ports Import Classification and Value (2010) ** Commodity Code Commodity Description 2010 Percentage of Total Import 1 Live Animals $3, % 3 Fish and Crustaceans $2, % 4 Dairy Products $675, % 5 Products of Animal Origin $2,277, % 6 Live Trees and Plants $258, % 7 Edible Vegetables and Roots $14,365, % 8 Edible Fruit and Nuts $116,794, % 9 Coffee; Tea and Spices $921, % 10 Cereals $10, % 11 Malts; Starches and Inulin $388, % 12 Oil Seeds and Oleaginous Fruits $196, % 14 Vegetable Plaiting Materials $127, % 16 Preparations of Fish and Meat $3,427, % 17 Sugars and Sugar Confectionery $49,897, % 18 Cocoa and Cocoa Preparations $14,545, % 19 Preparations of Cereals and Flour $19,920, % 20 Preparations of Vegetables; Fruits and Nuts $19,308, % 21 Miscellaneous Edible Preparations $898, % 22 Beverages; Spirits and Vinegar $1,872, % 23 Food Residues and Waste $23, % 25 Salt; Sulfur; Plaster and Cement $2,938, % 26 Ores; Slag and Ash $11, % 27 Mineral Fuels; Oils and Waxes $347, % 28 Inorganic Chemicals $10,296, % 30 Pharmaceutical Products $8,398, % 31 Fertilizers $880, % 32 Tanning or Dyeing Extracts $564, % 33 Essential Oils and Resinoids $791, % 34 Soap and Organic Surface-Active Agents $11,183, % 35 Albuminoidal Substances; Glues and Enzymes $49, % 36 Explosives $649, % 37 Photographic Goods $382, % 38 Miscellaneous Chemical Products $32,471, % 39 Plastics and Articles $329,079, % ** BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to United States. Texas Transportation Institute Page 31

38 Table III-3. El Paso Ports Import Classification and Value (2010) (continued) Commodity Code Commodity Description 2010 Percentage of Total 40 Rubber and Articles $101,930, % 41 Raw Hides and Skins $8,399, % 42 Articles of Leather and Handbags $5,054, % 43 Furskins and Artificial Fur $1, % 44 Wood and Articles $62,730, % 47 Pulp of Wood and Paperboard $1,401, % 48 Paper and Paperboard $83,986, % 49 Printed Books $75,800, % 52 Cotton $1,470, % 54 Man-made Filaments $2,951, % 55 Man-made Staple Fibers $1,054, % 56 Wadding; Felt and Nonwovens $15,382, % 57 Carpets and Other Textile Floor Coverings $190, % 58 Special Woven Fabrics $2,243, % 59 Impregnated Fabrics $124,937, % 60 Knitted or Crocheted Fabrics $195, % 61 Knitted or Crocheted Apparel $74,376, % 62 Not Knitted or Crocheted Apparel $387,018, % 63 Other Made up Textile Articles $130,098, % 64 Footwear $7,580, % 65 Headgear $1,298, % 66 Umbrellas and Walking Sticks $148, % 67 Feathers and Down $6, % 68 Stone; Plaster; Cement and Asbestos $31,767, % 69 Ceramic Products $37,894, % 70 Glass $40,882, % 71 Pearls; Stones; Metals and Imitation Jewelry $14,239, % 72 Iron and Steel $13,745, % 73 Articles of Iron and Steel $87,341, % 74 Copper and Articles $40,785, % 75 Nickel and Articles $795, % 76 Aluminum and Articles $115,592, % 78 Lead and Articles $858, % BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to United States. Texas Transportation Institute Page 32

39 Table III-3. El Paso Ports Import Classification and Value (2010) (continued) Commodity Code Commodity Description 2010 Percentage of Total 79 Zinc and Articles $372, % 80 Tin and Articles $1,271, % 81 Other Base Metals and Cermets $611, % 82 Tools of Base Metal $1,457, % 83 Miscellaneous Articles of Base Metals $104,995, % 84 Computer-Related Machinery and Parts $7,032,763, % 85 Electrical Machinery; Equipment and Parts $11,674,763, % 86 Locomotives and Traffic Signals $584, % 87 Vehicles Other than Railway $1,374,454, % 88 Aircraft; Spacecraft and Parts $39,320, % 89 Ships and Boats $8,360, % 90 Measuring and Testing Instruments $2,370,886, % 91 Clocks; Watches and Parts $34,503, % 92 Musical Instruments and Parts $126, % 93 Arms and Ammunition and Parts $3,505, % 94 Furniture; Lamps and Prefabricated Buildings $1,451,488, % 95 Toys; Games and Sport Equipment $37,710, % 96 Miscellaneous Manufactured Articles $17,283, % 97 Works of Art and Antiques $278, % 98 Special Classification Provisions $897,872, % TOTAL $27,168,727, % BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to United States. Texas Transportation Institute Page 33

40 Table III-4. El Paso Port Export Classification and Value (2010) Commodity Code Commodity Description 2010 Percentage of Total 1 Live Animals 2 Meat and Edible Offal 3 Fish and Crustaceans 4 Dairy Products 5 Products of Animal Origin 6 Live Trees and Plants 7 Edible Vegetables and Roots 8 Edible Fruit and Nuts 9 Coffee; Tea and Spices 10 Cereals 11 Malts; Starches and Inulin 12 Oil Seeds and Oleaginous Fruits 13 Lac; Gums; Resins and Saps 14 Vegetable Plaiting Materials 15 Animal or Vegetable Fats and Oils 16 Preparations of Fish and Meat 17 Sugars and Sugar Confectionery 18 Cocoa and Cocoa Preparations 19 Preparations of Cereals and Flour 20 Preparations of Vegetables; Fruits and Nuts 21 Miscellaneous Edible Preparations 22 Beverages; Spirits and Vinegar 23 Food Residues and Waste 24 Tobacco and Manufactured Tobacco 25 Salt; Sulfur; Plaster and Cement 26 Ores; Slag and Ash 27 Mineral Fuels; Oils and Waxes 28 Inorganic Chemicals 29 Organic Chemicals 30 Pharmaceutical Products 31 Fertilizers 32 Tanning or Dyeing Extracts 33 Essential Oils and Resinoids 34 Soap and Organic Surface-Active Agents 35 Albuminoidal Substances; Glues and Enzymes $4,851, % $246,555, % $1,902, % $184,849, % $15,392, % $257, % $24,580, % $65,628, % $596, % $6,001, % $4,312, % $14,270, % $52, % $35, % $30,810, % $9,088, % $59,646, % $11,012, % $27,588, % $15,018, % $37,880, % $16,444, % $7,824, % $153, % $4,049, % $60,762, % $140,444, % $24,900, % $23,167, % $53,307, % $2,937, % $49,241, % $6,506, % $20,689, % $27,680, % Southbound flows from United States to Mexico. Texas Transportation Institute Page 34

41 Table III-4. El Paso Port Export Classification and Value (2010)*** (continued) Commodity Code Commodity Description 2010 Percentage of Total 36 Explosives 37 Photographic Goods 38 Miscellaneous Chemical Products 39 Plastics and Articles 40 Rubber and Articles 41 Raw Hides and Skins 42 Articles of Leather and Handbags 43 Furskins and Artificial Fur 44 Wood and Articles 45 Cork and Articles 47 Pulp of Wood and Paperboard 48 Paper and Paperboard 49 Printed Books 50 Silk 51 Wool and Animal Hair 52 Cotton 53 Other Vegetable Fibers and Paper Yarn 54 Man-made Filaments 55 Man-made Staple Fibers 56 Wadding; Felt and Nonwovens 57 Carpets and Other Textile Floor Coverings 58 Special Woven Fabrics 59 Impregnated Fabrics 60 Knitted or Crocheted Fabrics 61 Knitted or Crocheted Apparel 62 Not Knitted or Crocheted Apparel 63 Other Made up Textile Articles 64 Footwear 65 Headgear 66 Umbrellas and Walking Sticks 67 Feathers and Down 68 Stone; Plaster; Cement and Asbestos 69 Ceramic Products 70 Glass 71 Pearls; Stones; Metals and Imitation Jewelry $62, % $39,781, % $49,224, % $1,640,134, % $169,182, % $29,377, % $33,051, % $79, % $61,238, % $41, % $21,050, % $453,054, % $58,330, % $15, % $2,243, % $81,663, % $79, % $88,002, % $36,816, % $104,832, % $20,631, % $31,693, % $261,441, % $23,356, % $36,680, % $39,933, % $46,200, % $447, % $1,594, % $720, % $231, % $23,037, % $20,532, % $73,092, % $25,754, % *** Southbound flows from United States to Mexico. Texas Transportation Institute Page 35

42 Table III-4. El Paso Port Export Classification and Value (2010) (continued) Commodity Code Commodity Description 2010 Percentage of Total 72 Iron and Steel $156,779, % 73 Articles of Iron and Steel $541,659, % 74 Copper and Articles $677,844, % 75 Nickel and Articles $12,543, % 76 Aluminum and Articles $436,644, % 79 Zinc and Articles $9,723, % 80 Tin and Articles $14,851, % 81 Other Base Metals and Cermets $20,677, % 82 Tools of Base Metal $50,877, % 83 Miscellaneous Articles of Base Metals $109,689, % 84 Computer-Related Machinery and Parts $4,875,763, % 85 Electrical Machinery; Equipment and Parts $7,568,936, % 86 Locomotives and Traffic Signals $2,774, % 87 Vehicles Other than Railway $565,377, % 88 Aircraft; Spacecraft and Parts $54,933, % 89 Ships and Boats $143, % 90 Measuring and Testing Instruments $1,082,382, % 91 Clocks; Watches and Parts $2,193, % 92 Musical Instruments and Parts $345, % 93 Arms and Ammunition and Parts $2,572, % 94 Furniture; Lamps and Prefabricated Buildings $118,578, % 95 Toys; Games and Sport Equipment $22,842, % 96 Miscellaneous Manufactured Articles $17,276, % 97 Works of Art and Antiques $143, % 98 Special Classification Provisions $796, % TOTAL $21,020,132, % Imports and exports to the United States El Paso region in 2010 are predominantly composed of computer and electronic equipment. Appendix 2 Tables VIII-4 and VIII-8 describe the breakdowns further based on TCBEED data and indicate that exports are broadly comprised of parts and intermediate goods, while imports are comprised mostly of parts and finished consumer durables. Southbound flows from the United States to Mexico. Texas Transportation Institute Page 36

43 PROXIMITY OF MAQUILAS TO BORDER PORTS OF ENTRY An interesting point to be made is the proximity of Juarez maquiladoras to specific border ports more specifically to industrial zones bounded by the Bridge of the Americas and Zaragoza (shown in Figure III-3). The implications of this location suggest the following: With current networks, delays and inefficiencies at BOTA and Zaragoza will be of importance to maquila stakeholders. One of the major goals of maquilas as profit maximizing entities striving for competitive positions is the maximization of truck trips (pickups and deliveries) in any given day. Most of these companies operate short-haul trips with approximately 2-3 round trips (or 4-6 individual crossings per day). This observation is similar to that reported by the 2007 Cambridge Systematics Study. Figure III-3. Location Distribution of Juarez Maquiladoras Relative to Border Ports of Entry (Source: Source: Maquila Stakeholder meeting with Cambridge Systematics, TTI in El Paso, November Texas Transportation Institute Page 37

44 CHAPTER IV: PERCEPTIONS ON BORDER DELAYS: EVIDENCE FROM SHIPPERS IN THE EL PASO JUAREZ REGION SHIPPER SURVEYS Shipper interviews were developed to understand the nature of freight movements in the El Paso-Juarez border region and with intent to understand the implications of border-related delays. The focus of the interviews was to capture information related to cross-border operations in the El Paso-Ciudad Juarez region. Interviews were conducted both in person and over the phone. The actual interview instrument is included in Appendix 3. Given the characteristics of the border crossing activity, a convenience sample of nine shippers was selected to analyze border activities. Seven of the eight companies listed below were maquiladora companies and the actual names are not indicated per Institutional Review Board guidelines. The selected interviewees comprised of: Three companies involved in the production of television sets (consumer durables) and other appliances, Two companies dedicated to computer parts and components; One company dedicated to automotive parts production; One company dedicated to the production of telecommunication devices and one company dedicated to food production specifically including refreshments and edible goods. One company dedicated to data and information services. Most of the respondents were certified under Customs-Trade Partnership against Terrorism (C-TPAT) at the time of the interviews. However, two of the shippers were not certified and had issues with certification at the time of the interview. Issues Identified by Shippers Seasonal Fluctuations and Peak Periods: Maquiladora managers that produce appliances and electrical components have observed peak crossing wait times at 8:00am and then again from 3:00pm to 6:00pm, and seasonal peaks from October to November. For those that produce refreshments, the demand was noted to peak during June to September. For data services, the peak season was noted to be during the holiday season, while the rest did not observe major fluctuations. Contract Terms Do Not Allow Cost-Shifting: In many cases, freight terms are freight-onboard (FOB) in El Paso warehouses. When cargo arrives in El Paso, costs of delays are a sender cost typically. Final costs are rarely ever passed on to final consumers. Texas Transportation Institute Page 38

45 Average Truck Costs: Shippers provided a range of responses on average per hour truck costs ranging from $30- $100. Additional Administrative Fees: In addition, maquiladora senders do incur additional costs that go from 12 to 100 dollars at customs offices, depending on specific procedures followed there. Cross-Cutting Issues: The logistical requirements and complexities faced by businesses and maquiladoras vary significantly. There are a few cross-cutting issues that emerged frequently in discussions with shippers and carriers. These issues have important implications for the business climate and economic future of the region precisely because they bear directly on either the cost of doing business or the ability to expand business operations to meet the demands of the binational region. The most significant cross-cutting issues include the following: Unpredictable/Variable Crossing Times are an Issue for Some Shippers. Depending on the bridge and the hour, most managers agreed that the waiting times can go from 30 minutes to up to five hours. Such delays affect maquiladoras where some managers usually have to increase the buffer time. Some shippers have adjusted to the delays and congestion at ports by building in buffer times in their business process. For instance, a few shippers indicated buffer times from 1 hour to 2 hours in the interviews. This is an effective strategy, however, given the need to maintain a profit maximizing number of truck trips the variability in the border crossing process may impact the number of trips. As trade volumes rise, these variabilities can impose costs on operations. Increased Costs of Inventory Management and Control for Some Shippers/Businesses. Most of the efficiencies in supply chain management over the past decade have been attributable to advances in inventory control and management of materials, components, and finished goods in the supply chain. Tight inventory controls and accurate accounting for inventory flows are a factor in both achieving profit margins and, arguably, the ability of the national and regional economies in many parts of the US to weather business cycles. However, the effects of delays tend to erode the significant progress made in inventory management and control by reintroducing uncertainty in shipping and receiving attributable to the border crossing process. The result can be a fallback to looser scheduling, lower targets and additional inventory to allow for uncertainty in delivery time. Texas Transportation Institute Page 39

46 Typical Supply Chain Raw materials and components come from Asia to California and from California to El Paso and Juarez. Finished product goes from Juarez to El Paso and to the rest of the U.S. Raw materials and components come from inner Mexico to Juarez. Finished product goes from Juarez to El Paso and to the rest of Texas and California Raw materials and components come fromel Paso to Juarez. Finished product goes from Juarez to El Paso. Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of Raw Materials/Intermediate Goods and Final Goods (Number Responding) Product Table IV-1. Origin/Destination of Commodities Identified by Shippers Origin Location/ Facility Destination Location/ Facility Product Origin Location/ Facility Destinati on Location/ Facility # Shippers Responding Raw Materials Electronic parts Inbound(I) I Asia Ciudad Juarez Finished Goods, Electronics Outbound (O) O Ciudad Juarez USA 5/9 Raw Materials Electronic parts, and Textiles I USA Ciudad Juarez Finished Goods, Electronics O Ciudad Juarez USA 3/9 Raw Materials I Inner Mexico Ciudad Juarez Refreshmint O Ciudad Juarez USA 1/9 Texas Transportation Institute Page 40

47 Hours Variation in Travel Times maximum average minimum Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number) Texas Transportation Institute Page 41

48 Daily Fluctuation No Significant Variation Peak in the morning around 8.00 am Peak in the afternoon around 4.30 pm 0 Varies all through the day Figure IV-3. Daily Peaks Identified by Respondents Seasonal Fluctuation No Significant Variation June-September October-December Daily Variation Figure IV-4. Seasonal Peaks Identified by Shippers Texas Transportation Institute Page 42

49 How the Supply Chain is Affected No major disruption 25% 12% Hire air carrier 13% 50% Adjust supply chains Incur delay Figure IV-5. Impacts on Delay on Supply Chains Who Absorbs the Costs of Delays? Costs absorbed by Company Costs absorbed by client for expedited delivery Cost absorbed by the final customer Figure IV-6. Shipper Responses on Ability to Pass Cost Increases Texas Transportation Institute Page 43

50 CHAPTER V: FRAMEWORK TO EVALUATE DIRECT COSTS OF BORDER CROSSING INEFFICIENCIES TO SHIPPERS AND CARRIERS FRAMEWORK COMPONENTS Based on the El Paso trade and commodity profiles, Chapter II provides a broad framework for evaluating direct economic implications that would accrue to shippers and carriers as system users and stakeholders and as part of a regional economy. Much of this can be subsequently related to broader implications in later stages, to broader social impacts, and to other costs; however, that discussion is not part of this research report. Quantifying impacts to other stakeholders is also not part of this report. Commodity/Trade Profiles by Direction of Flow Broad findings from earlier chapters suggest that: El Paso is a significant crossing point both in terms of value and weight for all US- Mexico trade. Laredo ports supersede El Paso ports in terms of their economic significance. A significant portion of trade through El Paso ports is Maquila related trade. Truck crossings involve a number of short trips to shippers/receivers on the other side of the border that transport the product to other destinations. A very small percentage of cargo traversing the borders is non-maquila trade and is comprised of other manufacturing products, textiles and agriculture. In other words, the broad commodity pattern of flows is somewhat similar for both directions of travel northbound and southbound. The fundamental difference is that just-in-time characteristics are more significant with finished good products relative to intermediate goods that travel to the shipper /receiver for final shipment. Other POE s can be analyzed similarly for their trade profiles. Appendix 2 profiles trade profiles for other POE s along the Texas-Mexico border based on Texas Center for Border Economic and Enterprise Development (TCBEED) data for imports and exports for several ports of entry. This may be complemented by BTS data since TCBEED data only cover the top 25 products in value. A large percentage of trucks travel empty based on Table III-2 in the northbound (NB) direction. This has direct implications as a social/environmental cost but is not a direct cost to a shipper/carrier. This can be easily approximated using simple methods based on emission factors of trucks and damage cost parameters. (See Ojah et al., 2002) (25). There will be no further discussion of this aspect in this report. Data Needs to Quantify Direct Costs and Definitions of Delay The time spent in crossing a border is an important element in assessing direct costs and other costs. However, not all time spent in the crossing process translates to a cost. The economic implications stem from inefficiencies in the process or time in excess of a threshold crossing time in other words, the focus is only on unanticipated delay. Prior research like that conducted by Ojah et al. (2002) has noted this as well. Unanticipated delay is generally Texas Transportation Institute Page 44

51 more costly than the same amount of anticipated delay. In terms of trucking costs, unanticipated delays can result in cost increases because of missed connections, as when a vehicle arrives too late for a pickup, leaving the vehicle and driver with some dead time. In practice, carriers cope with the risk of unanticipated delays by building buffer time into their schedules. Whatever the carrier s strategy, difficulty in predicting delays adds to the costs of trucking operations. (Ojah et al., 2002). More recently, because of costs to several stakeholders, there have been significant initiatives in terms of data inventories of crossing time data based on innovative data collection methods (see Rajbhandari et al., 2009, for instance (31)). This research relies on radio frequency identification data collected at El Paso Ports of Entry to be used to develop measures of delay. More specifically, this report focuses on the development of the approach based on RFID data. The actual measures developed for delay are dependent on the RFID collection itself and the placement of the readers. At the time of the report development, there were only two tags collecting the data (one on either sides of the border). General Layout of the Inbound (NB) Traffic at BOTA POE The BOTA land POE is a gateway between El Paso, Texas, and Ciudad Juarez, Chihuahua. The bridge is used for truck and passenger vehicle movements. The northbound passenger vehicles and commercial trucks cross the bridge by separated lanes. Commercial vehicles enter the Mexican export facility through the entering point where the first RFID reader is located, as shown in Figure V-1 (R1). After crossing the bridge, trucks advance to the U.S. federal inspection facility where the entering lanes are split into FAST traffic and non-fast traffic. After clearing the federal and state inspection facilities they merge onto Gateway Boulevard North, which provides access to US 54 or I-10. The second reader (R2) is located right after the trucks cross the state inspection facility. The operational hours for commercial traffic at BOTA are from 6 AM to 6 PM Monday through Friday and from 6 AM to 2 PM on Saturday. More details are available in Appendix 1. Texas Transportation Institute Page 45

52 U.S. Federal Inspection Facility RFID Reader R2 Texas State Inspection Facility Mexican Export Facility RFID Reader R1 Figure V-1. Map of BOTA Crossing Facilities (2009) Crossing Times by Direction of Flow RFID Data Collection BOTA is equipped with two RFID reader stations, R1 few miles south of the Mexican export inspection facility and R2 at the exit of the state inspection facility on the U.S. side. The readers read RFID tags installed in trucks with time stamps and send the data to a central location via a data communication link. The collected RFID raw data are filtered in the central system at the Texas Transportation Institute s El Paso, Texas, office to match the unique IDs from R1 and R2 stations. The crossing time of a truck is then calculated from the time difference from R1 to R2. In order to avoid the outliers among the matched RFID crossing time data, a 120-minute cap was used by the RFID collection team (Rajbhandari et.al, 2009, 30) to filter RFID records with longer than the cap. This report used the same filtered data to evaluate and build upon. After a matching and filtering process, a set of 23,381 records was collected between July 2009 and December 2009 at BOTA (Rajbhandari; TTI, Battelle et al, 2008, 2010) (31,32, 33). It is currently planned to have an additional RFID reader station installed near the federal inspection booths. The third reader would allow capturing more detailed crossing time observations by segment and by FAST and Non-FAST lanes. Usually, FAST trucks have shorter border wait times at the federal inspection facility compared to standard laden trucks and, therefore, will have less delay costs. Compared to the RFID crossing times, it should be mentioned that U.S. Customs and Border Protection (CBP) posts border wait times for 28 Canadian border ports of entry and 42 Mexican border ports of entry on their website ( The border crossing time is defined by CBP as wait time to reach the primary inspection booth, the first point of contact with CBP when crossing the Canada/U.S. Texas Transportation Institute Page 46

53 and Mexico/U.S. land borders. In contrast, with RFID data the crossing time is noted as time between the bridges to the primary inspection booth. The CBP border wait time is useful to understand the travel behaviors in general as it contains the information about the maximum lanes, number of current open lanes, and wait times by modes such as standard/fast commercial vehicles, standard/sentri passenger vehicles and pedestrians. However, CBP border wait time does not include the crossing times before U.S. border from the Mexican exporting lots. Another limitation of CBP border wait times is temporal resolution of one-hour. Current one-hour refresh rate is perhaps inadequate to capture the dynamic changes of the border crossing activities. RFID Counts of NB Truck Crossings Figure V-2 shows the hourly number of RFID readings collected from July 2009 through December 2009 at the Mexican entering point and the El Paso exit point. In Figure V-2 (A), it is generally observed that there are peak periods in the morning hours and in the late afternoon hours at the Mexican entering point. This observation is consistent with the stakeholder observations we received. However, the second graph (B) shows a more uniformly distributed exiting truck volume, though there are still peak periods in the morning hours. The reason for flattened peaks is because the incoming trucks have to pass the federal and state inspection stations after they across the bridge. Even though service rates of the federal and state inspection stations are not known, it is known that the number of booths are managed dynamically to cope with the changes of incoming traffic volume. Notice that the graphs do not necessarily show the true patterns of the influx and efflux at the POE. It is because the RFID readers capture only part of the whole truck volumes. Not all trucks have RFID installed and some observations are lost during the matching/filtering process. Figure V-3 shows the numbers of 2009 NB truck crossings at BOTA along with the RFID counts after July As shown in the plot, the RFID samples captured about 13 percent of the whole NB truck crossings during the sampling period. Texas Transportation Institute Page 47

54 Total Hourly RFID Counts at Entering Point Total Hourly RFID Counts at Exit Point July 500 July Aug Sep Oct Aug Sep Oct Nov Dec Nov Dec (A) At Entering Point (B) At Exit Point Figure V-2. Number of RFID Readings at El Paso BOTA Entering and Exiting Points (Weekday BOTA RFID Readings between July and December 2009) Monthly NB Truck Crossings at BOTA Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Actual NB Trucks RFID Counts Figure V-3. Monthly NB Truck Crossing and RFID Counts at BOTA Border Crossing Times Measured by RFID System Figure V-4 shows the average northbound truck crossing times from RFID data collected between July 7, 2009, and December 31, 2009, at the BOTA POE. The crossing times are averaged values and are not able to discriminate empty and nonempty trucks or FAST and Non- FAST trucks just yet. However, advances in filtering and classification methods applied to RFID data may soon be able to provide that disaggregation. Note that the pattern of average crossing time in Figure V-4 does not necessarily match the pattern of number of northbound trucks since capacity or the number of open lanes is altered at CBP s discretion in order to handle incoming traffic volumes. In Figure V-4, the month of October has the highest traffic volume, while average border crossing time by RFID observations shows a decrease from the previous month. Texas Transportation Institute Page 48

55 Average Crossing Time (minutes) Number of NB Trucks Crossing Time (minutes) 35,000 30,000 25,000 20,000 15,000 10,000 5, NB Truck Volume Avg. Crossing Time (RFID Obs.) Figure V-4. Monthly NB Truck Volumes and RFID Average of Crossing Times at BOTA (2009) Figure V-5 shows the average crossing time increasing until the 9:00AM-10:00AM period and has a decreasing pattern until the end of the operation hours. The graph shows a fairly stable pattern of standard deviation about half of the average values. Figure V-6 compares the hourly average crossing times from July to December It indicates that August had the longest crossing time during the 9:00-10:00 AM duration, while November showed the best performance in terms of average border crossing time Period (Hour) Average of Crossing Time StdDev of Crossing Time Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID Data July-December 2009) Texas Transportation Institute Page 49

56 Average Crossing Time (minutes) July Aug Sep Oct Nov Dec 0 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 Period (hour) Figure V-6. Hourly Average of Crossing Times: Comparison by Month (2009) Figure V-7 illustrates the average of crossing times and RFID counts by day of week during the whole sample period. The average crossing times range between 45 minutes and 50 minutes. This is consistent with the findings of a recent study by Accenture Group et al. (34) who note, BOTA s mean wait time 12 of 48 minutes in The same report also notes Ysleta s mean wait time as 47 minute with Free and Secure Trade (FAST) trucks wait times lower than empty and non-fast trucks. Based on the graph, there does not appear to be a significant day-of-theweek effect just by looking at average times. As mentioned earlier, the RFID counts do not necessarily reflect the actual trend of the traffic volumes. 12 The Accenture Group Report (2008) uses wait time interchangeably with crossing times. Texas Transportation Institute Page 50

57 Average Crossing Time (minutes) RFID Counts Monday Tuesday Wednesday Thursday Friday Average of Crossing Time Count of RFID Figure V-7. Average of Crossing Times by Day of Week (July-December, 2009) Fitting Border Crossing Times Distribution In order to run Monte Carlo simulation, hourly travel time distributions were fitted from the RFID data. Figure V-8 shows the histograms skewed to the right and the fitted lognormal distributions of the RFID data by time periods. The statistical distributions of arrival patterns were used in the Monte Carlo simulation to represent the uncertainty in the border crossing time. (a) AM Peak (b) Off Peak (c) PM Peak Figure V-8. Fitted Lognormal Distributions of RFID Observations by Time Periods Texas Transportation Institute Page 51

58 Table V-1 represents the fitted parameter values with lognormal distributions. Table V-1. Fitted Crossing Time Distribution Parameters Period AM Peak (06:00-10:00) Off Peak (10:00-16:00) PM Peak (16:00-19:00) Whole Day (06:00 19:00) Number of Samples Performance Measures for Border Crossing Times Lognormal Distribution Mean Crossing Time (minutes) Standard Deviation (minutes) 9, , , , Following the discussion on definitions of delay, it is noted here that there are many different ways to represent the performance of border crossings (Rajbhandari et al., 2009 (30)). In this report, it is how to define the delay and reliability so that the economic implications may be better estimated. Figure V-9 illustrates the weekday crossing time observations during a representative month of September It shows a wide range of border crossing times from 8 minutes to 120 minutes over the sample period. The minimum crossing time is the fastest possible crossing time from the first reader at the entering point on the Mexican side and the second reader at the exit point of the state inspections facility in El Paso. Since every truck passes through the inspection stations between the readers, this minimum crossing time is different from the physical free flow time between the two points. Other measures, average crossing time, median crossing and 95 th percentile crossing time, capture various aspects of the distribution of times and the variability of the border crossing time. The buffer time, 50 minutes in Figure V-9, is the difference between 95 th percentile travel time and average travel time. It can be expressed as the amount of extra time needed to be on time for 95 percent of the trips Travel Time Reliability Measures. (35) Texas Transportation Institute Page 52

59 Crossing Time (minutes) th Pecentile Crossing Time Buffer Time Average Crossing Time Minimum Crossing Time 0 RFID obervations during weekdays of September 2009 Figure V-9. Performance Measures from RFID Observations (Weekday Crossing Time by Minute, September 2009) (BOTA) Measure of Border Crossing Time Delay Unlike much of the earlier work in this arena, this study notes that delay is measured in reference to a baseline or benchmark measure since the crossing process takes a minimal length of time. This length of time will be different for different classes of trucks. For instance these identifiers will include at a minimum: FAST or non-fast Empty or loaded Cargo type Inspection stages a) (to secondary inspection) b) secondary to primary and c) through primary inspection. In reality, however, the available data rarely allows that fine a classification unless measurements follow using those criteria. Hence, a single mean or average might represent that benchmark. Several benchmarks are used to calculate the delay and the travel time reliability. The mean is the simplest known baseline or benchmark to assess delay. In Figure V-10 the median crossing time and average crossing time are used as threshold values to measure the delay. For example, by using median crossing time (41 minutes) threshold, any RFID record with a crossing time lower than 41 minutes was considered a no delay or normal trip. If a trip is identified with times higher than 41 minutes then the excess time over 41 minutes is treated as delay. By the same token, any crossing time over the current average of 48 minutes is measured as delay when using the average crossing time threshold. The other important measure is 95 th percentile Texas Transportation Institute Page 53

60 Values x 10^-2 95th Percentile CT Median CT Average CT travel time. Certain commodities such as just-in-time products and perishable products are likely to incur additional costs when the delay exceeds a given buffer time (damages for perishable goods, for instance). In the current sample statistics, 95 th percentile crossing time was 98 minutes and the buffer time was calculated as 40 minutes, as shown in the Figure V-10. Lognorm(49.525, ) Shift= Delay by Median Crossing Time 2.0 Delay by Average Crossing Time Buffer Time < 5.0% 90.0% 5.0% > Figure V-10. Crossing Time Distribution (BOTA) and Performance Measures/Statistics (July-September 2009 BOTA) OTHER CRITICAL DATA ELEMENTS The framework draws upon several additional components and data aspects that are of value in determining direct economic implications. These include: Truck Volumes by Direction of Flow, Loaded and Empty Trucks by Direction of Flow, and Weight and Value of Cargo Flows by Direction of Flow. These aspects are discussed in detail in the following chapters. Figure V-11 is a visual representation of the various elements of the framework that are incorporated in the development of a border delay direct cost estimation tool. This framework was developed based on the stakeholder feedback combined with an assessment of freight movement patterns at the ports of El Paso. As such, the framework is transferable and may be adapted to other POE s. Texas Transportation Institute Page 54

61 Crossing Time (Archived/Near Real Time) Trade Profiles at Ports of Entry & Freight Movement Patterns Direct Economic Variable Costs Crossing Volumes Cargo information (Loaded, Value, Weight) Figure V-11. Various Components of the Framework (by Direction of Flows) Texas Transportation Institute Page 55

62 CHAPTER VI: DIRECT COSTS CATEGORIES In this research, only direct monetary delay costs were considered in terms of shippers and carriers. The various cost categories were combined with performance measures from RFID data into an interactive spreadsheet tool that allows users to arrive at direct cost consequences. Furthermore, while the statistics and data are primarily reflective of northbound flows into the United States, it must be noted that the framework is only limited at this time by the availability of data on archived time. Hence, with additional data, the framework may be adapted to other ports. The costs are all variable, in the sense that they are all functions of time. VARIABLE DIRECT COST CATEGORIES: SHIPPER Shippers incur inventory costs such as inventory capital cost, inventory risk cost, and cost of delayed schedule due to extraordinary border crossing times. Those inventory cost parameters are set to account for the different commodity groups. Manufactured just-in-time (JIT) products have the most expensive logistic costs for schedule delay since a delay in one manufacturing part may lead to disturbances in the downstream of production schedules. Maquila production that is so highly represented in the El Paso ports is one that falls in this category. In the interactive spreadsheet tool, the following cost components are considered in regard to shippers: inventory capital costs inventory damage/risk costs for perishables and JIT products, and finally additional logistics costs from excess variability or when times exceed buffer times. VARIABLE DIRECT COST CATEGORY: CARRIER Carrier related time dependent costs include: Vehicle Operating Costs (Fuel, Maintenance, Wear and Tear) Labor costs COMMODITY CLASSIFICATIONS AND PORTS OF ENTRY Based on the commodity profile of ports of entry evaluated in earlier chapters, it was decided that a five-fold breakdown of commodities would meet the trading profile of most ports for the evaluation of direct costs and subsequently broader costs. This five-fold breakdown is: manufactured JIT products (Referenced as Comm-1 henceforth), manufactured non-jit products (Comm-2), agricultural perishable products (Comm-3), agricultural non-perishable products (Comm-4), and other products (Comm-5). Texas Transportation Institute Page 56

63 SHIPPER COSTS Cargo Values Average cargo values per truck trip are important for assessing inventory capital costs for loaded trucks. These values are obtained from secondary sources. However, it is important to note that there is currently no readily available information about average cargo values, and in many cases this is an imputed parameter or one that a user may choose to provide. Currently, TCBEED provides export and import values for the top 25 (2-digit Standard Industrial classification Code SITC) traded commodities by POE region. The Bureau of Transportation Statistics also publishes export and import values and weights by 2-digit Harmonized Tariff Schedule (HTS) codes by ports. The average cargo value is the dollar amount of shipments carried by a loaded commercial truck. Since this not directly available, it is estimated from the annual imports value by truck through El Paso and the number of annual loaded truck containers. Table VI-1 shows the calculated average cargo values per truck since 2004 in the last column. The analysis of values is kept to year 2009 to maintain consistency with RFID dates. PORT EL PASO YEAR Table VI-1. Average Imports Cargo Value per Loaded Truck (Northbound Crossings El Paso) Imports Value by All Land Modes (Destination in Texas) Imports Value by Truck (Destination in Texas) # LOADED TRUCK CONTAINERS. Average Cargo Value per loaded truck container ($/truck) 2004 $12,469,348,486 $12,155,269, ,093 $29, $11,309,017,253 $11,246,227, ,768 $26, $11,513,235,758 $11,429,703, ,026 $27, $12,493,795,483 $12,320,196, ,456 $30, $13,923,529,950 $13,251,291, ,586 $34, $12,250,863,192 $11,579,415, ,119 $34,450 SOURCE: U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics, Transborder Freight Data; U.S. Department of Homeland Security, Customs and Border Protection, OMR database; UTEP Border Region Modeling Project. The El Paso-Juarez region shows highly industrialized characteristics. Table VI-2 shows the top 25 traded imports by value. 78 percent is represented by machinery and transport equipment (SITC 7), 15 percent by miscellaneous manufactured articles (SITC 8) and less than 2 percent is represented by food and live animals (SITC 1). The majority of the imports are JIT related and over 90 percent of the imports are manufactured products. Texas Transportation Institute Page 57

64 POE EL PASO 1-Digit SITC 7 5-Digit SITC Table VI-2. Imports through El Paso Ports (2009) Top 25 RANK TRADE VALUE POE 1-Digit SITC 5-Digit SITC Top 25 RANK TRADE VALUE $3,610,013, $191,113,402 $2,807,041, $165,804,360 $1,552,590, $163,832,342 $1,478,732, $695,905, $725,377, $661,838, $696,582,383 EL $445,923,612 PASO $455,037, $259,295, $372,816, $180,015, $339,980, $165,947, $280,367, $147,282, $260,017, $911,418, $230,873, $285,973, $212,998,471 Sum of Top 25 Import $17,296,781,817 SOURCE: Texas Center for Border Economic & Enterprise Development Inventory Costs: Ownership Aspects and Whose Costs? In attempting to discern relevant costs of delay, it is important to recognize that inventory costs are costs to either the shipper or the receiver depending on when the change of hands takes place. If the ownership change occurs at the very beginning of a movement, the cost reflects a cost to the receiver. On the other hand, if the ownership change occurs at the end, the costs reflect a shipper cost throughout. While in principal this is very difficult to assess across the board and is likely to vary across goods and shippers and linked to terms of trade, this report makes an assumption that the inventory cost is a shipper cost. This is corroborated by shipper responses discussed in Chapter 4. Research by Cambridge Systematics (2) indicates that the El Paso bi-national gateway region acts largely as a support center for locally manufactured goods (maquila industry), and yet other research suggests that a large percentage of shippers are also receivers in the El Paso-Juarez bi-national region. This suggests that the assumption of assigning costs to the shipper is perhaps not an onerous assumption. Inventory Cost Components Capital Cost This component represents the cost of goods in transit. It is usually an internal cost of funds rate multiplied by the value of the product. Because value is added to the product as it moves along the supply chain, this cost tends to increase as the product moves downstream. Holding inventory ties up money that could be used for other types of investments. Consequently, a shipper s true opportunity cost of capital of any time related delay is reflected in the capital costs. Since this cost is associated with a direct move through the chain, this component is therefore a critical component of traditional cost-benefit analysis. Texas Transportation Institute Page 58

65 Storage Cost Units in inventory take up physical space, and may incur costs for storage, heating, refrigeration, insurance, etc. This is of particular import for goods requiring refrigeration. Quality Cost High levels of inventory usually increase the chance of product damage and create slower feedback loops between supply chain partners. The result: lower levels of quality and a rise in the myriad costs associated with low quality. These costs are difficult to quantify precisely, but the current consensus is that they can be quite significant. This is of particular import for perishables. Typically, all these costs are rolled together into a single inventory cost rate, expressed as a percentage of the value of the product or material per unit time (e.g., 20 percent of the value per year). The Council of Supply Chain Management places this value at 18 percent, for instance. Other equivalent terms for this same cost rate are inventory holding cost rate and inventory carrying cost rate. Border Delays and Relevant Inventory Costs The social costs of the border delays can be captured by the interest carrying (capital) costs of inventories and/or the wastage (perishing) of inventories in addition to the time costs. It is important to point out there are two factors that determine which of these components become important, including the following: Nature of freight movements traversing the region: Gateways and ports characterized by primarily short-haul movements could risk the capital cost of goods/value in transit. Capital cost components accrue to all goods in transit and can be influenced by travel time delays and efficiencies and has been therefore included in most benefit cost analysis related to transportation movement. On the other hand, ports characterized by longer origins and destinations could potentially incur additional logistic cost components because of longer supply chains. The size of these added interest carrying or capital costs depend on value assumptions as well as the interest rate. Nature of cargo: This determines if elements of storage costs or quality costs become relevant. Perishables, for instance, loose value. In the case of the Canadian borders, the Ontario Chamber of Commerce noted that storage of inventory was a significant cost in the automotive sector due to delays at the Ontario-U.S. border crossings (OCC, 2005). The size of this cost depends on rate of decay of goods. The hourly inventory capital cost of a truckload of commodity is given by i: Where, H i = annual unit holding cost per $1 value of inventory. S i = dollar value of a truckload of commodity i. Currently default values of H i are approximated by market interest rates to proxy the cost of capital. It can be adjusted by a user to include more general inventory carrying cost terms in the spreadsheet tool if necessary. Texas Transportation Institute Page 59

66 Inventory Damage/Risk Costs for Perishables and JIT Products In concept, JIT production is designed to keep minimum possible inventory and to rely on a punctual supply chain for running the production lines. If assembly parts are not delivered on time due to unexpected delays at the border, JIT production lines could be affected by the shortage. Similarly, perishable products decay in the event of excess delays. Hence, JIT products and perishable products have higher inventory costs due to the more stringent time constraints within the supply chain. In the current spreadsheet tool, it is assumed that 9 percent to 18 percent of inventory value on hand is used to account for the damage/risk costs for perishables and JIT products. 14 Additional Logistics Costs from Variability in Crossing Times Uncertainty comes with a cost and this is approximated by using the value of reliability and is only valued for just-in-time production systems using buffer times (based on 95 th percentile time). Shippers usually schedule ahead considering this extra buffer time in their regular business process, but excess delays may occur. Additional logistics costs are calculated as follows: Truck-hour over 95% tile crossing time*vor Where VOR = value of reliability. Since region-specific reliability estimates are not available, this parameter is approximated by work done by Small. Hence, in the spreadsheet tool VOR ranges from $ to $ (Small et al, 1999) (36). This term is heavily influenced by shipper/carrier perceptions on time spent traversing borders and their built in buffer times for the crossing. Another interpretation is that 95% percent of the times, these costs would not apply but when they do- they are high. VARIABLE CARRIER COSTS Fuel Costs One of the key components of carrier variable operating costs is fuel consumption due to delay. Fuel costs are treated analogous to dealing with congestion and stuck in traffic. When a truck approaches the border inspection facilities, it reduces its speed to creeping mode until it is inspected and cleared at the booths. This slow movement usually starts at the beginning of the Mexican export inspection facility through the U.S. federal inspections facility and the state inspections facility. At these border delay segments, additional fuel is needed to deal with the slow speed and the extra time due to delay. The fuel cost due to delay is calculated by the product of fuel consumption rate, delay time, and the fuel price. This estimate includes taxes, but may be netted out by adjusting the fuel price. 14 The typical range cited by these authors for risk costs ranges from 9-18% of value while storage costs range from 7-16% of value. (Richardson, 1995) (37) Texas Transportation Institute Page 60

67 Fuel Cost = Fuel consumption rate * Truck fuel price * Delay hours. Labor Costs Labor cost is defined as the direct cost that carriers have to spend for hourly wages. The USDOT guidance recommends the use of $22.15 in the year 2009 as the basis of benefit cost analysis and 100 percent of wages as recommended value of time savings. Table VI-3 shows the commercial vehicle values of time in the United States. Because of the wide discrepancy shown in the table, current 2009 statewide wages were used as a basis of Texas value-of-time conditions. According to the Texas Workforce Commission (TWC), the 2009 median hourly wage statistics for truck transportation was $17.11 for general freight trucking and $14.38 for specialized trucking. These values are upgraded to include 25 percent fringe and vehicle occupancy of 1.1, suggesting wages of $24.90 in generalized freight and $23.00 in specialized trucking. Mexican trucker wages are known to be lower than for US-based trucks and many of them may have wages in the range of $6-$10 per hour. However, the range of costs entered are consistent with initial shipper response noted in Chapter 4. For these reasons, the design of the tool is such that it is extremely transparent, and user-developed inputs may enable better assessment of costs. For this report, the US-based values are currently used as defaults. In prior studies (Ojah et al., 2002), a California toll study estimate was to approximate time costs. Instead, this study assumes a more conservative approach and bases it purely on wage costs. The benefit-cost model Highway Economic Requirements System (HERS) (38), for instance, uses a similar concept of wage-based assessment but also adjusts these costs by cargo type and by adding in inventory carrying costs based on cargo value and hourly discount rate factors. The approach developed in this report, on the hand, breaks up the various components into individual elements so that inventory costs may be assessed separate from wage-based costs. Finally, this separation also allows for inventory to be linked directly to variance in delays. Texas Transportation Institute Page 61

68 Source Haning & MacFarland (1963) (39) McFarland and Chui (1986) (40) Waters et al. (1995) (41) Buffington & MacFarland (1975) (42) Table VI-3. Commercial Vehicle Values of Time in the United States Specific Purpose Project evaluation Project evaluation Values Reported Dollars per hour (in 1998 dollars) Updated to Comments 2009 Dollar Amount (/hour) First study to estimate commercial value of time. Truck operators. Minimum and maximum values of time based on low to high utilization of time (1985 dollars) For small cars, large, medium cars, and pickup trucks (in 1998 dollars) Evaluation Single unit 2-4 axles = Other singles unit = Semi combination 4 axles = All others 5 axles = (in 1985 dollars) Cargo vehicles. Minimum value = 40% of driver wages. Maximum = all time savings converted to additional business. = Updated American Association of State Highway and Transportation = Officials (AASHTO) values. Average = $38.80/hour (in 2006 = dollars) = Kawamura (1999) (43) Lewis NCHRP 2-18 (1994) (44) HERS (FHWA) (38) Toll road application a) 26.8 (std dev=43.68) = California truck operators b) 23.4 (std. de=32) = > 100 (in 1994 dollars) Scheduling benefits for drivers for vehicle/inventory carrying costs (in 1997 dollars) = Wage costs and inventory carrying costs Texas Transportation Institute Page 62

69 CHAPTER VII: MODEL STRUCTURE STRUCTURE OF THE SPREADSHEET TOOL The DCET tool was designed to utilize the historical freight flow statistics and direct input from users to run Monte Carlo simulation experiments on various parameters with uncertainties. Figure VII-1 demonstrates overall modules and data flows between the modules in a schematic diagram. The key features of this proposed economic impact tool are as follows: It is designed to provide a current assessment of delay related economic impact in terms of shippers and carriers separately. It allows users to change the default input parameters easily to see the influence of an input parameter on the direct delay costs. It is designed to consider different commodity groups. It is designed to permit interface with archived travel time/near real time data collection efforts. It is currently NOT designed to directly handle influence of port strategies since it works with crossing times. In other words, capacity changes can only be analyzed ex-post through their influence on times, but not in an ex-ante sense as in typical simulation studies. In Figure VII-1, the data flows can be grouped by the following three main components: time component, volume or number of truck component, and cost component. Since the direct delay cost is a function of volume, delay hours, and per-hour unit costs, the information flows from the three components are gathered together in the input parameters worksheet to be used in the calculation module generating the direct delay cost estimations by different delay criteria. Texas Transportation Institute Page 63

70 Simulation Results from each iteration Monthly NB Truck Crossings at BOTA Stats about Crossing times and Delays Annual/monthly NB trucks at BOTA Base_Stats RFID_Sample Avg. cargo value, commodity distribution, etc. Default crossing times Monte Carlo Simulation User Input Cost parameter values TimeComponent Delay hours by cutoff criteria No.TruckComponent No. NB trucks CostComponent Delay costs by commodity group Input Parameters Delay cutoff times, % of trucks delayed Daily costs Calculation Delay costs, Average delay, No. trucks delayed SimResults Daily NB Trucks REPORT_Time REPORT_Cost REPORT_TrkVol Figure VII-1. Structure of the Delay Cost Estimation Tool Schematic Data Flows In the spreadsheet tool many input parameters are based on the historical freight flow statistics that can be changed by direct user inputs. In the user input screen most of the input items are already filled with default values drawn from the various transportation statistics sources. Users can change any of the default values based on the current observations at the port of entry to see the effect of the changes. The input values are processed by several intermediate calculations. These are subjected to risk analysis via Monte Carlo simulation to deal with the underlying inherent uncertainties about the costs and delays. The current spreadsheet framework is designed to be flexible to handle different types of commodity groups and also different types of traffic flows to represent the actual border crossing conditions as close as possible. Figure VII-2 shows the schematic diagram of data flow of the spreadsheet tool. Texas Transportation Institute Page 64

71 Historical Freight Flow Statistics & RFID Observations Main INPUT SCREEN NB Truck Volume Distribution Average Cargo Value Inventory Cost Parameters Logistics Cost Parameters Carrier Cost Parameters Operating Cost Parameters Intermediate Process Shipper Costs Carrier Costs Delay Time Truck Crossings RISK ANALYSIS (MONTE CARLO SIMULATION) Total Daily Cost Caused by Delays at POE = function [(Unit Delay Cost x Daily # Trucks) by (Loaded Truck / Empty Truck) by (Commodity Category)] OUTPUT REPORTS Total Delay Costs, Total Delay Hours, Truck Volumes, etc. Figure VII-2. Schematic Data Flow Diagram of the Spreadsheet Tool Basic Input Parameters Crossing Time and Delay: What Represents a Delay? Border crossing times are measured by RFID readers installed at the entering point of the Mexican export facility and the exit of the state inspection facility. Since crossing time is a travel time between the two RFID readers, it can be partitioned into normal travel time and delay. Delay can be viewed in many different ways by how the regular travel time is defined. In some cases, free flow travel time could be considered as regular travel time. In other cases, average travel time could be regarded as normal travel time. In order to deal with the range of delay measures, the current spreadsheet tool uses several different delay measures to calculate the impact of delay. The different delay criteria are shown in Figure VII-3. Texas Transportation Institute Page 65

72 Values x 10^ Values x 10^ Values x 10^ Delay by Average Crossing Time Lognorm(49.303, ) Shift= Delay by Median Crossing Time Lognorm(49.303, ) Shift= %tile Buffer Time Lognorm(49.303, ) Shift= Delay Delay Buffer Time Delay Average Crossing Time < 5.0% 90.0% 5.0% > Median Crossing Time < 5.0% 90.0% 5.0% > Average < 5.0% 90.0% 5.0% > %tile Crossing Time (a) by average CT (b) by median CT (c) by 95%tile CT Figure VII-3. Delay Measures Freight Traffic Volume Annual freight traffic volumes by ports of entry from BTS were used to derive the daily truck crossings since the daily traffic volumes were not available. They were divided by the number of the yearly weekday equivalent. The average freight traffic volume on Saturday at BOTA observed 30 percent of the average weekday volume from the RFID data. Hence, the yearly number of weekday equivalent was translated as follows: (52 weeks/year * 5 weekdays/week) + (52 Saturdays/year * 0.3) = days/year In the BOTA case example, the northbound truck traffic in the year 2009 was 316,731 trucks, and the average daily traffic was estimated as follows: Laden-Empty Truck Ratio 316,731 trucks / = 1,149 trucks/day. The BTS annual freight traffic volumes table includes the data about loaded and empty truck containers. The ratio between the loaded and empty containers was used in the tool to calculate the daily loaded and empty freight truck crossings. The number of loaded trucks is important to assess shipper costs such as inventory cost and additional logistic costs from variability in crossing times. Distribution of Commodities Commodities were grouped into three major categories of commodities: Manufactured, Agricultural, and Other commodity groups. Manufactured items were then further divided into Just-In-Time and Non-JIT commodities. Agricultural items consist of Perishable and Non- Texas Transportation Institute Page 66

73 perishable commodities. This break up allows the consideration of variability in delays. Some of the default input values of these commodities were collected by one-digit SITC codes from various sources such as U.S. Department of Commerce Bureau of the Census, Foreign Trade Division and Texas Center for Border Economic and Enterprise Development. Unfortunately, there were no available data for the number of truck crossings by SITC for the border ports of entry by commodity type. The default truck volume distribution was therefore approximated from the import value distribution obtained from TCBEED. Superior user-based information, or survey based data may override these defaults, if they are available and will enable more accurate assessments. Just-in-Time Freight In order to demonstrate, characteristics of any POE, the spreadsheet tool uses truck volume distributions of five commodity groups. As mentioned in the previous chapter, JIT related products represent a large portion of the freight traffic volume in the El Paso region with the assumed default value of 78.3 percent. Since the JIT products are more sensitive to unexpected delays, the simulation model allows users to input inventory risk cost in addition to the common capital cost. Perishable Commodities Another commodity group that needs special attention is perishable items. Even though perishable items are a very small percentage of overall northbound flows through El Paso ports, they should be considered explicitly for additional holding cost due to delay because they need more resources to offset decay of the freight until they are delivered to final destinations. Like just-in-time freight, perishable commodities have separate input values for inventory holding cost to yield final inventory costs. Average Cargo Values Cargo values are critical for the determination of inventory costs. Due to lack of common public domain source, the following values are imputed from BTS data: Average Cargo Value = Imports value by truck / Number of loaded trucks. Currently the BTS tables show only aggregated values at the port region level by mode. Texas Transportation Institute Page 67

74 CHAPTER VIII: BRIDGE OF THE AMERICAS ILLUSTRATION NUMBER OF FREIGHT TRUCK CROSSINGS Even though there has been tremendous innovation in technology for data collection and for archiving travel time or crossing time, the methods available to date are still inadequate to identify other factors that are critical for economic assessments. For instance, RFID readings give vital information about the border crossing times; they are not sufficient enough to estimate the freight traffic volumes due to the partiality of the RFID observations and the lack of ability to distinguish loaded and empty trucks. In the current framework, freight traffic volumes are estimated from the historical statistics published by BTS based on Table III-2. In the current BOTA case example, daily loaded trucks are estimated by the following equation: Daily loaded NB trucks = Daily NB Trucks * Loaded truck % at El Paso USER INPUT VALUES IN THE SPREADSHEET TOOL The input values in the current BOTA example are based on the historical data as default values. Even though the spreadsheet tool will be able to generate the output reports with those default values, it is designed so that superior information provided by users may override defaults. Figure VIII-1 and Table VIII-1 illustrate the main input screen and the default input parameters used in the simulation model. Texas Transportation Institute Page 68

75 Figure VIII-1. Main Input Screen DCET Crossing Times % of Trucks Delayed Idling/Creeping Fuel Consumption Table VIII-1. Default Values Bridge of the Americas, El Paso Parameter Value Parameter Value Average CT 47.5 minutes by Average CT 26.7 minutes Median CT 41.0 minutes Delay Times by Median CT 27.2 minutes 95%tile CT 98.0 minutes by 95%tile CT 28.6 minutes by Average CT 42.80% JIT 78.30% by Median CT 53.50% Truck Volume Non-JIT 20.00% Distribution by by 95%tile CT 6.00% Perishable 0% Commodity Loaded 4 gallons/hour Group (by Top Non-perishable 0% imports) Empty Other 1.70% gallons/hour Texas Transportation Institute Page 69

76 OUTPUT RESULTS FROM THE SIMULATION 1,000 replications were used in the simulation experiment. Each replication represents the daily border crossing activities. The simulation results were summarized in the separate output reports pertaining to the three components: cost, time, and truck volume. Notice that the figures of the output reports shown in Figure VIII-2 and Figure VIII-3 are subjects to the assumed conditions in the previous section and are therefore only a proxy to the costs of delay. Delay Cutoff Time Criteria (50%tile+) (95%tile+) Average Median Reliability Cost - Buffer Time Estimated Annual Cost $4,809,890 $5,469,138 $2,387,898 Just-In-Time $3,237,843 $3,512,196 $2,229,905 Carrier Costs $987,252 $1,255,974 Shipper Costs $2,250,591 $2,256,222 $2,229,905 Non-JIT $399,544 $468,569 $145,956 Carrier Costs $252,778 $321,583 Shipper Costs $146,766 $146,986 $145,956 Perishable $0 $0 $0 Carrier Costs $0 $0 Shipper Costs $0 $0 $0 Non-Perishable $0 $0 $0 Carrier Costs $0 $0 Shipper Costs $0 $0 $0 Other $32,950 $38,643 $12,037 Carrier Costs $20,847 $26,521 Shipper Costs $12,104 $12,122 $12,037 Empty Trucks $1,139,553 $1,449,730 (Carrier Costs Only) $0 $0 Delay Cutoff Time 48 minutes 41 minutes 98 minutes PER-HOUR COSTS BY COMMODITY GROUP Per-hour Commodity Group JIT (Comm 1) Carrier Cost Regualr Shipper Cost (Typical delay) Reliability Cost (Delay over 95%tile) Non-JIT (Comm 2) Carrier Cost Regualr Shipper Cost (Typical delay) Reliability Cost (Delay over 95%tile) Perishable (Comm 3) Carrier Cost Regualr Shipper Cost (Typical delay) Reliability Cost (Delay over 95%tile) Non-perishable (Comm 4) Carrier Cost Regualr Shipper Cost (Typical delay) Reliability Cost (Delay over 95%tile) Other (Comm 5) Carrier Cost Regualr Shipper Cost (Typical delay) Reliability Cost (Delay over 95%tile) Empty Truck Carrier Cost Delay Cost ($/hour) $39.88 $0.84 $ $39.88 $0.13 $ $39.88 $0.48 $ $39.88 $0.13 $ $39.88 $0.13 $ $39.88 Figure VIII-2. Sample Screenshots of Output Reports BOTA Illustration Texas Transportation Institute Page 70

77 Figure VIII-3. Ninety-Five Percent Confidence Interval Cost Estimates BOTA Illustration RESULTS Figure VIII-2 shows a range of reliability based inventory costs per hour ($564.4-$144) based on commodity grouping. Labor/fuel/maintenance wear and tear costs are assessed at approximately $39 dollars per hour. Based on commodity splits, the actual estimated costs per day based on July September (2009) archived crossing time information and evaluated at delay Texas Transportation Institute Page 71

78 based on mean or average crossing time, and including buffer time (also based on mean time) are as follows: $8,166 for those in just-in-time production systems for a total of $189,455 for one month. These costs assume that shippers hold less than one hour in buffer time to combat variance in delay. In the event that buffer times of 1 hour or more are held, these costs may be significantly lower. Per our initial stakeholder feedback, a few hold buffers of one hour or so, while others do not. Anticipating and understanding travel patterns may be in the interest of shippers wishing to maximize their trips or optimize their productions. Combining the archived data on crossing times to communicate meaningful statistics may be of value in enabling shippers to take action on all fronts. Some portions of these costs will be borne entirely by shippers themselves and may represent a clear loss with much broader economic implications. The monthly and daily costs for other manufacturing shippers is much lower at $12,355and $533, respectively. The total daily costs for shippers and carriers jointly are estimated at $17,452 (delay evaluated relative to the mean). Other benchmarks will obviously change these estimates. CONCLUSIONS This research conducted an evaluation of El Paso ports of entry. Based on an exhaustive literature review, a framework and tool was developed to develop the direct economic implications of border-related delays. This report focused on direct costs (those are time variable) and developed an interactive spreadsheet tool (DCET) that allows users to investigate how a variety of freight performance measures may be quantified in terms of economic consequences to the freight industry (shippers, carriers). In particular, the Bridge of the Americas was adopted as a case example. This choice of POE does not impact the validity of the application in any way. BOTA was selected for illustration because it provides a unique opportunity to draw upon archived RFID data on bridge crossing times and utilize those in the development of freight performance measures, including measures reflecting trip reliability. The value of the high quality of data is important since the analysis is highly dependent on primary and secondary data sources to establish distributions and defaults. Given this aspect, the spreadsheet was designed as flexible with defaults that users could override. Given the high levels on uncertainty in many inputs, including crossing times (the most critical input), risk analysis via Monte Carlo simulation was an integral element of the tool as well as sensitivity analysis. This interactive element was also crucial to maintaining transparency of the tool to users. The method adopted in this research was based on the factor cost method. This involved identifying the components of vehicle costs that vary with the amount of elapsed time (mostly wages, interest on capital employed or tied up in inventory on wheels, and licensing fees). It also considered inventory costs. Texas Transportation Institute Page 72

79 The research shows that direct costs of variability can be rather high for those in JIT systems and more than twice the cost of wages and other operating costs. This is consistent with observations in the literature (Huang and Whalley, 2008). The research suggests that economic costs and economic implications are important and can be significant. Policy initiatives impacting delays must consider the balance since there is a strong correlation between delay and economic outcomes for the bi-national regions. Security is critical at the borders, and a variety of operational strategies may be adopted to manage delays but economic consequences are sometimes non-trivial. Hence, a balance must be struck. Future research along several directions may enhance the assessment of economic costs: Enhanced data sources, if available especially pertaining to crossing time fine-tuned by category. Better estimates of shipper based reliability at border ports of entry. Improved assessment of direct cost reliability based on alternative theories based on preferred arrival and departure and those sensitive to built-in buffers. In addition, the current work is based on near real time/archived data. In subsequent work, this could be extended to real time applications. The El Paso Regional Management Information System (RMIS) developed by researchers at the Center for Intelligent International Transportation Research at Texas Transportation Institute provides a framework for enabling this process. Conduct a study of broader economic implications. Prior research along these lines has primarily focused on the partial equilibrium methods with several assumptions made in regard to substitution elasticities and other elasticities. These assumptions will need to be reviewed in light of current economic situations as well as other assumptions used to extrapolate broader impacts. Consider policy sensitivity aspects and their direct implications to costs. Texas Transportation Institute Page 73

80 REFERENCES 1. Hanson, G. U.S.-Mexico Integration and Regional Economies: Evidence from Border City Pairs. Journal of Urban Economics, Volume 50, Issue Cambridge Systematics. Texas NAFTA Study Update. Final Report, Prepared for Texas Department of Transportation, Kristjansson, K.A., M. Bomba, and A. Goodchild. Intra-Industry Trade Analysis of American State-Canadian Province Pairs: Implications for Cost of Border Delays. Transportation Research Board, Transportation Research Record, No. 2162, Anderson, J.E., and E. van Wincoop. Borders, Trade, and Welfare. NBER Working Paper Series Available at: Beilock, R., P. Boneva, G. Jostova, K. Kostadinova, and D. Vassileva Road Conditions, Border Crossings and Freight Rates in Europe and Western Asia. Transportation Quarterly. 50(1), pp Matisziw, T. Modeling Transnational Surface Freight Flow and Border Crossing Improvement. Doctoral Dissertation, Ohio State University, Fox, A., J. Francois, and M.P. Kent. Measuring Border Crossing Costs and their Impact on Trade Flows, pp Haralambides, H., and M.P. Kent. Supply Chain Bottlenecks: Border Crossing Inefficiencies between United States and Mexico. International Journal of Transport Economics, Vol. XXXI, No. 2, pp Ojah, M., J. Villa, W. Stockton, D. Lufkin, and R. Harrison. Truck Transportation through Border Ports of Entry: Analysis of Coordination Systems. Texas Transportation Institute, Taylor, J., D. Robideaux, and G. Jackson. US-Canada Transportation and Logistics: Border Impacts and Costs, Causes, and Possible Solutions. Transportation Journal HLB Decision Economics: Economic Impacts of Delays at the Border on Freight Movement and Trade between the United States and Mexico. Technical Memorandum #1. Literature Review and Data Needs. May HLB Decision Economics: Economic Impacts of Delays at the Border on Freight Movement and Trade between the United States and Mexico. Technical Memorandum #2. Framework and Methodology. June HDR/HLB Decision Economics: Economic Effects of Wait Times at the San Diego Baja California Border, Final Report. Report Prepared for San Diego Association of Governments (SANDAG), California Department of Transportation. January HLB Decision Economics: Estimating Economic Impacts of Border Wait Times at the San Diego Baja California Border Region Framework. Technical Memorandum #1. Literature Review and Proposed Methodology. September HLB Decision Economics: Imperial Valley-Mexicali Economic Delay Study: Identification of data needs. September True North Research. Estimating Economic Impacts of Border Wait Times at the San Diego Baja California Border Region Framework. Technical Memorandum #3. Report prepared for SANDAG, 2004 a. Texas Transportation Institute Page 74

81 17. True North Research. Estimating Economic Impacts of Border Wait Times at the San Diego Baja California Border Region Framework. Technical Memorandum #4. Report prepared for SANDAG, 2004b. 18. HLB Decision Economics: Regional and National Economic Impact of Increasing Delay and Delay Related Costs at the Windsor Detroit Crossings. Final Report. Prepared for Ontario, Canada and Michigan Department of Transportation. January Belzer, M. The Jobs Tunnel: The Economic Impact of Adequate Border Crossing Infrastructure. 2003a. 20. Belzer. M. Regional and National Economic Analysis of Delay and Delay-Related Costs at the Detroit Windsor Crossings. 2003b. 21. RTI International. The Economic Benefits of Expanding the Border Crossing for Commercial Vehicles at the Mariposa Crossing in Nogales, Arizona. Final Report. Prepared for U.S. Department of Homeland Security, Washington, D.C. June Ontario Chamber of Commerce Studies (OCC). Develop Estimates of Costs of Border Delays on the Province of Ontario and its Businesses OCC Borders and Trade Development Committee. Cost of Delays to the United States Economy. Ontario Chamber of Commerce Goodchild, A., S. Globerman, and S. Albrecht. Service Time Variability at the Blaine, Washington international Border Crossing and the Impact on Regional Supply Chains. Border Policy Research Institute (BPRI) Final Report, Research Report No. 3, Western Washington University, (Also presented at the Transportation Research Board Annual Meeting, 2007, Paper # ) 25. Cambridge Systematics. Border Economic Impacts Study Accessed, Limao, N., and A. Venables. Infrastructure, Geographical Disadvantage, and Transport Costs. World Bank Policy Research Paper No. 2257, Hummels, D. Time as a Trade Barrier. Working Paper: Purdue University. July Fox, A., and M. P. Kent. Measuring Border Crossing Costs and their Impact on Trade Flows: The United States-Mexican Trucking Case. Unpublished Manuscript., Huang, Hui, and John Whalley. Baumol-Tobin and the Welfare Costs of National Security Border Delays. Economic Letters, Rajbhandari, R., J.C. Villa, and R.A. Sanchez. Expansion of the Border Crossing Information System. Final Report. DOT Grant No. DTRT06-G University Transportation Centers for Mobility FHWA. Travel Time Reliability Measures Rajbhandari, R., J.C. Villa, and R.A. Sanchez. Expansion of the Border Crossing Information System. Final Report. DOT Grant No. DTRT06-G University Transportation Centers for Mobility Battelle and Texas Transportation Institute. Measuring Border Delay and Crossing Times at the U.S. Mexico Border Battelle and Texas Transportation Institute. Measuring Border Delay and Crossing Times at the U.S. Mexico Border Part II Final Report on Automated Crossing Time Measurement (Contract No. DTFH61-06-D-00007/T.O. BA07-040) September 30, Accenture Group and HDR Engineering. Improving Economic Outcomes by Reducing Border Delays. DRAFT Texas Transportation Institute Page 75

82 36. Small, K., R. Noland., X, Chu and D. Lewis. Valuation of Travel-Time Savings and Predictability in Congested Conditions for Highway User-Cost Estimation, NCHRP 431, TRB ( 37. Richardson, Helen: Transportation & Distribution, Control Your Costs then Cut Them, December Highway Economic Requirements Model. Technical Report. USDOT, Federal Highway Administration Haning, C., and W. McFarland. Value of Time Saved to Commercial Motor Vehicles Through Use of Improved Highways. Texas Transportation Institute Research Report, McFarland, W. M. Chui. The Value of Travel Time. New Estimates Using a Speed Choice Model. TTI Report Waters, W. G., C. Wong., K. Megale. The Value of Commercial Vehicle Time Savings for the Evaluation of Highway Investments: A Resource Saving Approach. Journal of Transportation Research Forum, Vol. 35, no. 1., Buffington, J and W. McFarland. Benefit-Cost Analysis: Updated Unit Costs and Procedures, Research Report 202-2, College Station, Texas, Texas Transportation Institute, August, Kawamura, K. Perceived Value of Time for Truck Operators. Transportation Research Record, Journal of the Transportation Research Board, No. 1725, D. Lewis. Valuation of Travel-Time Savings and Predictability in Congested Conditions for Highway User-Cost Estimation. National Cooperative Highway Research Program Report 431, Texas Transportation Institute Page 76

83 APPENDIX 1: BRIDGE OF THE AMERICAS DETAILS Infrastructure and the Services Available at the Bridge of the Americas Bridge Details: BOTA consists of two adjacent bridges, one for northbound and one for southbound traffic. There are two dedicated truck lanes on the outside of each bridge four lanes total. Inspection Booth: BOTA is open 24 hours a day, 7 days a week to both passenger vehicle and pedestrian traffic. Commercial traffic services are limited to 6:00 am to 6:00 pm for northbound traffic and 8:00 am to 9:00 pm for southbound traffic. Tolls: By treaty, there are no tolls on the BOTA. Capacity: There are a total of three northbound commercial lanes exiting the Cordova Mexican Aduana Ex port lot in Cd. Juarez, Mexico one Fast Lane and two regular commercial lanes. The United States side of the bridge is owned by the International Boundary Water Commission (IBWC) and the Commission de Limites y Aguas (CILA). There are a total of 14 primary inspection stations for passenger vehicles entering the United States. Passenger vehicles undergo Customs, Immigration and Agricultural inspection at the primary inspection points. At the discretion of the inspector, passenger vehicles may be pulled aside into a stall for secondary inspection. There are a total of 4 primary inspection stations for pedestrians entering the United States. Pedestrians needing to go through agricultural or secondary inspections either enter this area once they have crossed the bridge (following signage), or they are directed to the secondary inspection areas after going through primary inspection. There are a total of eight passenger vehicle lanes (four northbound and four southbound), and four (two northbound and two southbound) commercial vehicle lanes crossing on the bridge. There are Customs, Immigration, and Agricultural inspections performed going northbound on the U.S. side. Programs: Free and Secure Trade (FAST) Texas Transportation Institute Page 77

84 Figure IX-1. BOTA Land Port of Entry: View from the Mexican Side Texas Transportation Institute Page 78