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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
Center for International Intelligent Transportation Research Report No: 186041-00005 July 2011 Report prepared by Center for International Intelligent Transportation Research Texas Transportation Institute 4050 Rio Bravo, Suite 151 El Paso, Texas 79902 TEXAS TRANSPORTATION INSTITUTE The Texas A&M University System College Station, Texas 77843-3135
Center for International Intelligent Transportation Research Texas Transportation Institute Page i
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 .................................................................................................................... 13 Ports are not Identical ............................................................................................................... 13
Passenger Ports ..................................................................................................................... 13
Commercial and Passengers Ports ........................................................................................ 13 Ports Vary in Terms of Commodity/Trade Profiles .............................................................. 14
Ports Vary in Terms of Transport Corridors They Serve ..................................................... 17 Ports Vary in Terms of How They Move Goods .................................................................. 17
Ports Vary in Terms of final Destinations they Serve/Trading Partners (Truck Trade flow
Distributions) ............................................................................................................................ 19 Borders as Components of Transport Costs and Links to Logistical Efficiency ...................... 21
Factors Causing Delays ......................................................................................................... 21 Prior Literature, Perspectives in Assessing Economic Costs of Delay ................................. 24
Types of Economic Costs ..................................................................................................... 26
Chapter III: El Paso Freight Movements ................................................................................ 27 Freight Movement Trends – El Paso Ports of Entry ................................................................. 27
Proximity of Maquilas to Border Ports of Entry ....................................................................... 37
Chapter IV: Perceptions on Border Delays: Evidence from Shippers in the El Paso
Juarez Region .............................................................................................................................. 38 Shipper Surveys ........................................................................................................................ 38
Issues Identified by Shippers ................................................................................................ 38
Chapter V: Framework to Evaluate Direct Costs of Border Crossing Inefficiencies
to Shippers and carriers ............................................................................................................. 44 Framework Components ........................................................................................................... 44
Commodity/Trade Profiles by Direction of Flow ................................................................. 44
Data Needs to Quantify Direct Costs and Definitions of Delay ........................................... 44 Other Critical Data Elements .................................................................................................... 54
Chapter VI: Direct Costs Categories ....................................................................................... 56 Variable Direct Cost Categories: Shipper ................................................................................. 56 Variable Direct Cost Category: Carrier .................................................................................... 56 Commodity Classifications and Ports of Entry ......................................................................... 56
Center for International Intelligent Transportation Research Texas Transportation Institute Page ii
Shipper Costs ............................................................................................................................ 57
Variable Carrier Costs .............................................................................................................. 60
Chapter VII: Model Structure .................................................................................................. 63 Structure of the Spreadsheet Tool ............................................................................................. 63
Schematic Data Flows ........................................................................................................... 64
Chapter VIII: Bridge of the Americas Illustration ................................................................. 68 Number of Freight Truck Crossings ......................................................................................... 68 User Input Values in the Spreadsheet Tool .............................................................................. 68 Output Results from the Simulation ......................................................................................... 70
Results ....................................................................................................................................... 71 Conclusions ............................................................................................................................... 72
References .................................................................................................................................... 74 Appendix 1: Bridge of the Americas’ Details .......................................................................... 77
Appendix 2: Commodity Profiles (Ports of Entry) (By Value [2008]) .................................. 79 Appendix 3: Interview Instrument ........................................................................................... 89
Center for International Intelligent Transportation Research Texas Transportation Institute Page iii
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) ................................................................................................................................... 29 Figure III-2. Trends in Import Trade Weight through El Paso Ports of Entry (with Entire USA
and with Texas Alone) (Short Tons) ..................................................................................... 29 Figure III-3. Location Distribution of Juarez Maquiladoras Relative to Border Ports of Entry
(Source: http://www.pdnmapa.org/pdnmapa/index.htm) ..................................................... 37 Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of Raw
Materials/Intermediate Goods and Final Goods (Number Responding) .............................. 40
Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number) .... 41 Figure IV-3. Daily Peaks Identified by Respondents .................................................................. 42
Figure IV-4. Seasonal Peaks Identified by Shippers ................................................................... 42
Figure IV-5. Impacts on Delay on Supply Chains ....................................................................... 43 Figure IV-6. Shipper Responses on Ability to Pass Cost Increases ............................................ 43 Figure V-1. Map of BOTA Crossing Facilities (2009) ................................................................ 46
Figure V-2. Number of RFID Readings at El Paso BOTA Entering and Exiting Points
(Weekday BOTA RFID Readings between July and December 2009) ................................. 48
Figure V-3. Monthly NB Truck Crossing and RFID Counts at BOTA ....................................... 48 Figure V-4. Monthly NB Truck Volumes and RFID Average of Crossing Times at BOTA
(2009) .................................................................................................................................... 49
Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID Data
July-December 2009) ............................................................................................................ 49
Figure V-6. Hourly Average of Crossing Times: Comparison by Month (2009) ....................... 50 Figure V-7. Average of Crossing Times by Day of Week (July-December, 2009) .................... 51
Figure V-8. Fitted Lognormal Distributions of RFID Observations by Time Periods ................ 51 Figure V-9. Performance Measures from RFID Observations (Weekday Crossing Time by
Minute, September 2009) (BOTA) ....................................................................................... 53
Figure V-10. Crossing Time Distribution (BOTA) and Performance Measures/Statistics
(July-September 2009 BOTA) .............................................................................................. 54
Figure V-11. Various Components of the Framework (by Direction of Flows) ......................... 55 Figure VII-1. Structure of the Delay Cost Estimation Tool ......................................................... 64 Figure VII-2. Schematic Data Flow Diagram of the Spreadsheet Tool ....................................... 65
Figure VII-3. Delay Measures ..................................................................................................... 66 Figure VIII-1. Main Input Screen − DCET ................................................................................. 69
Figure VIII-2. Sample Screenshots of Output Reports − BOTA Illustration .............................. 70 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 ...................................... 78
Center for International Intelligent Transportation Research Texas Transportation Institute Page iv
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 ............. 25 Table II-2. Additional Perspectives on Wider Economic Implications and General Port
Efficiencies ........................................................................................................................... 26
Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and
Weight) ................................................................................................................................. 28 Table III-2. Northbound Crossing Volumes (Trucks) (El Paso Ports of Entry) and by
Loaded or Empty................................................................................................................... 30 Table III-3. El Paso Ports Import Classification and Value (2010) ............................................. 31
Table III-4. El Paso Port Export Classification and Value (2010) .............................................. 34 Table IV-1. Origin/Destination of Commodities Identified by Shippers .................................... 40
Table V-1. Fitted Crossing Time Distribution Parameters .......................................................... 52
Table VI-1. Average Imports Cargo Value per Loaded Truck (Northbound
Crossings El Paso) ................................................................................................................ 57 Table VI-2. Imports through El Paso Ports (2009) ...................................................................... 58
Table VI-3. Commercial Vehicle Values of Time in the United States ...................................... 62 Table VIII-1. Default Values − Bridge of the Americas, El Paso ............................................... 69
Table XI-1. Commodity Profile Brownsville Exports to Mexico ................................................ 79 Table XI-2. Commodity Profile Eagle Pass Exports to Mexico (Primarily Agriculture) ............ 80 Table XI-3. Commodity Profile El Paso Exports to Mexico (Primarily Maquila Products) ....... 81
Table XI-4. Commodity Profile Hidalgo Exports to Mexico ...................................................... 82 Table XI-5. Commodity Profile Laredo Exports to Mexico ........................................................ 83
Table XI-6. Commodity Profile Brownsville Imports to United States ...................................... 84 Table XI-7. Commodity Profile Eagle Pass Imports to United States ......................................... 85
Table XI-8. Commodity Profile El Paso Imports to United States .............................................. 86 Table XI-9. Commodity Profile Hidalgo Imports to United States ............................................. 87 Table XI-10. Commodity Profile Laredo Imports to United States ............................................. 88
Center for International Intelligent Transportation Research Texas Transportation Institute Page v
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 1
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 95th
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 2
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 2009. 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 non-
trivial. Hence, a balance must be struck.
Center for International Intelligent Transportation Research
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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)
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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 2010. 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 18-19 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.
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Figure I-2. Top Trading Partners (by Value and Weight − 2009) (Source: BTS-TBS)
-
–
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Figure I-3. Top Border Port Trading Partners (by Value and Weight − 2009)
–
–
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Figure I-4. Total Trade Flows for US-Mexico Ports (2005-2008) (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)
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Table I-1. Truck Volumes through All US-Mexico Ports of Entry (2010)
Port Name Year Trucks Percentage Percentage
AZ:Douglas 2010 25,504 0.5%
AZ:Lukeville 2010 90 0.0%
AZ:Naco 2010 2,512 0.1%
AZ:Nogales 2010 307,510 6.5%
AZ:San Luis 2010 37,103 0.8%
AZ:Sasabe 2010 0 0.0%
Arizona total:
7.9%
CA:Andrade 2010 342 0.0%
CA:Calexico 2010 0 0.0%
CA:Calexico East 2010 303,552 6.4%
CA:Otay Mesa 2010 729,605 15.4%
CA:San Ysidro 2010 0 0.0%
CA:Tecate 2010 55,208 1.2% California: 23%
NM:Columbus 2010 8,411 0.2%
NM:Santa Teresa 2010 78,879 1.7%
New Mexico:
1.8%
TX:Brownsville 2010 207,408 4.4%
TX:Del Rio 2010 55,852 1.2%
TX:Eagle Pass 2010 95,028 2.0%
TX:El Paso 2010 710,363 15.0%*
TX:Fabens 2010 0 0.0%
TX:Hidalgo 2010 459,331 9.7%
TX:Laredo 2010 1,585,682 33.4%
TX:Presidio 2010 9,298 0.2%
TX:Progreso 2010 43,327 0.9%
TX:Rio Grande City 2010 21,503 0.5%
TX:Roma 2010 6,417 0.1% Texas: 67.3%
Total 2010 4,742,925
* The highlighted categories show the regions with highest percentage of truck crossing volumes.
Center for International Intelligent Transportation Research
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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 re-
exported. 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.
TX:Brownsville 7%
TX:Del Rio 2% TX:Eagle Pass
3%
TX:El Paso 22%
TX:Fabens 0% TX:Hidalgo
14%
TX:Laredo 50%
TX:Presidio 0%
TX:Progreso 1%
TX:Rio Grande City 1%
TX:Roma 0%
Truck Volumes through Texas Ports 2010
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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, non-
tariff 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
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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 30-40 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.
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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.
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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 1938. 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.
Center for International Intelligent Transportation Research
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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) .
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 15
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.
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)
Electrical Machinery; Equipment and
Parts, 26.7%
Computer-Related Machinery and Parts,
19.3% Vehicles Other than Railway, 7.2%
Ceramic Products, 6.1%
Furniture; Lamps and Prefabricated
Buildings, 5.3%
Special Classification Provisions, 4.2%
Plastics and Articles, 3.6%
Sugars and Sugar Confectionery, 2.8%
Measuring and Testing Instruments,
2.1%
Wood and Articles, 1.9%
, 0 , 0 , 0 , 0
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 16
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)
Figure II-4. El Paso Ports’ Exports Value Profile (2010) (Top Eleven of 93 Truck Traded
Commodities) (Source: BTS-TBS)
Electrical Machinery; Equipment and Parts, 42.97%
Computer-Related Machinery and Parts,
25.89%
Measuring and Testing Instruments,
8.73%
Furniture; Lamps and Prefabricated
Buildings, 5.34%
Vehicles Other than Railway, 5.06%
Special Classification Provisions, 3.30% Not Knitted or
Crocheted Apparel, 1.42%
Plastics and Articles, 1.21% Other Made up
Textile Articles, 0.48%
Impregnated Fabrics, 0.46%
Electrical Machinery; Equipment and
Parts, 36.0%
Computer-Related Machinery and Parts,
23.2%
Plastics and Articles, 7.8%
Measuring and Testing Instruments,
5.1%
Copper and Articles, 3.2%
Vehicles Other than Railway, 2.7%
Articles of Iron and Steel, 2.6%
Paper and Paperboard, 2.2% Aluminum and
Articles, 2.1%
Impregnated Fabrics, 1.2%
Meat and Edible Offal, 1.2% Dairy Products, 0.9%
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 17
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, 1995.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 18
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.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 19
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).
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 20
Figure II-7. Top 12 of 48 Trading Partners by Import Value 2010 (Truck Inbound Flows-
El Paso POE’s) (Source: BTS-TBS)
Figure II-8. Top 12 of 48 Trading Partners by Import Weight 2010 (Truck Inbound Flows-
El Paso POE’s) (Source: BTS-TBS)
Texas(USA), 57.7% Michigan(USA),
10.5%
California(USA), 6.0%
Ohio(USA), 3.7%
Minnesota(USA), 2.8%
Pennsylvania(USA), 2.4%
Illinois(USA), 2.1%
Missouri(USA), 1.9%
Florida(USA), 1.6% Wisconsin(USA),
1.6% New Jersey(USA),
1.2% Tennessee(USA),
1.1%
Texas(USA), 51.6%
Michigan(USA), 9.1%
California(USA), 5.9%
Connecticut(USA), 3.5%
Pennsylvania(USA), 3.1%
Ohio(USA), 3.0%
Minnesota(USA), 2.9%
Wisconsin(USA), 2.7%
Illinois(USA), 2.0%
Missouri(USA), 2.0% New Mexico(USA), 1.9% Georgia(USA), 1.2%
Massachusetts(USA), 1.2%
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 21
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).
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 22
Figure II-9. Typical Border Crossing Stages for US-Mexico Border Crossings (Source,
Matisziw, 2005)
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 23
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 2001. 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.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 24
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.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 25
Table II-1. Summary of Perspectives Adopted in Assessing Economic Costs of Delay
Authors Approach Costs Region Aspects Considered
Ojah et al.
(2002) (9)
Factor cost/Direct costs
Social Cost
Congestion delays to
others in queue.
(Focus on effects of
coordination to one or
more stakeholders)
Direct- Inputs and
Environment
Delay data, fuel
prices, literature,
time valuation,
pollution costs.
Several Ports
along US-
Mexico
Border
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.
HLB Decision
Economics
(2006, 2007–
Mexicali):
Economic
Impacts &
True North
(11-17)
Static/Microeconomic
−Partial equilibrium
perspective
Indirect costs −
output and
employment costs
(macroeconomic)
Mexicali Cargo type
Directional aspect.
Delays treated as a cost
increase.
Risk analysis.
Direct, indirect and
induced effect
FAST lanes.
HLB (2004)
(Detroit–
Windsor
[D-W]) (18)
Same as HLB 2006, 2007
Indirect costs
(macroeconomic)
Detroit-
Windsor
Use of STRATBENCOST
to develop volume and
time forecasts for analysis
of three bridges at the D-W
border.
Belzer, 2003
(19, 20)
Factor costs Direct Ambassador
Bridge and
other bridges
Operating costs for trucks
valued at $2.32 per minute
and inventory transit costs.
RTI
International
(2007) (21)
Similar to HLB studies
Indirect costs
(macroeconomic)
FAST lanes,
Nogales,
Arizona
Impact of the FAST lanes
is the specific analysis goal
(FAST lanes introduced in
Nogales, in 2006)
Taylor et al.
(2003) (10)
Administrative costs
perspective
Agency costs and
other administrative
crossing costs from
uncertainties and
delays (fees, duties)
General Carrier costs and
manufacturer/shipper
costs
OCC (2004)
(22,23)
Similar to HLB Canadian
context
Goodchild et al.
(2007) (24)
Variability in delays
No costs Specific
Gateways
No economic costs
reported. Links delay
variability to output
elasticity
Kristjansson et
al. (2010) (3)
Regional integration-
intra-industry trade
(Grubel Lloyd Index)
(GLI)
No costs Specific
Gateways;
Cascade
Gateway,
Great Lakes
Corridor
Implications of variations
in GLI across corridors to
economic costs of delays.
No actual cost analysis
conducted.
Fischer, 2010
(Cambridge
Systematics)
(25)
Vehicle hours traveled
(delay) and partial
equilibrium methods
Indirect costs
(macroeconomic)
Canadian
context
Actual estimates of delays
not reported.
Methodology discussed.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 26
Table II-2. Additional Perspectives on Wider Economic Implications and
General Port Efficiencies
Authors Approach Implications
Limao and Venables
(1999) (26)
10% increase in
transport costs
associated with 20%
reduction in trade
volume.
Trade: Indirect benefit
Hummels (2001) (27) Inventory costs due
to transport delays
equivalent to 0.8%
per day of delay of
the value of goods
delivered.
Inventory management:
Direct cost from
uncertainties.
Kent and Fox (2004)
(28)
Effects of port
inefficiency on
welfare
Applicable to ports like
Laredo that are associated
with longer haul moves.
Haralambides and Kent
(2004) (8)
Effects of port
inefficiency on
welfare
Applicable to ports like
Laredo that are associated
with longer haul moves.
Huang and Whalley
(2008) (29)
Effects of port
inefficiency on
welfare
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.
Center for International Intelligent Transportation Research
Texas Transportation Institute Page 27
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.
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Table III-1. Imports Total Weight by Land Mode (Trade with USA and Texas) (Value and Weight)§
Year Trader Partner
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 $5,253,472,161 769,132
1996 USA MEXICO 2402 El Paso - Texas $11,601,370,475 1,938,915 Texas $5,635,791,343 1,050,210
1997 USA MEXICO 2402 El Paso - Texas $12,342,837,252 1,919,563 Texas $5,655,309,456 992,023
1998 USA MEXICO 2402 El Paso - Texas $14,609,540,221 2,163,031 Texas $6,253,885,378 991,533
1999 USA MEXICO 2402 El Paso - Texas $16,822,150,647 2,303,713 Texas $8,026,982,212 1,194,074
2000 USA MEXICO 2402 El Paso - Texas $19,162,738,608 2,431,439 Texas $9,172,475,227 1,253,441
2001 USA MEXICO 2402 El Paso - Texas $19,156,612,097 2,444,918 Texas $8,900,508,521 1,169,681
2002 USA MEXICO 2402 El Paso - Texas $19,762,057,224 2,393,390 Texas $9,620,016,010 1,161,951
2003 USA MEXICO 2402 El Paso - Texas $19,745,171,951 2,396,149 Texas $9,312,135,706 1,123,994
2004 USA MEXICO 2402 El Paso - Texas $21,875,628,271 3,618,372 Texas $12,155,269,477 2,279,216
2005 USA MEXICO 2402 El Paso - Texas $22,216,587,475 3,463,483 Texas $11,246,226,743 2,025,717
2006 USA MEXICO 2402 El Paso - Texas $23,528,112,532 3,419,745 Texas $11,429,703,442 1,906,324
2007 USA MEXICO 2402 El Paso - Texas $25,949,296,025 3,054,959 Texas $12,320,195,844 1,742,412
2008 USA MEXICO 2402 El Paso - Texas $24,803,329,148 2,861,107 Texas $13,251,291,021 1,595,711
2009 USA MEXICO 2402 El Paso - Texas $21,156,892,085 2,261,460 Texas $11,579,415,114 1,248,330
2010 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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 29
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)
$0
$5,000,000,000
$10,000,000,000
$15,000,000,000
$20,000,000,000
$25,000,000,000
$30,000,000,000
1995 1997 1999 2001 2003 2005 2007 2009
Imports Value byTruck_Entire USA
Imports Value byTruck_Entire Texas
Linear ( Imports Value byTruck_Entire USA)
Linear ( Imports Value byTruck_Entire Texas)
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
1995 1997 1999 2001 2003 2005 2007 2009
Imports Weight by Truck (USShort Tons)_Entire USA
Imports Weight by Truck (USShort Tons)_Entire Texas
Linear ( Imports Weight byTruck (US Short Tons)_EntireUSA)
Linear ( Imports Weight byTruck (US Short Tons)_EntireTexas)
Center for International Intelligent Transportation Research Texas Transportation Institute Page 30
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)
Empty Truck
Containers
(Number)
TX:El Paso 1995 606,742 296,000 281,000 NA NA
TX:El Paso 1996 556,134 245,000 340,000 280,867 287,479
TX:El Paso 1997 582,707 308,000 289,000 297,663 296,006
TX:El Paso 1998 605,980 312,000 294,000 256,236 163,036
TX:El Paso 1999 673,003 343,000 329,000 360,982 305,394
TX:El Paso 2000 720,406 363,000 365,000 361,412 326,812
TX:El Paso 2001 660,583 335,000 330,000 360,517 306,638
TX:El Paso 2002 705,199 375,000 329,000 382,193 332,738
TX:El Paso 2003 659,614 346,000 314,000 368,562 296,860
TX:El Paso 2004 719,545 383,000 337,000 409,093 308,152
TX:El Paso 2005 740,654 393,000 341,000 430,768 304,083
TX:El Paso 2006 744,951 373,000 371,000 418,026 339,769
TX:El Paso 2007 782,936 398,000 382,000 402,456 356,863
TX:El Paso 2008 758,856
316,731 315,947 384,586 367,988
TX:El Paso 2009 644,272
316,731 315,947 336,119 303,777
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 31
Table III-3. El Paso Ports Import Classification and Value (2010)**
Commodity Code Commodity Description 2010 Percentage of Total Import
1 Live Animals $3,000 0.0%
3 Fish and Crustaceans $2,705 0.0%
4 Dairy Products $675,382 0.0%
5 Products of Animal Origin $2,277,675 0.0%
6 Live Trees and Plants $258,439 0.0%
7 Edible Vegetables and Roots $14,365,683 0.1%
8 Edible Fruit and Nuts $116,794,167 0.4%
9 Coffee; Tea and Spices $921,026 0.0%
10 Cereals $10,154 0.0%
11 Malts; Starches and Inulin $388,347 0.0%
12 Oil Seeds and Oleaginous Fruits $196,477 0.0%
14 Vegetable Plaiting Materials $127,001 0.0%
16 Preparations of Fish and Meat $3,427,461 0.0%
17 Sugars and Sugar Confectionery $49,897,376 0.2%
18 Cocoa and Cocoa Preparations $14,545,289 0.1%
19 Preparations of Cereals and Flour $19,920,538 0.1%
20 Preparations of Vegetables; Fruits and Nuts $19,308,834 0.1%
21 Miscellaneous Edible Preparations $898,630 0.0%
22 Beverages; Spirits and Vinegar $1,872,182 0.0%
23 Food Residues and Waste $23,665 0.0%
25 Salt; Sulfur; Plaster and Cement $2,938,182 0.0%
26 Ores; Slag and Ash $11,193 0.0%
27 Mineral Fuels; Oils and Waxes $347,079 0.0%
28 Inorganic Chemicals $10,296,191 0.0%
30 Pharmaceutical Products $8,398,650 0.0%
31 Fertilizers $880,601 0.0%
32 Tanning or Dyeing Extracts $564,018 0.0%
33 Essential Oils and Resinoids $791,387 0.0%
34 Soap and Organic Surface-Active Agents $11,183,301 0.0%
35 Albuminoidal Substances; Glues and Enzymes $49,831 0.0%
36 Explosives $649,421 0.0%
37 Photographic Goods $382,835 0.0%
38 Miscellaneous Chemical Products $32,471,973 0.1%
39 Plastics and Articles $329,079,049 1.2%
**
BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to
United States.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 32
Table III-3. El Paso Ports Import Classification and Value (2010)†† (continued) Commodity Code Commodity Description 2010 Percentage of Total
40 Rubber and Articles $101,930,921 0.4%
41 Raw Hides and Skins $8,399,698 0.0%
42 Articles of Leather and Handbags $5,054,872 0.0%
43 Furskins and Artificial Fur $1,208 0.0%
44 Wood and Articles $62,730,334 0.2%
47 Pulp of Wood and Paperboard $1,401,108 0.0%
48 Paper and Paperboard $83,986,751 0.3%
49 Printed Books $75,800,657 0.3%
52 Cotton $1,470,664 0.0%
54 Man-made Filaments $2,951,932 0.0%
55 Man-made Staple Fibers $1,054,544 0.0%
56 Wadding; Felt and Nonwovens $15,382,943 0.1%
57 Carpets and Other Textile Floor Coverings $190,308 0.0%
58 Special Woven Fabrics $2,243,501 0.0%
59 Impregnated Fabrics $124,937,859 0.5%
60 Knitted or Crocheted Fabrics $195,738 0.0%
61 Knitted or Crocheted Apparel $74,376,453 0.3%
62 Not Knitted or Crocheted Apparel $387,018,098 1.4%
63 Other Made up Textile Articles $130,098,548 0.5%
64 Footwear $7,580,074 0.0%
65 Headgear $1,298,161 0.0%
66 Umbrellas and Walking Sticks $148,151 0.0%
67 Feathers and Down $6,341 0.0%
68 Stone; Plaster; Cement and Asbestos $31,767,316 0.1%
69 Ceramic Products $37,894,499 0.1%
70 Glass $40,882,410 0.2%
71 Pearls; Stones; Metals and Imitation Jewelry $14,239,047 0.1%
72 Iron and Steel $13,745,410 0.1%
73 Articles of Iron and Steel $87,341,056 0.3%
74 Copper and Articles $40,785,155 0.2%
75 Nickel and Articles $795,991 0.0%
76 Aluminum and Articles $115,592,924 0.4%
78 Lead and Articles $858,313 0.0%
††
BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to
United States.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 33
Table III-3. El Paso Ports Import Classification and Value (2010)‡‡ (continued) Commodity Code Commodity Description 2010 Percentage of Total
79 Zinc and Articles $372,000 0.0%
80 Tin and Articles $1,271,850 0.0%
81 Other Base Metals and Cermets $611,350 0.0%
82 Tools of Base Metal $1,457,264 0.0%
83 Miscellaneous Articles of Base Metals $104,995,101 0.4%
84 Computer-Related Machinery and Parts $7,032,763,057 25.9%
85 Electrical Machinery; Equipment and Parts $11,674,763,562 43.0%
86 Locomotives and Traffic Signals $584,055 0.0%
87 Vehicles Other than Railway $1,374,454,791 5.1%
88 Aircraft; Spacecraft and Parts $39,320,563 0.1%
89 Ships and Boats $8,360,190 0.0%
90 Measuring and Testing Instruments $2,370,886,166 8.7%
91 Clocks; Watches and Parts $34,503,793 0.1%
92 Musical Instruments and Parts $126,357 0.0%
93 Arms and Ammunition and Parts $3,505,220 0.0%
94 Furniture; Lamps and Prefabricated Buildings $1,451,488,208 5.3%
95 Toys; Games and Sport Equipment $37,710,197 0.1%
96 Miscellaneous Manufactured Articles $17,283,986 0.1%
97 Works of Art and Antiques $278,142 0.0%
98 Special Classification Provisions $897,872,636 3.3%
TOTAL $27,168,727,215 100.0%
‡‡
BTS-TBS Data and 2-digit commodity codes as defined by BTS. These are northbound flows from Mexico to
United States.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 34
Table III-4. El Paso Port Export Classification and Value (2010)§§
Commodity Code Commodity Description 2010 Percentage of Total
1 Live Animals $4,851,141 0.0%
2 Meat and Edible Offal $246,555,140 1.2%
3 Fish and Crustaceans $1,902,449 0.0%
4 Dairy Products $184,849,952 0.9%
5 Products of Animal Origin $15,392,651 0.1%
6 Live Trees and Plants $257,877 0.0%
7 Edible Vegetables and Roots $24,580,614 0.1%
8 Edible Fruit and Nuts $65,628,706 0.3%
9 Coffee; Tea and Spices $596,350 0.0%
10 Cereals $6,001,216 0.0%
11 Malts; Starches and Inulin $4,312,701 0.0%
12 Oil Seeds and Oleaginous Fruits $14,270,125 0.1%
13 Lac; Gums; Resins and Saps $52,172 0.0%
14 Vegetable Plaiting Materials $35,670 0.0%
15 Animal or Vegetable Fats and Oils $30,810,045 0.1%
16 Preparations of Fish and Meat $9,088,630 0.0%
17 Sugars and Sugar Confectionery $59,646,667 0.3%
18 Cocoa and Cocoa Preparations $11,012,116 0.1%
19 Preparations of Cereals and Flour $27,588,410 0.1%
20 Preparations of Vegetables; Fruits and Nuts $15,018,552 0.1%
21 Miscellaneous Edible Preparations $37,880,085 0.2%
22 Beverages; Spirits and Vinegar $16,444,818 0.1%
23 Food Residues and Waste $7,824,443 0.0%
24 Tobacco and Manufactured Tobacco $153,928 0.0%
25 Salt; Sulfur; Plaster and Cement $4,049,652 0.0%
26 Ores; Slag and Ash $60,762,287 0.3%
27 Mineral Fuels; Oils and Waxes $140,444,191 0.7%
28 Inorganic Chemicals $24,900,954 0.1%
29 Organic Chemicals $23,167,421 0.1%
30 Pharmaceutical Products $53,307,090 0.3%
31 Fertilizers $2,937,834 0.0%
32 Tanning or Dyeing Extracts $49,241,588 0.2%
33 Essential Oils and Resinoids $6,506,994 0.0%
34 Soap and Organic Surface-Active Agents $20,689,673 0.1%
35 Albuminoidal Substances; Glues and Enzymes $27,680,657 0.1%
§§
Southbound flows from United States to Mexico.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 35
Table III-4. El Paso Port Export Classification and Value (2010)*** (continued) Commodity Code Commodity Description 2010 Percentage of Total
36 Explosives $62,163 0.0%
37 Photographic Goods $39,781,566 0.2%
38 Miscellaneous Chemical Products $49,224,991 0.2%
39 Plastics and Articles $1,640,134,462 7.8%
40 Rubber and Articles $169,182,932 0.8%
41 Raw Hides and Skins $29,377,861 0.1%
42 Articles of Leather and Handbags $33,051,434 0.2%
43 Furskins and Artificial Fur $79,836 0.0%
44 Wood and Articles $61,238,659 0.3%
45 Cork and Articles $41,215 0.0%
47 Pulp of Wood and Paperboard $21,050,859 0.1%
48 Paper and Paperboard $453,054,448 2.2%
49 Printed Books $58,330,869 0.3%
50 Silk $15,160 0.0%
51 Wool and Animal Hair $2,243,987 0.0%
52 Cotton $81,663,210 0.4%
53 Other Vegetable Fibers and Paper Yarn $79,228 0.0%
54 Man-made Filaments $88,002,586 0.4%
55 Man-made Staple Fibers $36,816,256 0.2%
56 Wadding; Felt and Nonwovens $104,832,381 0.5%
57 Carpets and Other Textile Floor Coverings $20,631,409 0.1%
58 Special Woven Fabrics $31,693,187 0.2%
59 Impregnated Fabrics $261,441,836 1.2%
60 Knitted or Crocheted Fabrics $23,356,498 0.1%
61 Knitted or Crocheted Apparel $36,680,680 0.2%
62 Not Knitted or Crocheted Apparel $39,933,076 0.2%
63 Other Made up Textile Articles $46,200,073 0.2%
64 Footwear $447,155 0.0%
65 Headgear $1,594,783 0.0%
66 Umbrellas and Walking Sticks $720,996 0.0%
67 Feathers and Down $231,219 0.0%
68 Stone; Plaster; Cement and Asbestos $23,037,927 0.1%
69 Ceramic Products $20,532,441 0.1%
70 Glass $73,092,864 0.3%
71 Pearls; Stones; Metals and Imitation Jewelry $25,754,700 0.1%
***
Southbound flows from United States to Mexico.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 36
Table III-4. El Paso Port Export Classification and Value (2010)††† (continued) Commodity Code Commodity Description 2010 Percentage of Total
72 Iron and Steel $156,779,489 0.7%
73 Articles of Iron and Steel $541,659,538 2.6%
74 Copper and Articles $677,844,279 3.2%
75 Nickel and Articles $12,543,749 0.1%
76 Aluminum and Articles $436,644,670 2.1%
79 Zinc and Articles $9,723,301 0.0%
80 Tin and Articles $14,851,983 0.1%
81 Other Base Metals and Cermets $20,677,378 0.1%
82 Tools of Base Metal $50,877,969 0.2%
83 Miscellaneous Articles of Base Metals $109,689,443 0.5%
84 Computer-Related Machinery and Parts $4,875,763,075 23.2%
85 Electrical Machinery; Equipment and Parts $7,568,936,682 36.0%
86 Locomotives and Traffic Signals $2,774,547 0.0%
87 Vehicles Other than Railway $565,377,537 2.7%
88 Aircraft; Spacecraft and Parts $54,933,025 0.3%
89 Ships and Boats $143,610 0.0%
90 Measuring and Testing Instruments $1,082,382,595 5.1%
91 Clocks; Watches and Parts $2,193,128 0.0%
92 Musical Instruments and Parts $345,269 0.0%
93 Arms and Ammunition and Parts $2,572,392 0.0%
94 Furniture; Lamps and Prefabricated Buildings $118,578,721 0.6%
95 Toys; Games and Sport Equipment $22,842,336 0.1%
96 Miscellaneous Manufactured Articles $17,276,975 0.1%
97 Works of Art and Antiques $143,215 0.0%
98 Special Classification Provisions $796,649 0.0%
TOTAL $21,020,132,352 100.0%
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 37
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: http://www.pdnmapa.org/pdnmapa/index.htm)
‡‡‡
Source: Maquila Stakeholder meeting with Cambridge Systematics, TTI in El Paso, November 2010.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 38
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-on-
board (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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 39
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 bi-
national 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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 40
Figure IV-1. Typical Supply Chains of Shippers of Respondents Indicating Movements of
Raw Materials/Intermediate Goods and Final Goods (Number Responding)
Table IV-1. Origin/Destination of Commodities Identified by Shippers
Product Origin
Location/
Facility
Destination
Location/
Facility
Product Origin
Location/
Facility
Destinati
on
Location/
Facility
# Shippers
Responding
Inbound(I) Outbound
(O)
Raw
Materials
Electronic
parts
I Asia Ciudad
Juarez
Finished
Goods,
Electronics
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
Refresh-
mint
O Ciudad
Juarez
USA 1/9
02
46
8
Typical Supply Chain
Raw materials and componentscome from Asia to Californiaand from California to El Pasoand Juarez. Finished productgoes from Juarez to El Paso andto the rest of the U.S.Raw materials and componentscome from inner Mexico toJuarez. Finished product goesfrom Juarez to El Paso and tothe rest of Texas and California.
Raw materials and componentscome fromEl Paso to Juarez.Finished product goes fromJuarez to El Paso.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 41
Figure IV-2. Shipper Responses on Variation in Crossing Times (By Respondent Number)
minimum
maximum
average
0
5
10
15
20
1 2 3 4 5 6 7 8 9
Ho
urs
Variation in Travel Times
Center for International Intelligent Transportation Research Texas Transportation Institute Page 42
Figure IV-3. Daily Peaks Identified by Respondents
Figure IV-4. Seasonal Peaks Identified by Shippers
0
0.5
1
1.5
2
2.5
3
Daily Fluctuation
No Significant Variation
Peak in the morning around8.00 am
Peak in the afternoon around4.30 pm
Varies all through the day
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Seasonal Fluctuation
No Significant Variation
June-September
October-December
Daily Variation
Center for International Intelligent Transportation Research Texas Transportation Institute Page 43
Figure IV-5. Impacts on Delay on Supply Chains
Figure IV-6. Shipper Responses on Ability to Pass Cost Increases
12%
50%
13%
25%
How the Supply Chain is Affected
Incur delay
Hire air carrier
No major disruption
Adjust supply chains
02
46
8
Who Absorbs the Costs of Delays?
Costs absorbed by Company
Costs absorbed by client for expedited delivery
Cost absorbed by the final customer
Center for International Intelligent Transportation Research Texas Transportation Institute Page 44
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
Center for International Intelligent Transportation Research Texas Transportation Institute Page 45
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 46
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
(http://apps.cbp.gov/bwt/). 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.
RFID Reader R2
RFID Reader R1
U.S. Federal Inspection
Facility
Texas State Inspection
Facility
Mexican
Export Facility
Center for International Intelligent Transportation Research Texas Transportation Institute Page 47
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 2009. As shown in the plot, the RFID
samples captured about 13 percent of the whole NB truck crossings during the sampling period.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 48
(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)
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.
0
100
200
300
400
500
600
700
6 7 8 9 10 11 12 13 14 15 16 17 18
Total Hourly RFID Counts at Entering Point
July
Aug
Sep
Oct
Nov
Dec
0
100
200
300
400
500
600
700
6 7 8 9 10 11 12 13 14 15 16 17 18 19
Total Hourly RFID Counts at Exit Point
July
Aug
Sep
Oct
Nov
Dec
0
5000
10000
15000
20000
25000
30000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2009 Monthly NB Truck Crossings at BOTA
Actual NB Trucks RFID Counts
Center for International Intelligent Transportation Research Texas Transportation Institute Page 49
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 2009. 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.
Figure V-5. Hourly Average of Crossing Time and Standard Deviations (BOTA RFID
Data July-December 2009)
0
10
20
30
40
50
60
70
80
90
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Cro
ssin
g Ti
me
(m
inu
tes)
Nu
mb
er
of
NB
Tru
cks
NB Truck Volume Avg. Crossing Time (RFID Obs.)
0
10
20
30
40
50
60
70
6 7 8 9 10 11 12 13 14 15 16 17 18
Ave
rage
Cro
ssin
g Ti
me
(m
inu
tes)
Period (Hour)
Average of Crossing Time StdDev of Crossing Time
Center for International Intelligent Transportation Research Texas Transportation Institute Page 50
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 time12
of 48 minutes in 2008. 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-the-
week” 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. www.bta.org
0
10
20
30
40
50
60
70
6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00
Aver
age
Cros
sing
Tim
e (m
inut
es)
Period (hour)
July
Aug
Sep
Oct
Nov
Dec
Center for International Intelligent Transportation Research Texas Transportation Institute Page 51
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
0
1000
2000
3000
4000
5000
6000
0
10
20
30
40
50
60
70
80
Monday Tuesday Wednesday Thursday Friday
RFI
D C
ou
nts
Ave
rage
Cro
ssin
g Ti
me
(m
inu
tes)
Average of Crossing Time Count of RFID
Center for International Intelligent Transportation Research Texas Transportation Institute Page 52
Table V-1 represents the fitted parameter values with lognormal distributions.
Table V-1. Fitted Crossing Time Distribution Parameters
Period
Number of
Samples
Lognormal Distribution
Mean Crossing Time (minutes)
Standard Deviation (minutes)
AM Peak (06:00 - 10:00)
9,049 57.0 27.8
Off Peak (10:00 - 16:00)
10,270 49.0 29.5
PM Peak (16:00 - 19:00)
2,548 32.9 25.9
Whole Day (06:00 – 19:00)
21,867 49.5 28.9
Performance Measures for Border Crossing Times
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 2009. 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 95th
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 95th
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.13
13
Travel Time Reliability Measures.
http://www.ops.fhwa.dot.gov/perf_measurement/reliability_measures/index.htm. (35)
Center for International Intelligent Transportation Research Texas Transportation Institute Page 53
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 95th
percentile
0
20
40
60
80
100
120
140
Cro
ssin
g Ti
me
(m
inu
tes)
RFID obervations during weekdays of September 2009
95th Pecentile Crossing Time
Average Crossing TimeBuffer Time
MinimumCrossing Time
Center for International Intelligent Transportation Research Texas Transportation Institute Page 54
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, 95th
percentile crossing time was 98
minutes and the buffer time was calculated as 40 minutes, as shown in the Figure V-10.
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.
Lognorm(49.525, 28.949) Shift=-1.6951
Value
s x 10
^-2
0.0
0.5
1.0
1.5
2.0
2.5
0 20 40 60 80 100
120
< >5.0% 5.0%90.0%
15.8 102.6
Delay by Median Crossing Time
Delay by Average Crossing Time
Buffer Time
Med
ian
CT
Ave
rage
CT
95th
Per
cent
ile C
T
Center for International Intelligent Transportation Research Texas Transportation Institute Page 55
Figure V-11. Various Components of the Framework (by Direction of Flows)
Crossing Time (Archived/Near Real Time)
Trade Profiles at Ports of Entry & Freight Movement
Patterns
Crossing Volumes Cargo information (Loaded,
Value, Weight)
Direct Economic Variable Costs
Center for International Intelligent Transportation Research Texas Transportation Institute Page 56
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).
Center for International Intelligent Transportation Research Texas Transportation Institute Page 57
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.
Table VI-1. Average Imports Cargo Value per Loaded Truck
(Northbound Crossings El Paso)
PORT YEAR
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)
EL PASO
2004 $12,469,348,486 $12,155,269,000 409,093 $29,713
2005 $11,309,017,253 $11,246,227,000 430,768 $26,107
2006 $11,513,235,758 $11,429,703,000 418,026 $27,342
2007 $12,493,795,483 $12,320,196,000 402,456 $30,613
2008 $13,923,529,950 $13,251,291,000 384,586 $34,456
2009 $12,250,863,192 $11,579,415,114 336,119 $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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 58
Table VI-2. Imports through El Paso Ports (2009)
POE 1-Digit SITC
5-Digit SITC
Top 25 RANK
TRADE VALUE
POE 1-Digit SITC
5-Digit SITC
Top 25 RANK
TRADE VALUE
EL PASO
7
76160 1 $3,610,013,86
8
EL PASO
7
71322 20 $191,113,402
75230 2 $2,807,041,80
9 77884 23 $165,804,360
78120 3 $1,552,590,99
7 77551 24 $163,832,342
77313 4 $1,478,732,33
6
8
82119 8 $695,905,824
78439 6 $725,377,610 87229 9 $661,838,844
78219 7 $696,582,383 87221 11 $445,923,612
77521 10 $455,037,963 84140 17 $259,295,113
77261 12 $372,816,644 87465 21 $180,015,882
76412 13 $339,980,659 89399 22 $165,947,083
77316 15 $280,367,521 87461 25 $147,282,365
71631 16 $260,017,133 9 93100 5 $911,418,487
75197 18 $230,873,563 1 11230 14 $285,973,546
74780 19 $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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 59
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, Hi = annual unit holding cost per $1 value of inventory. Si = dollar value of a
truckload of commodity i. Currently default values of Hi 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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 60
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 95th
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 $144.22 to $192.83
(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)
Center for International Intelligent Transportation Research Texas Transportation Institute Page 61
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 62
Table VI-3. Commercial Vehicle Values of Time in the United States
Source Specific
Purpose
Values Reported
Dollars per hour
Updated to
2009 Dollar
Amount
(/hour)
Comments
Haning &
MacFarland
(1963) (39)
Project
evaluation
17.4 - 22.6 (in 1998
dollars)
21.5 – 27.97 First study to estimate commercial
value of time. Truck operators.
Minimum and maximum values of
time based on low to high utilization
of time.
McFarland and
Chui (1986)
(40)
Project
evaluation
8.03 (1985 dollars) 14.99 For small cars, large, medium cars,
and pickup trucks.
Waters et al.
(1995) (41)
14.5 - 35.6 (in 1998
dollars)
17.9 – 44.05 Cargo vehicles. Minimum value =
40% of driver wages. Maximum = all
time savings converted to additional
business.
Buffington &
MacFarland
(1975) (42)
Evaluation Single unit 2-4 axles =
15.59
Other singles unit =
18.61
Semi combination ≤ 4
axles = 23.20
All others ≥ 5 axles =
25.75 (in 1985 dollars)
= 29.11
= 34.75
= 43.30
= 48.08
Updated American Association of
State Highway and Transportation
Officials (AASHTO) values.
Average = $38.80/hour (in 2006
dollars)
Kawamura
(1999) (43)
Toll road
application
a) 26.8 (std dev=43.68)
b) 23.4 (std. de=32)
= 32.30
= 28.30
California truck operators
Lewis NCHRP
2-18 (1994)
(44)
> 100 (in 1994 dollars) 135.69 Scheduling benefits
HERS
(FHWA) (38)
21.95 for drivers + 9.63
for vehicle/inventory
carrying costs (in 1997
dollars)
27.59 + 12.10
= 39.69
Wage costs and inventory carrying
costs
Center for International Intelligent Transportation Research Texas Transportation Institute Page 63
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 64
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.
REPORT_Cost
Calculation
Input Parameters
No.TruckComponent TimeComponent CostComponent
Base_Stats
RFID_Sample
REPORT_Time REPORT_TrkVol
Default
User Input
Daily costs
Delay costs, Average delay, No. trucks delayed
Delay cutoff times, % of trucks delayed
Delay costs by commodity group
No. NB trucks Delay hours by cutoff criteria
Stat
s ab
ou
t C
ross
ing
tim
es a
nd
Del
ays
Mo
nth
ly N
B T
ruck
C
ross
ings
at
BO
TA
Daily NB Trucks
An
nu
al/m
on
thly
NB
tr
uck
s at
BO
TA
Avg. cargo value, commodity distribution, etc.
Cost parameter values
Monte Carlo Simulation
crossing times
SimResults
Sim
ula
tio
n R
esu
lts
fro
m e
ach
iter
atio
n
Center for International Intelligent Transportation Research Texas Transportation Institute Page 65
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.
RISK ANALYSIS (MONTE CARLO SIMULATION)
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
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.
Historical Freight Flow Statistics &
RFID Observations
Center for International Intelligent Transportation Research Texas Transportation Institute Page 66
(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) = 275.6 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:
316,731 trucks / 275.6 = 1,149 trucks/day.
Laden-Empty Truck Ratio
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-
Lognorm(49.303, 28.949) Shift= -1.5571
Va
lue
s x 1
0^
-2
0.0
0.5
1.0
1.5
2.0
2.5
0
20
40
60
80
10
0
12
0
< >5.0% 5.0%90.0%
15.8 102.5
Delay by Average Crossing Time
Average Crossing Time
Delay
Lognorm(49.303, 28.949) Shift= -1.5571
Va
lue
s x 1
0^
-2
0.0
0.5
1.0
1.5
2.0
2.5
0
20
40
60
80
10
0
12
0
< >5.0% 5.0%90.0%
15.8 102.5
Delay by Median Crossing Time
MedianCrossing Time
Delay
Lognorm(49.303, 28.949) Shift= -1.5571
Va
lue
s x 1
0^
-2
0.0
0.5
1.0
1.5
2.0
2.5
0
20
40
60
80
10
0
12
0
< >5.0% 5.0%90.0%
15.8 102.5
95%tile Buffer Time
95%tileCrossing Time
Average
BufferTime
Delay
Center for International Intelligent Transportation Research Texas Transportation Institute Page 67
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 68
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 69
Figure VIII-1. Main Input Screen − DCET
Table VIII-1. Default Values − Bridge of the Americas, El Paso
Parameter Value Parameter Value
Crossing Times
Average CT 47.5 minutes
Delay Times
by Average CT 26.7 minutes
Median CT 41.0 minutes by Median CT 27.2 minutes
95%tile CT 98.0 minutes by 95%tile CT 28.6 minutes
% of Trucks Delayed
by Average CT 42.80% Truck Volume Distribution by
Commodity Group (by Top
25 imports)
JIT 78.30%
by Median CT 53.50% Non-JIT 20.00%
by 95%tile CT 6.00% Perishable 0%
Idling/Creeping Fuel
Consumption
Loaded 4 gallons/hour Non-perishable 0%
Empty 3.5
gallons/hour Other 1.70%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 70
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.
Figure VIII-2. Sample Screenshots of Output Reports − BOTA Illustration
(50%tile+) (95%tile+)
Average Median
Reliability Cost -
Buffer Time
$4,809,890 $5,469,138 $2,387,898
Just-In-Time $3,237,843 $3,512,196 $2,229,905Carrier Costs $987,252 $1,255,974
Shipper Costs $2,250,591 $2,256,222 $2,229,905
Non-JIT $399,544 $468,569 $145,956Carrier Costs $252,778 $321,583
Shipper Costs $146,766 $146,986 $145,956
Perishable $0 $0 $0Carrier Costs $0 $0
Shipper Costs $0 $0 $0
Non-Perishable $0 $0 $0Carrier Costs $0 $0
Shipper Costs $0 $0 $0
Other $32,950 $38,643 $12,037Carrier 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 $0
Delay Cutoff Time 48 minutes 41 minutes 98 minutes
PER-HOUR COSTS BY COMMODITY GROUP
Per-hour
Delay Cost
($/hour)
$39.88
$0.84
$564.16
$39.88
$0.13
$144.22
$39.88
$0.48
$192.83
$39.88
$0.13
$144.22
$39.88
$0.13
$144.22
$39.88
Estimated Annual
Cost
Carrier Cost
Commodity Group
JIT (Comm 1)
Carrier Cost
Regualr Shipper Cost (Typical delay)
Non-JIT (Comm 2)
Delay Cutoff Time Criteria
Reliability Cost (Delay over 95%tile)
Carrier Cost
Regualr Shipper Cost (Typical delay)
Empty Truck
Carrier Cost
Non-perishable (Comm 4)
Carrier Cost
Regualr Shipper Cost (Typical delay)
Reliability Cost (Delay over 95%tile)
Reliability Cost (Delay over 95%tile)
Other (Comm 5)
Reliability Cost (Delay over 95%tile)
Regualr Shipper Cost (Typical delay)
Perishable (Comm 3)
Carrier Cost
Regualr Shipper Cost (Typical delay)
Reliability Cost (Delay over 95%tile)
Center for International Intelligent Transportation Research Texas Transportation Institute Page 71
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
Center for International Intelligent Transportation Research Texas Transportation Institute Page 72
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 73
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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 74
REFERENCES
1. Hanson, G. U.S.-Mexico Integration and Regional Economies: Evidence from Border City
Pairs. Journal of Urban Economics, Volume 50, Issue 2. 2001.
2. Cambridge Systematics. Texas NAFTA Study Update. Final Report, Prepared for Texas
Department of Transportation, 2007.
3. 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, 2010.
4. Anderson, J.E., and E. van Wincoop. Borders, Trade, and Welfare. NBER Working Paper
Series. 8515. Available at: http://www.nber.org/papers/w8515. 2001.
5. Beilock, R., P. Boneva, G. Jostova, K. Kostadinova, and D. Vassileva. 1996. Road
Conditions, Border Crossings and Freight Rates in Europe and Western Asia.
Transportation Quarterly. 50(1), pp. 79-89.
6. Matisziw, T. Modeling Transnational Surface Freight Flow and Border Crossing
Improvement. Doctoral Dissertation, Ohio State University, 2005.
7. Fox, A., J. Francois, and M.P. Kent. Measuring Border Crossing Costs and their Impact on
Trade Flows, pp. 1-17. 2004.
8. 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. 171-183. 2004.
9. 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,
2002. http://www.borderplanning.fhwa.dot.gov/TTIstudy/FOA_english.htm.
10. Taylor, J., D. Robideaux, and G. Jackson. US-Canada Transportation and Logistics: Border
Impacts and Costs, Causes, and Possible Solutions. Transportation Journal. 2003.
11. 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 2005.
12. 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 2005.
13. 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 2006.
14. 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 2004.
15. HLB Decision Economics: Imperial Valley-Mexicali Economic Delay Study: Identification
of data needs. September 2007.
16. 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.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 75
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 2004.
19. 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 2007.
22. Ontario Chamber of Commerce Studies (OCC). Develop Estimates of Costs of Border
Delays on the Province of Ontario and its Businesses. 2004.
23. OCC Borders and Trade Development Committee. Cost of Delays to the United States
Economy. Ontario Chamber of Commerce. 2005.
24. 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, 2007. (Also presented at the Transportation Research Board
Annual Meeting, 2007, Paper #08-0558.)
25. Cambridge Systematics. Border Economic Impacts Study. 2008. www.thetbwg.org.
Accessed, 2009.
26. Limao, N., and A. Venables. Infrastructure, Geographical Disadvantage, and Transport
Costs. World Bank Policy Research Paper No. 2257, 1999.
27. Hummels, D. Time as a Trade Barrier. Working Paper: Purdue University. July. 2001. 28. Fox, A., and M. P. Kent. Measuring Border Crossing Costs and their Impact on Trade
Flows: The United States-Mexican Trucking Case. Unpublished Manuscript. , 2003.
29. Huang, Hui, and John Whalley. Baumol-Tobin and the Welfare Costs of National Security
Border Delays. Economic Letters, 2008.
30. Rajbhandari, R., J.C. Villa, and R.A. Sanchez. Expansion of the Border Crossing Information
System. Final Report. DOT Grant No. DTRT06-G-0044. University Transportation
Centers for Mobility. 2009.
31. FHWA. Travel Time Reliability Measures.
www.ops.fhwa.dot.gov/perf_measurement/reliability.../index.htm
32. Rajbhandari, R., J.C. Villa, and R.A. Sanchez. Expansion of the Border Crossing
Information System. Final Report. DOT Grant No. DTRT06-G-0044. University
Transportation Centers for Mobility. 2009.
33. Battelle and Texas Transportation Institute. “Measuring Border Delay and Crossing Times
at the U.S. – Mexico Border. http://tti.tamu.edu/documents/TTI-2008-5.pdf.
34. 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, 2010.
35. Accenture Group and HDR Engineering. Improving Economic Outcomes by Reducing
Border Delays. DRAFT. 2008. www.bta.org.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 76
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,
1999. TRB (www.trb.org).
37. Richardson, Helen: Transportation & Distribution, “Control Your Costs then Cut Them,”
December 1995.
38. Highway Economic Requirements Model. Technical Report. USDOT, Federal Highway
Administration. 1996.
39. Haning, C., and W. McFarland. Value of Time Saved to Commercial Motor Vehicles
Through Use of Improved Highways. Texas Transportation Institute Research Report,
1963.
40. McFarland, W. M. Chui. The Value of Travel Time. New Estimates Using a Speed Choice
Model. TTI Report. 1985.
41. 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., 1995.
42. Buffington , J and W. McFarland. Benefit-Cost Analysis: Updated Unit Costs and
Procedures, Research Report 202-2, College Station, Texas, Texas Transportation Institute,
August, 1975..
43. Kawamura, K. Perceived Value of Time for Truck Operators. Transportation Research
Record, Journal of the Transportation Research Board, No. 1725, 2000.
44. D. Lewis. Valuation of Travel-Time Savings and Predictability in Congested Conditions for
Highway User-Cost Estimation. National Cooperative Highway Research Program Report
431, 1997.
Center for International Intelligent Transportation Research Texas Transportation Institute Page 77
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)
Center for International Intelligent Transportation Research Texas Transportation Institute Page 78
Figure IX-1. BOTA Land Port of Entry: View from the Mexican Side
Center for International Intelligent Transportation Research Texas Transportation Institute Page 79
APPENDIX 2: COMMODITY PROFILES (PORTS OF ENTRY) (BY VALUE [2008])
Tables XI-1 to XI-10 shows the commodity profiles of several POE’s.
Table XI-1. Commodity Profile Brownsville Exports to Mexico
BROWNSVILLE Soya beans 10.3% Other parts and accessories 8.3% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils
8.0%
Natural gas, in the gaseous state 7.3% Hearing-aids (excluding parts and accessories) 5.5% Processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, clock and timing circuits, or other circuits
5.4%
Transmission apparatus 5.1% Articles of iron or steel 4.5% Optical media 3.3% Polyethylene having a specific gravity of 0.94 or more 3.2% Parts and accessories suitable for use solely or principally with the apparatus of division 76 - with the apparatus and equipment of groups 761 and 762 and subgroups 764.3 and 764.8
3.0%
Injection- or compression-types of moulds for rubber or plastics
3.0%
Cotton (other than linters), not carded or combed 3.0% Other apparatus 3.0% Other polyethers 2.9% Other articles 2.8% Rape or colza seeds, whether or not broken 2.6% Tantalum, unwrought (including bars and rods obtained simply by sintering); waste and scrap; powders
2.5%
Flat-rolled products of iron or non-alloy steel, not clad, plated or coated, not further worked than hot-rolled - of a width of 600 mm or more, in coils
2.4%
Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures
2.4%
Paraffin wax, microcrystalline petroleum wax, slack wax, ozokerite, lignite wax, peat wax, other mineral waxes, and similar products obtained by synthesis or by other processes, whether or not colored
2.4%
Polycarbonates 2.3% Parts and accessories for machines, appliances, instruments and apparatus.
2.3%
Whey and modified whey, whether or not concentrated or containing added sugar or other sweetening matter
2.3%
Plugs and sockets 2.2%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 80
Table XI-2. Commodity Profile Eagle Pass Exports to Mexico (Primarily Agriculture)
EAGLE PASS Soya beans 21.0% Other parts and accessories 7.7% Maize (not including sweet corn), unmilled other 7.3% Polyethylene having a specific gravity of 0.94 or more 6.0% Flours and meals of oil-seeds or oleaginous fruits (excluding mustard flour), non-defatted, partially defatted, or defatted and wholly or partially refatted with their original oils
5.4%
Brewing or distilling dregs and waste 4.6% Knitted or crocheted fabrics. 4.5% Propane, liquefied 4.1% Polypropylene 3.6% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc
3.3%
Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures
3.1%
Prepared explosives (other than propellant powders) 2.9% Polyethylene having a specific gravity of less than 0.94 2.5% Textile fabrics impregnated, coated, covered or laminated with plastics, other than those of heading 657.93.
2.3%
Bituminous 2.3% Motor vehicles for the transport of persons. 2.2% Other fructose and fructose syrup, containing in the dry state more than 50% by weight of fructose
2.2%
Oil-cake and other solid residues (except dregs), whether or not ground or in the form of pellets, resulting from the extraction of fats or oils from oil-seeds, oleaginous fruits and germs of cereals of soya beans
2.1%
Other wheat (including spelt) and meslin, unmilled 2.0% Crude oil, whether or not degummed 1.9% Polystyrene other 1.9% Milk, in solid form, of a fat content, by weight, not exceeding 1.5%
1.9%
Motor vehicles for the transport of goods. 1.8% Trousers, bib and brace overalls, breeches and shorts 1.8% Malt, whether or not roasted (including malt flour) 1.6%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 81
Table XI-3. Commodity Profile El Paso Exports to Mexico (Primarily Maquila Products)
EL PASO Parts and accessories (other than covers, carrying cases and the like) suitable for use solely or principally with the machines of subgroups 751.1, 751.2, 751.9 and group 752 -for the machines of group 752
20.9%
Other electric conductors, for a voltage not exceeding 1,000 V
6.1%
Motor vehicles for the transport of persons. 5.7% Other parts and accessories 5.4% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations., containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils
4.9%
Other articles 4.3% Parts suitable for use solely or principally with the apparatus falling within subgroups 772.4, 772.5 and 772.6 - Other parts
4.0%
Processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, clock and timing circuits, or other circuits
3.9%
Other instruments and appliances 3.9% Other electrical apparatus for switching or protecting electrical circuits, or for making connections to or in electrical circuits
3.9%
Articles of iron or steel. 3.7% Other wheat (including spelt) and meslin, unmilled 3.5% Parts and accessories 3.4% Electronic integrated circuits - Other 3.2% Copper wire - of refined copper 3.0% Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures
2.8%
Maize (not including sweet corn), unmilled other 2.6% Vacuum cleaners - parts 2.2% Textile fabrics impregnated, coated, covered or laminated with plastics, other than those of heading 657.93.
2.2%
Plugs and sockets 2.0% Aluminum alloys 1.9% Refined copper 1.8% Winding wire 1.7% Syringes, needles, catheters, cannulae and the like 1.6% Soya beans 1.6%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 82
Table XI-4. Commodity Profile Hidalgo Exports to Mexico
HIDALGO
Video games of a kind used with a television receiver 19.2%
Petroleum oils and oils obtained from bituminous minerals
(other than crude) and preparations., containing by weight
70% or more of petroleum oils or of oils obtained from
bituminous minerals, these oils being the basic constituents of
the preparations, other than waste oils
10.4%
Parts and accessories suitable for use solely or principally
with the apparatus of division 76 - with the apparatus and
equipment of groups 761 and 762 and subgroups 764.3 and
764.8
9.5%
Telephone sets, including telephones for cellular networks or
for other wireless networks
9.3%
Parts and accessories for machines, appliances, instruments 5.3%
Parts suitable for use solely or principally with the apparatus 5.0%
Parts, suitable for use solely or principally with the machines
falling within group 716
3.8%
Other articles 3.7%
Telephone sets, including telephones for cellular networks or
for other wireless networks; other apparatus
3.5%
Parts for the appliances of group 747 3.3%
Machines and mechanical appliances having individual
functions.
2.5%
Other parts and accessories of bodies (including cabs) 2.4%
Parts and accessories (other than covers, carrying cases and
the like) suitable for use solely or principally with the
machines of subgroups 751.1, 751.2, 751.9 and group 752 -for
the machines of group 752
2.3%
Parts and accessories suitable for use solely or principally
with the machine tools of groups 731 and 733 - for machines
of group 733
2.0%
Cartons, boxes and cases, of corrugated paper or paperboard 1.9%
Other regulating or controlling instruments and apparatus 1.9%
Parts for boring or sinking machinery of heading 723.37 or
723.44
1.8%
Articles of iron or steel. 1.8%
Guts, bladders and stomachs of animals (other than fish),
whole and pieces thereof
1.8%
Other electric conductors, for a voltage not exceeding 1,000 V 1.7%
Syringes, needles, catheters, cannulae and the like 1.5%
Reception apparatus for television, whether or not
incorporating radio-broadcast receivers or sound or video
recording or reproducing apparatus
1.5%
Articles for the conveyance or packing of goods; stoppers,
lids, caps and other closures
1.3%
Storage units 1.3%
Other electrical apparatus for switching or protecting
electrical circuits, or for making connections to or in electrical
circuits
1.2%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 83
Table XI-5. Commodity Profile Laredo Exports to Mexico
LAREDO Motor vehicles for the transport of persons. 14.8% Other parts and accessories 10.9% Other parts and accessories of bodies (including cabs) 7.9% Compression-ignition internal combustion piston engines (diesel or semi-diesel engines) of a kind used for the propulsion of vehicles of division 78
6.6%
Gearboxes and parts thereof 4.4% Maize (not including sweet corn), unmilled other 4.2% Parts and accessories 4.1% Copper wire - of refined copper 3.8% Polypropylene 3.6% Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations, containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils
3.4%
Other automatic data processing machines 3.2% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc
2.9%
Meat of bovine animals, fresh or chilled, boneless 2.8% Chemical wood pulp, soda or sulphate, other than dissolving grades, semi-bleached or bleached coniferous
2.7%
Milk, in solid form, of a fat content, by weight, not exceeding 1.5%
2.5%
Polyethylene having a specific gravity of 0.94 or more 2.5% Aluminum plates, sheets and strip, of a thickness exceeding 0.2 mm
2.4%
Motor vehicles for the transport of goods. 2.4% Parts, for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8 - suitable for use solely or principally with spark-ignition internal combustion piston engines.
2.4%
Other wheat (including spelt) and meslin, unmilled 2.2% Polyethylene having a specific gravity of less than 0.94 2.1% Articles for the conveyance or packing of goods.; stoppers, lids, caps and other closures
2.1%
Telephone sets, including telephones for cellular networks or for other wireless networks
2.1%
Tires, pneumatic, new, of a kind used on motor cars (including station wagons and racing cars).
2.1%
Other electric conductors, for a voltage not exceeding 1,000 V
2.0%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 84
Table XI-6. Commodity Profile Brownsville Imports to United States
BROWNSVILLE Ceramic dielectric fixed capacitors, multilayer 9.2% Other parts and accessories 7.8% Special transactions and commodities not classified according to kind
7.5%
Other parts and accessories of bodies (including cabs) 5.4% Ballasts for discharge lamps or tubes 5.4% Static converters (e.g., rectifiers) 5.3% Flat-rolled products of stainless steel, not further worked than cold-rolled (cold-reduced) - of a width of 600 mm or more and of a thickness of 0.5 mm or more but not exceeding 1 mm
5.1%
Parts of the seats 4.8% Parts for boring or sinking machinery of heading 4.7%
Tantalum fixed capacitors 4.6% Parts of the equipment of heading 4.2% Flat-rolled products of stainless steel, not further worked than cold-rolled (cold-reduced) - of a width of 600 mm or more and of a thickness exceeding 1 mm but less than 3 mm.
4.0%
Styrene-butadiene rubber (SBR); carboxylated styrene-butadiene rubber (XSBR)
3.9%
Other inorganic acids 3.4% Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus
2.7%
Fire extinguishers, whether or not charged 2.6% Motors (other than motors of an output not exceeding 37.5 W) and generators, direct current
2.5%
Brakes and servo-brakes and parts thereof 2.5% Other switches 2.3% Other parts for the machinery of group 2.3%
Thyristors, diacs and triacs (excluding photosensitive devices)
2.2%
Rock-drilling or earth-boring tools 2.1% Articles of iron or steel. 1.9% Binders (other than book covers), folders and file covers 1.9% Multiple-walled insulating units of glass 1.8%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 85
Table XI-7. Commodity Profile Eagle Pass Imports to United States
EAGLE PASS Motor vehicles for the transport of goods. 28.8% Other parts and accessories 11.7% Motor vehicles for the transport of persons. 10.5% Trousers, bib and brace overalls, breeches and shorts 7.2% Springs and leaves for springs, of iron or steel 5.2% Bars and rods of iron or non-alloy steel, not further worked than hot-rolled, hot-drawn or hot-extruded, but including those twisted after rolling - of iron or non-alloy steel, containing indentations, ribs, grooves or other deformations produced during the rolling process or twisted after rolling
4.6%
Beer made from malt (including ale, stout and porter) 4.6% Parts of the seats of subgroup 4.4% Polyethylene terephthalate 3.9% Drive-axles with differential, whether or not provided with other transmission components, and non-driving axles; parts thereof
2.1%
Parts for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8
1.8%
Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships
1.8%
Jerseys, pullovers, cardigans, waistcoats and similar articles, knitted or crocheted
1.7%
Unrefined copper (including blister copper but excluding cement copper); copper anodes for electrolytic refining
1.7%
AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)
1.3%
Trousers, bib and brace overalls, breeches and shorts 1.1% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc
1.1%
Line pipe of a kind used for oil or gas pipelines. 1.0% Flat-rolled products of iron or non-alloy steel, not clad, plated or coated, not further worked than hot-rolled - of a width of 600 mm or more, in coils
1.0%
Special transactions and commodities not classified according to kind
0.9%
Other hosiery 0.8% Other electric conductors, for a voltage not exceeding 1,000 V
0.8%
Other parts and accessories of bodies (including cabs) 0.8% Zinc, not alloyed 0.7% Parts for the air-conditioning machines of subgroup 741.5 0.7%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 86
Table XI-8. Commodity Profile El Paso Imports to United States
EL PASO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus
18.7%
Other automatic data processing machines 13.0% Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships
12.5%
Motor vehicles for the transport of persons. 6.0% Other parts and accessories 6.0% Parts of the seats of subgroup 821.1 5.7% Special transactions and commodities not classified according to kind
4.3%
Motor vehicles for the transport of goods. 4.1% Other instruments and appliances 2.8% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases, equipped with two or more apparatus of subgroup 772.4 or 772.5, for electrical control or the distribution of electricity (including those incorporating instruments or apparatus of groups 774, 881, 884 or of division 87, but excluding the switching apparatus of subgroup 764.1) - for a voltage not exceeding 1,000 V
2.8%
Refrigerators, household-type (electric or other), whether or not containing a deep-freeze compartment
2.5%
Other monitors 2.3% Other electric conductors, for a voltage not exceeding 1,000 V
2.2%
Parts and accessories 1.9% AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)
1.8%
Syringes, needles, catheters, cannulae and the like 1.8% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)
1.6%
Trousers, bib and brace overalls, breeches and shorts 1.5% Beer made from malt (including ale, stout and porter) 1.4% Reciprocating piston engines of a cylinder capacity exceeding 1,000 cc
1.4%
Taps, cocks, valves and similar appliances. 1.2% Parts for the internal combustion piston engines of subgroups 713.2, 713.3 and 713.8 - suitable for use solely or principally with spark-ignition internal combustion piston engines.
1.2%
Vacuum cleaners - with self-contained electric motor 1.1% Mowers for lawns, parks or sports grounds 1.1% Electrical lighting or signaling equipment (excluding articles of subgroup 778.2), windscreen wipers, defrosters and demisters, of a kind used for cycles or motor vehicles
1.1%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 87
Table XI-9. Commodity Profile Hidalgo Imports to United States
HIDALGO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus
11.3%
Special transactions and commodities not classified according to kind
8.4%
Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus
7.2%
Telephone sets, including telephones for cellular networks or for other wireless networks
7.0%
Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations
6.6%
Other parts and accessories of bodies (including cabs) 4.6% Other parts and accessories 4.4% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases
4.3%
Parts for the pumps, compressors, fans and hoods 4.1%
Avocados, guavas, mangoes and mangosteens, fresh or dried
4.0%
Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships
3.8%
AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)
3.7%
Orange juice 3.5% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)
3.0%
Other switches 2.9% Drills of all kinds 2.7% Vacuum cleaners - with self-contained electric motor 2.6% Lemons and limes fresh or dried 2.5% Other tools 2.1% Syringes, needles, catheters, cannulae and the like 1.9% Parts for the air-conditioning machines of subgroup 741.5 1.9% Portable automatic data processing machines, weighing not more than 10 kg, consisting of a least a central processing unit, a keyboard and a display
1.9%
Tomatoes, fresh or chilled 1.9% Radar apparatus, radio navigational aid apparatus and radio remote control apparatus
1.8%
Strawberries, raspberries, blackberries, mulberries, loganberries, cranberries, bilberries, and other fruits of the genus Vaccinium, fresh
1.7%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 88
Table XI-10. Commodity Profile Laredo Imports to United States
HIDALGO Reception apparatus for television, whether or not incorporating radio-broadcast receivers or sound or video recording or reproducing apparatus
11.3%
Special transactions and commodities not classified according to kind
8.4%
Radio-broadcast receivers not capable of operating without an external source of power, of a kind used in motor vehicles - combined with sound-recording or reproducing apparatus
7.2%
Telephone sets, including telephones for cellular networks or for other wireless networks
7.0%
Petroleum oils and oils obtained from bituminous minerals (other than crude) and preparations., containing by weight 70% or more of petroleum oils or of oils obtained from bituminous minerals, these oils being the basic constituents of the preparations, other than waste oils
6.6%
Other parts and accessories of bodies (including cabs) 4.6% Other parts and accessories 4.4% Boards, panels (including numerical control panels), consoles, desks, cabinets and other bases,
4.3%
Parts for the pumps, compressors, fans and hoods of subgroups 743.1 and 743.4
4.1%
Avocados, guavas, mangoes and mangosteens, fresh or dried
4.0%
Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships
3.8%
AC motors (including universal (AC/DC) motors, but excluding motors of an output not exceeding 37.5 W)
3.7%
Orange juice 3.5% Other apparatus for transmission or reception of voice, images or other data, including apparatus for communication in a wired or wireless network (such as a local or wide area network)
3.0%
Other switches 2.9% Drills of all kinds 2.7% Vacuum cleaners - with self-contained electric motor 2.6% Lemons and limes fresh or dried 2.5% Other tools 2.1% Syringes, needles, catheters, cannulae and the like 1.9% Parts for the air-conditioning machines of subgroup 741.5 1.9% Portable automatic data processing machines, weighing not more than 10 kg, consisting of a least a central processing unit, a keyboard and a display
1.9%
Tomatoes, fresh or chilled 1.9% Radar apparatus, radio navigational aid apparatus and radio remote control apparatus
1.8%
Strawberries, raspberries, blackberries, mulberries, loganberries, cranberries, bilberries, and other fruits of the genus Vaccinium, fresh
1.7%
Center for International Intelligent Transportation Research Texas Transportation Institute Page 89
APPENDIX 3: INTERVIEW INSTRUMENT
Interview Guide for Operations Contact Information
Name _________________________________________________________
Organization _________________________________________________________
Position _________________________________________________________
Address _________________________________________________________
_________________________________________________________
Telephone ______________________ Email address________________________
I. Cross-Border Operations.
1. Please describe your typical supply chain.
2. Do you currently have C-TPAT certification?
3. What are the primary products, volume, and origin/destination that your company moves by
truck across the border?
Product Inbound(I)
Outbound(O)
Origin
Location/Facility
Destination
Location/Facility
FAST
Non-
FAST
# of shipments
per month
(truckloads)
# Empty
Trips
4. Do you experience any seasonal fluctuations in your cross-border operations?
5. Do you hold any inventory? If yes, where (El Paso or Ciudad Juarez)?
Center for International Intelligent Transportation Research Texas Transportation Institute Page 90
6. What are the terms of sale for your products/cargo? Where does cargo change
ownership?
A) FOB B) Mid-bridge C) Other (list)
7. Do you have any plans for future developments? If so, could you provide more detail?
8. What are the main impediments to your cross-border operations (delays, costs, current
infrastructure, access roads, etc.)?
II. Trip Characteristics
9. Are carriers bound to schedules and bridge selections made?
10. What is the variation in travel time from origin to destination for your crossing? (Max
and min time)
11. Which bridge do you typically use for your cross-border operations?
12. What factors are important for deciding a) trip timing b) bridge selection, and who
makes these decisions?
13. What is the average travel time from origin to destination for your crossing?
Time of
Day Origin Destination
FAST /
Non-FAST
Range of Travel
Times (minutes)
Average Travel Time
(minutes)
14. Does travel time vary during the day?
15. How does this variability affect the supply chain and decisions?
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16. Do you adopt specific strategies to deal with crossing delays at your port of entry?
A) Change buffer time; B) Change delivery time; C) Change route; D) Change POE; E) Other
17. Do you pass on the delay cost to your ultimate customer?
III. Cost and Performance Parameters to Attract Sustaining Levels of
Traffic
18. Currently, how do you manage your company’s shipments?
□ Shipments are carried by the company (internal transportation)
□ Hire one carrier company
□ Hire two or more carrier companies
19. Approximately how much is the actual cost of every shipment/container per unit (MX-
Pesos)? □ 0 to 499
□ 500 to 999
□ 1,000 to 1,499
□ 1,500 to 1,999
□ 2,000 or more
20. Are there any other costs related to your shipments?
□ Yes
□ No
21. If Yes, what are those other costs and how much do you pay for each?
Additional Costs Description Estimated Cost $
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22. Please mark the cell(s) with the parameters that most influence your decision-making
process regarding your border crossing operations:
Parameter Cost Crossing
Time Reliability
Inspection
Simplification
Number
of Trips
per day
Distance
from the
POE
Type of
Commodity
Cost
Crossing Time
Reliability
Inspection
Simplification
Number of
Trips per Day
Distance from
the POE
Type of
Commodity
23. Would you use a New Border Crossing System if:
the New Border Crossing System and Increase Costs
Significantly improves border-crossing
times?
□ Yes
□ No
Increases the number of crossings per
day?
□ Yes
□ No
Has an excellent trip and schedule
reliability?
□ Yes
□ No
24. If Yes, how much are you willing to pay for said system?
Expected Increase
in Cost (Pesos) Yes/No
200 or less
200 to 400
400 to 600
600 to 800
800 to 1000
More
Center for International Intelligent Transportation Research Texas Transportation Institute Page 93
IV. Information System
25. What border-crossing information does your company use on a regular basis?
26. What information elements would you like to have in a border-crossing information
system?
27. In what format would you prefer for the information to be provided?