Intermodal Chassis Availability for Containerized Agricultural Exports

INTERMODAL CHASSIS AVAILABILITY FOR CONTAINERIZED AGRICULTURAL EXPORTS

A Case Study of the Ports of Los Angeles, Long Beach, and Oakland

Orfalea College of Business California Polytechnic State University 1 Grand Avenue San Luis Obispo, California 93407

Report Prepared for USDA-AMS USDA Cooperative Agreement No. 19-TMTSD-CA-0003 25 February 2021 ACKNOWLEDGMENTS

This research was supported by Cooperative Agreement Number 19-TMTSD-CA-0003 with the Agricultural Marketing Services (AMS) of the U.S. Department of Agriculture (USDA). The opin- ions and conclusions expressed here are those of the authors and do not necessarily represent those of USDA or AMS.

The authors gratefully acknowledge industry participants, including agricultural exporters, shippers, freight forwarders, chassis providers, motor carriers, and various Ports’ staff, for their input and data related to this research. Mr. Kevin Gard served as an outstanding graduate research assistant on this project. Any errors or omissions are the sole responsibility of the authors. Contents

List of Tables 5

List of Figures6

Executive Summary7

1 Introduction and Problem Statement9

2 Objectives and Scope of the Study 11

3 Methodology 14

4 U.S. and California Agricultural Exports 15 4.1 Containerized Agricultural Exports...... 23

5 Containerized Agricultural Exports Through California Ports 25 5.1 Port of Los Angeles...... 27 5.2 Port of Long Beach...... 36 5.3 Port of Oakland...... 45

6 The Rise of Mega Ships and Chassis Shortages 54 6.1 Mapping Container Volume to Chassis Demand and Supply...... 61 6.2 Chassis Supply at California Ports...... 70 6.2.1 San Pedro Bay Ports...... 71 6.2.2 Port of Oakland...... 73

7 Proposed Chassis Solutions for California Ports 74 7.1 Incentivize Chassis Ownership and Long-Term Leases...... 76 7.2 Develop a Dedicated Chassis Pool to Serve Agricultural Exporters...... 76

8 Conclusions and Directions for Future Research 81

9 Appendix A: Supporting Data Tables 82

10 Appendix B: U.S. Chassis Provisioning Models 97 10.1 Conventional Ocean Carrier Chassis Model...... 97 10.2 Regional Cooperative (Co-op) and Alliance Co-op Chassis Pool Model...... 98 10.3 Neutral/Gray Chassis Pool Model...... 98 10.4 Terminal Pool Chassis Model...... 99 10.5 Motor Carrier Supplied Chassis Model...... 99 10.6 Chassis Provider Independent Pool Model...... 100 10.7 Market Pool...... 100 10.8 Not-for-Proﬁt Chassis Pool Cooperative...... 101 10.9 The Role of Chassis Manufacturing and Sales in Chassis Supply...... 101

11 Additional References 103 List of Tables

4.1: Top 10 United States High Value Product Exports ($B)...... 18 4.2: Top 15 U.S. Agricultural Export Destinations (% of Total), by Calendar Year...... 19 4.3: California Agricultural Products Export Values ($M)...... 20 4.4: California’s Share of U.S. Agricultural Exports (%) by Commodity...... 21 4.5: Shares of California agricultural exports (%) by Destinations...... 22 LA.1: Port of Los Angeles Total Agricultural Exports (TEUs and % of Total)...... 32 LA.2: Port of Los Angeles Top 10 Containerized Agricultural Exports (TEUs)...... 33 LB.1: Port of Long Beach Total Agricultural Exports (TEUs and % of Total)...... 41 LB.2: Port of Long Beach Top 10 Containerized Agricultural Exports (TEUs)...... 42 O.1: Port of Oakland Total Agricultural Exports (TEUs and % of Total)...... 50 O.2: Port of Oakland Top 10 Containerized Agricultural Exports (TEUs)...... 51 7.1: Transportation Concerns of Agricultural Exporters...... 75 4.1A: U.S. Exports of Bulk and High-Valued Agricultural Products (HVP)...... 82 4.2A: Composition of High Value Product Exports (% of Total HPV)...... 83 LA-1A: Port of Los Angeles Aggregate Container Movement...... 84 LA-2A: Port of Los Angeles Empty Container Volume...... 85 LA-3A: Port of Los Angeles, Containerized Agricultural Exports (TEUs)...... 86 LB-1A: Port of Long Beach Aggregate Container Movement...... 87 LB-2A: Port of Long Beach Empty Container Volume...... 88 LB-3A: Port of Long Beach, Containerized Agricultural Exports (TEUs)...... 89 O-1A: Port of Oakland Aggregate Container Movement...... 90 O-2A: Port of Oakland Empty Container Volume...... 91 O-3A: Port of Oakland, Containerized Agricultural Exports (TEUs)...... 92 6.1A: Number of Container Vessels by Size in TEUs...... 93 6.2A: Capacity of Container Vessels (TEUs)...... 94 6.3A: Capacity of Container Ships Calling on U.S. Ports (TEUs)...... 95 6.4A: Average Monthly Container Freight Rates ($)...... 96 List of Figures

2.1: Dynamics of Container Volume at California Ports...... 12 4.1: U.S. Exports of Bulk and High-Valued Agricultural Products...... 16 4.2: Composition of High Value Product Exports (% of Total HPV)...... 17 LA.1: Port of Los Angeles Monthly Export Container Movement...... 28 LA.2: Port of Los Angeles Monthly Import Container Movement...... 29 LA.3: Port of Los Angeles Monthly Net Container Movement...... 30 LA.4: Port of Los Angeles Monthly Empty Container Movement...... 31 LA.5: Port of Los Angeles, Containerized Agricultural Exports...... 34 LA.6: Port of Los Angeles Containerized Edible Nuts Exports...... 35 LB.1: Port of Long Beach Monthly Export Container Movement...... 37 LB.2: Port of Long Beach Monthly Import Container Movement...... 38 LB.3: Port of Long Beach Monthly Net Container Movement...... 39 LB.4: Port of Long Beach Monthly Empty Container Movement...... 40 LB.5: Port of Long Beach, Containerized Agricultural Exports...... 43 LB.6: Port of Long Beach Containerized Edible Nuts Exports...... 44 O.1: Port of Oakland Monthly Export Container Movement...... 46 O.2: Port of Oakland Monthly Import Container Movement...... 47 O.3: Port of Oakland Monthly Net Container Movement...... 48 O.4: Port of Oakland Monthly Empty Container Movement...... 49 O.5: Port of Oakland, Containerized Agricultural Exports...... 52 O.6: Port of Oakland Containerized Edible Nuts Exports...... 53 6.1: Monthly Container Freight Rates (20-ft and 40-ft $)...... 56 6.2: Distribution of Monthly Container Freight Rates (20-ft $)...... 57 6.3: Distribution of Monthly Container Freight Rates (40-ft $)...... 58 6.4: Asymmetric Container Freight Rates (40-ft $)...... 59 6.5: Advantages and Disadvantages of Chassis Supply Models...... 63 6.6: Use of Chassis in Import and Export of Containerized Freight...... 64 6.7: Container Movement Patterns - Without On-Dock Rail Terminal...... 66 6.8: Container Movement Patterns - With On- or Off-Dock Rail Terminals...... 68 Executive Summary

Containerized shipping accounts for a significant percentage of United State’s international trade. The provisioning of the “appropriate” container and chassis is critical to the success of U.S. agricultural exports. The availability of containers and chassis is viewed by many market participants as one of the most significant sources of inefficiencies in the intermodal logistics system, and a major impediment to expanding U.S. agricultural exports. This study addresses the factors that impact the provisioning of “the right” containers and chassis at the “right time” for the movement of agricultural commodities through the Ports of Los Angeles, Long Beach, and Oakland. The volume of containers transiting through these ports has grown several fold since the 1990s. This trend mirrors growth in trade, particularly with Asia- Pacific countries. The container volume data attaching to these ports shows large variability in monthly volume movements. Excessive volume variability creates significant uncertainty, causing planning and execution problems for the various stakeholders in the import-export logistics chain. This is particularly true for truckers, shippers, and freight forwarders serving the agricultural export sector, as the “optimal period” for exporting food products usually coincides with the peak of import-export volume imbalance at these ports. A broad overview of U.S. trade over the past decades reveals that agricultural exports have grown by more than seven-fold. Over this period, agricultural exports have shifted away from “bulk” to “high value products” (HVPs). A large portion of HVPs, grown in California and the rest of the nation, are exported from these three ports. Economic development and increased prosperity in the Asia-Pacific region has resulted in significant increased demand for U.S. agricultural products. At the same time, U.S. containerized imports originating from the Asia-Pacific region have grown exponentially, creating a large supply of empty containers needing to return to their port of origin, mostly in Asia. It is this growth in demand, the shift to HVP exports, an over-supply of empty containers, as well as stable shipping costs that drive containerized agricultural exports through these ports. While this pattern has been periodically impacted by several commodity price spikes, and more recently trade friction and COVID-19, it is expected to continue into the foreseeable future. Understanding of the dynamics of aggregate container movement at these ports is critical for developing strategies that can help mitigate the problems arising from shortages of equipment, such as containers and chassis. Thus, the primary purpose of this study is to characterize the

Ramezani-Carr Intermodal Chassis Availability Page 7 dynamic pattern of container transit through these ports, its impact on chassis availability, and its implications for containerized agricultural exports (particularly HPVs). To this end, we study the historical container movements at these ports and delineate the seasonal patterns that lead to imbalances in demand and supply of containers and chassis. Based on our statistical analysis and insights from key stakeholders, we identify a number of impediments to the efﬁcient movement of containerized agricultural exports. Several important insights, including economic policy tools and incentives schemes, emerge from our analysis. Our study, the literature reviewed, and the feedback we have received from on-the-ground stakeholders make clear that there is no “one-size ﬁts all” solution for containers and chassis shortages appropriate for all U.S ports. Instead, we present three strategies to mitigate and potentially alleviate the perennial equipment shortages that disproportionately impact agricultural exporters at these ports (the report contains a detailed analysis of each):

• Shift the Timing of Agricultural Exports: Depending on the commodity, simply shift the timing of containerized agricultural export, even if the shift involves days or weeks (versus months). Time series data analysis can be used to identify cyclical patterns to implement this recommendation.

• Promote Chassis Leasing and Ownership: Create and offer ﬁnancial incentives for more agricultural shippers and/or their logistics providers to own or long-term lease equipment, particularly chassis, rather than rely on the short term day-rental market.

• Develop a Dedicated Chassis Pool: Develop and operate a buffer not-for-proﬁt chassis pool, dedicated to movement of agricultural exports. This study also provides a rough outline of what this buffer pool might look like and how it could operate. A number of stakeholders we spoke with responded favorably to this idea and approach.

Ramezani-Carr Intermodal Chassis Availability Page 8 1. Introduction and Problem Statement

Containerized shipping accounts for a significant percentage of high value agricultural trade. The transportation and logistics value chain linking containerized agricultural exporters to their global customers is vast and complex. The provisioning of the “appropriate” container and chassis – i.e., the right-sized container and chassis, available at the right location and time at a competitive price, and fully compliant with domestic and international regulatory requirements - is critical to the success of containerized agricultural export. While a number of factors cause friction in the delivery of containerized agricultural products to international markets, the availability of containers and chassis is viewed by many market participants in the United States as one of the most significant sources of inefficiencies in the system, and an impediment to further expanding exports. Containerized agricultural export requires specialized equipment that must meet strict regulatory standards. Containers are needed at specific locations and times; they must be available in terms of proximity and in sufficient quantities; and they must be of a suitable load unit. Other container issues include preparations, such as cleaning- sanitization, and specific liner and air circulation requirements. The proper provisioning of the appropriate chassis is equally critical, and chassis shortages or dislocation result in additional inefficiencies within the drayage system. This study addresses the factors that impact the provisioning of “the right” containers and chassis for the movement of agricultural commodities through the ports of Los Angeles, Long Beach, and Oakland. We consider the historical container movements at these ports and delineate the seasonal patterns that lead to excessive imbalances in demand and supply of container and chassis. Several important insights emerge from our analysis, suggesting a number of mechanisms that can mitigate and ultimately alleviate the burden of perennial chassis shortages that disproportionately impact agricultural exporters. We provide concrete examples that include shifting the timing of containerized agricultural exports, creation of financial incentives for chassis ownership and long- term lease arrangements, and the development of a targeted buffer chassis pool. On the practical side, we engaged various industry stakeholders to better understand the nu- ances of their decision making process as follows: • We interacted and interviewed economic agents within the targeted transportation value chain, identifying the determinants of container and chassis bottlenecks from their perspective.

Ramezani-Carr Intermodal Chassis Availability Page 9 • We surveyed various stakeholders, placing special emphasis on containerized agricultural exporters, as it appears the unique needs of this group of stakeholders have not received adequate attention to date.

• We acquired data from the Ports of Los Angeles, Long Beach, and Oakland, U.S. Department of Agriculture, and other sources.

• We surveyed previous reports produced by the ports and regulatory agencies.

• To gain insights from various stakeholders, we attended industry sponsored events, including meetings of the Agriculture Transportation Coalition (AgTC Tacoma, Sacramento and Fresno).

The analysis presented in this report is reﬂective of the insights provided by all participating stakeholders. The information shared by these stakeholders has enabled us to better document the challenges affecting containerized agricultural exports.

Ramezani-Carr Intermodal Chassis Availability Page 10 2. Objectives and Scope of the Study

Containerized international trade is affected by global economic growth, currency fluctuations, consumer preferences, trade pacts, treaties and tariffs, short- and long-term macroeconomic trends, and other factors. Since much of the containerized cargo consists of consumer goods and agricultural products, seasonal variations (for example, due to holiday shopping and timing of harvests in the North and South hemisphere) are a prominent feature of volume fluctuations at ports around the world. Fluctuation in container volume in turn drives the variability in equipment used to transport containers at ports, inland water ways, by rail and trucks. A critical piece of equipment for transporting containers is the chassis, and demand for chassis is directly tied to the volume of containers transiting through ports and rail terminals. Figure 2.1 below shows the monthly volume of containers transiting through the major Cali- fornia Ports of Los Angeles, Long Beach, and Oakland.1 The data in Figure 2.1 highlights several important points. First, there has been a growing trend in total container volume handled by these ports. This trend is reflective of growth in trade, particularly with the Asia-Pacific nations over the last thirty years. Second, and most importantly, there is large variability in monthly volume movements, particularly at the Ports of Los Angeles and Long Beach, because these ports experience large imbalances between the volume of imports and exports. A major consequence of high variability in container volume movement is that it creates significant difficulties for downstream logistic operators, particularly chassis providers and motor carriers, to determine the optimal quantity of costly equipment necessary to efficiently transport the volume of containers at these ports. Given this high degree of uncertainty, actual investment in equipment such as chassis is likely to be insufficient to handle the spikes in container volume. However, a better understanding of the dynamics of the aggregate container movement is needed for developing strategies that can mitigate the problems arising from shortages of critical equipment such as chassis. Thus, the primary purpose of this study is to characterize the dynamic pattern of container transit through these ports, its impact on chassis availability, and its implications for containerized agricultural exports.

1 The monthly volume is normalized by the volume on July 1997.

Ramezani-Carr Intermodal Chassis Availability Page 11 Figure 2.1: Dynamics of Container Volume at California Ports Total Monthly Volume (Imports plus Exports, Loaded and Empty Containers) Period: July 1997 to May 2020 Source: Ports of Los Angeles, Long Beach, and Oakland

Specifically, the objectives of this project are to identify the factors that impact the provisioning of containers and chassis that are appropriately suited for agricultural export at these ports. To this end, we first study the general pattern of containerized trade through these particular ports. We then focus on issues that effect agricultural exports, particularly high value and specialty products. Utilizing recent data and insights from key stakeholders, this study then identifies the main impediments to the efficient movement of containerized agricultural exports. We also formulate potential mitigating strategies, including economic policy tools and incentives to address the problem of securing this equipment.

Ramezani-Carr Intermodal Chassis Availability Page 12 The scope of this study addresses the following:

• Our focus is on the demand and supply of appropriate containers and chassis for the movement of high value crops and specialty products. While we consider all containerized agricultural exports from these ports, we also consider important specialty products, including edible nuts (almond, pistachios, and walnuts), processed tomatoes, rice, and wine.

• A number of regulatory bodies - international/domestic agencies and industry organizations - affect the transportation value chain linking containerized agricultural producers to their customers. We take the rules emanating from these agencies as a given. This study is not concerned with the efﬁcacy of speciﬁc agencies/rules.

• Various economic agents within this value chain posses a high degree of market power relative to others (pricing, timing, and physical requirements). Our study takes this “market structure” as a given. We offer incentive schemes and policy solutions under the current organizational market structure.

• The containerized transportation value chain is constantly evolving in response to changes in international trade patterns (trade frictions), local or global regulatory change (for example the transition to low sulfur fuel), shifts in market forces (increased international competition), technological change (for example GPS and RFID) and random shocks to consump- tion or production. Our study focuses on current industry challenges rather than their likely evolution in response to these shocks.

Ramezani-Carr Intermodal Chassis Availability Page 13 3. Methodology

This study will be highly data driven and practical in nature. First, we utilize the historical data to investigate the dynamic pattern of containerized trade, particularly the volume of imports and exports, as well as freight costs at each port. We then characterize the long-term dynamics and seasonal variations in the volume of agricultural exports. Based on this analysis, we show how the dynamics of container volume creates chassis shortages. Second, we conduct parallel analysis using data on containerized agricultural exports through these ports. We then consider the cyclical pattern of agricultural exports, within the broader dynamics of containerized trade. This analysis enables us to identify the spillover effect of overall container movements on chassis demand and its subsequent impact on the availability of chassis for agricultural exports. The remainder of this report is organized as follows. Section 4 provides an overview of agricultural exports, with particular focus on HVPs that are exported through the Ports of Los Angeles, Long Beach, and Oakland. Section 5 presents our analysis of containerized international trade, as well as U.S. agricultural exports, through these ports and identiﬁes historical trends and seasonal patterns for each port. In Section 6 we undertake a detailed examination of the forces that drive the demand and supply for containers and chassis. Our analysis focuses on the evolving market for containerized trade and its impact on chassis provisioning at these ports. In section 7 we propose speciﬁc solutions for mitigating chassis shortages for agricultural exporters. In Section 8 we provide a summary and suggest directions for future research.

Ramezani-Carr Intermodal Chassis Availability Page 14 4. U.S. and California Agricultural Exports

Agricultural commodities represent a signiﬁcant share of the overall U.S. exports, playing an important role in reducing our trade imbalance with the rest of the world. In this section, we present a broad overview of the dynamics of U.S. agricultural exports over recent decades and highlight the forces driving the containerization of such exports. We provide a summary of the key ﬁndings as follows:

• US agricultural exports have grown by more than seven-fold over the past four decades.

• Over that period, many agricultural exports have shifted away from “bulk” to “high value products” (HVPs).

• A large portion of HVP agricultural exports are grown in California and exported from nearby ports. Among these, edible nuts (almonds, walnuts, and pistachios) represent the largest commodity group.

• Economic development and increased prosperity in Asia-Paciﬁc region have resulted in a signiﬁcant increase in demand for American agricultural products.

• At the same time, U.S. containerized imports originating from the Asia-Paciﬁc region have grown exponentially, creating a large supply of empty containers needing to return to their ports of origin.

• Growth in demand, the increase in HVP exports, an over supply of empty containers, and stable shipping costs to the Asia-Paciﬁc region are the key forces driving containerized agricultural exports through Western U.S. ports, particularly Los Angeles, Long Beach, and Oakland.

• This pattern has been impacted by several commodity price spikes, and more recently trade friction, but is expected to continue into the foreseeable future.

U.S. agricultural exports have experienced a 4.38% cumulative annual growth since 1975, see Table 4.1A – henceforth Tables and Figures with numbers ending with letter “A” refer to items contained in Appendix A. The boom in overall agricultural exports has been accompanied with a diametrical shift away from bulk commodities, toward high value products. Figure 4.1

Ramezani-Carr Intermodal Chassis Availability Page 15 depicts this shift. While there are several episodes of reversals, it appears that these trends will likely continue into the foreseeable future.

Figure 4.1: U.S. Exports of Bulk and High-Valued Agricultural Products Period: 1975-2018 Source: USDA, Economic Research Service https://www.ers.usda.gov/webdocs/DataFiles/50441/ XfyHVPBULK.xls?v=1237.8

Focusing on the high value products (HVPs), Figure 4.2 shows that since the 1990s, the composition of exports has shifted to processed food exports and away from semi-processed and raw products (see Table 2A in Appendix A for supporting data). However, the proportion of processed food exports appears to have stabilized since 2000. Regardless of this shift in composition, HVPs constitute the main containerized agricultural exports.

Ramezani-Carr Intermodal Chassis Availability Page 16 Figure 4.2: Composition of High Value Product Exports (% of Total HPV) Period: 1990-2017 Source: USDA, Economic Research Service https://www.ers.usda.gov/webdocs/DataFiles/50441/ fyhvpsumexp.xls?v=4130.4

Turning to speciﬁc commodities, Table 4.1 below provides a list of the top ten HVP exports since 2012. As the table shows, as a group, the protein products that are exported in refrigerated containers (reefers) are consistently the top value items, followed by “Feed & Foder” category, and an assortment of commodities including almonds and nuts. It is important to note that the value of the HVP exports exceed 65%, and the top ten exports are over 30%, of the total U.S. agricultural exports. Furthermore, the majority of these products are exported in dry or reefer containers.

Ramezani-Carr Intermodal Chassis Availability Page 17 Table 4.1: Top 10 United States High Value Product Exports ($B) Period: 1990-2017 Source: Compiled by USDA-ERS using data from U.S. Department of Commerce, Census Bureau https://www.ers.usda.gov/data-products/foreign-agricultural- trade-of-the-united-states-fatus/fiscal-year/

Commodity group 2015 Commodity group 2016 Commodity group 2017 Other Feeds & Fodder 7.40 Other Feeds & Fodder 6.66 Other Feeds & Fodder 6.43 Misc Hort Products 5.55 Misc Hort Products 5.89 Beef & Veal Fr/Froz 6.18 Beef & Veal Fr/Froz 5.16 Beef & Veal Fr/Froz 5.24 Misc Hort Products 5.80 Almonds 5.14 Almonds 4.50 Pork, Fr/Froz 4.56 Soybean Meal 4.78 Pork, Fr/Froz 4.20 Almonds 4.48 Pork, Fr/Froz 4.03 Soybean Meal 4.07 Soybean Meal 3.89 Other Grain Prods 3.79 Other Grain Prods 3.65 Other Grain Prods 3.57 Chickens, Fr/Froz 2.79 Chickens, Fr/Froz 2.65 Chickens, Fr/Froz 2.91 Beverages Ex Juice 1.99 Beverages Ex Juice 1.93 Essential Oils 2.02 Essential Oils 1.79 Essential Oils 1.89 Beverages Ex Juice 1.95 2012 2013 2014 Other Feeds & Fodder 6.34 Other Feeds & Fodder 7.56 Other Feeds & Fodder 7.40 Misc Hort Products 4.94 Soybean Meal 5.41 Beef & Veal Fr/Froz 6.01 Soybean Meal 4.86 Misc Hort Products 5.38 Misc Hort Products 5.59 Pork, Fr/Froz 4.84 Beef & Veal Fr/Froz 5.22 Soybean Meal 5.48 Beef & Veal Fr/Froz 4.63 Pork, Fr/Froz 4.43 Pork, Fr/Froz 4.97 Chickens, Fr/Froz 3.97 Almonds 4.16 Almonds 4.53 Other Grain Prods 3.57 Chickens, Fr/Froz 4.01 Other Grain Prods 3.90 Almonds 3.39 Other Grain Prods 3.83 Chickens, Fr/Froz 3.82 Related Sugar Prod 1.88 Nonfat Dry Milk 2.15 Nonfat Dry Milk 2.26 Other Veg Oils/Waxes 1.82 Other Dairy Prods 1.91 Other Dairy Prods 1.94

Next, we consider the key destinations for the U.S. agricultural exports. Table 4.2 lists the top 15 countries that import food products from the U.S. As these data show, in 2017 over 70% of total agricultural exports were destined for countries along the Paciﬁc Rim and Far East Asia. Moreover, the ranking of the top destinations are relatively stable over time, with Canada, China, Mexico, Japan, and South Korea claiming the top spots every year since 2012.

Ramezani-Carr Intermodal Chassis Availability Page 18 Table 4.2: Top 15 U.S. Agricultural Export Destinations (% of Total), by Calendar Year Period: 2012-2017 Source: Compiled by USDA-ERS using data from U.S. Department of Commerce, Census Bureau https://www.ers.usda.gov/data-products/foreign-agricultural- trade-of-the-united-states-fatus/fiscal-year/

Country (Rank) 2015 Country (Rank) 2016 Country (Rank) 2017 Australia (14) 1 Canada (2) 15 Canada (1) 15 Canada (1) 16 China (1) 16 China (2) 14 China (2) 15 Colombia (12) 2 Colombia (12) 2 Colombia (9) 2 European Union-28 (4) 9 European Union-28 (5) 8 European Union-28 (4) 9 Hong Kong (7) 3 Hong Kong (7) 3 Hong Kong (7) 3 Indonesia (9) 2 India (15) 1 Indonesia (12) 2 Japan (5) 8 Indonesia (9) 2 Japan (5) 8 Mexico (3) 13 Japan (4) 9 Mexico (3) 13 Philippines (11) 2 Mexico (3) 13 Philippines (10) 2 Saudi Arabia (14) 1 Philippines (10) 2 South Korea (6) 5 South Korea (6) 5 South Korea (6) 5 Taiwan (8) 2 Taiwan (8) 2 Taiwan (8) 2 Thailand (13) 1 Thailand (13) 1 Thailand (13) 1 Turkey (15) 1 Turkey (15) 1 Turkey (14) 1 Vietnam (11) 2 Vietnam (10) 2 Vietnam (11) 2 Total Exports ($B) 139.70 129.60 141.80 2012 2013 2014 Canada (2) 15 Brazil (13) 1 Canada (2) 15 China (1) 18 Canada (2) 15 China (1) 16 Egypt (12) 1 China (1) 18 Colombia (11) 2 European Union-28 (5) 7 Egypt (14) 1 Egypt (14) 1 Hong Kong (7) 2 European Union-28 (5) 8 European Union-28 (5) 8 Indonesia (9) 2 Hong Kong (7) 3 Hong Kong (7) 3 Japan (4) 10 Indonesia (9) 2 Indonesia (9) 2 Mexico (3) 13 Japan (4) 8 Japan (4) 9 Philippines (10) 2 Mexico (3) 13 Mexico (3) 13 Russia (14) 1 Philippines (10) 2 Philippines (10) 2 South Korea (6) 4 South Korea (6) 4 South Korea (6) 5 Taiwan (8) 2 Taiwan (8) 2 Taiwan (8) 2 Turkey (11) 1 Turkey (11) 1 Thailand (15) 1 Venezuela (13) 1 Venezuela (15) 1 Turkey (13) 1 Vietnam (15) 1 Vietnam (12) 1 Vietnam (12) 2 Total Exports ($B) 135.90 141.10 152.30

Ramezani-Carr Intermodal Chassis Availability Page 19 Table 4.3: California Agricultural Products Export Values ($M) Source: University of California, Agricultural Issues Center https://aic.ucdavis.edu/california-agricultural- exports-year-2000-through-latest-available-2/

Product 2014 2015 2016 2017 2018 Almonds 4,528 5,143 4,497 4,483 4,530 Pistachios 1,124 848 1,145 1,518 1,736 Dairy and products 2,423 1,633 1,416 1,599 1,696 Wine 1,392 1,480 1,493 1,401 1,327 Walnuts 1,446 1,485 1,342 1,370 1,281 Table Grapes 890 766 799 795 801 Oranges and Products 573 587 678 679 650 Rice 681 751 714 637 629 Tomatoes, processed 784 814 743 649 599 Cotton 377 229 324 377 445 Total CA Agricultural Exports 21,554 20,806 19,983 20,746 21,017

Turning to agricultural exports that originate from the State of California, Table 4.3 presents the value of key commodities for the period 2014-2018. As these data show, California’s agricultural exports represent a signiﬁcant portion of value of the total U.S. agricultural exports. Considering the commodities in Table 4.3, the edible nuts group (almonds, walnuts, and pistachios), represent the lion’s share of California’s exports. Table 4.4 presents California’s share of the overall U.S. agricultural exports for selected commodities. As these data show, nearly all exports of the listed commodities are grown in California.

Ramezani-Carr Intermodal Chassis Availability Page 20 Table 4.4: California’s Share of U.S. Agricultural Exports (%) by Commodity Source: University of California, Agricultural Issues Center https://aic.ucdavis.edu/california-agricultural- exports-year-2000-through-latest-available-2/

Commodity 2014 2015 2016 2017 2018 Rice 35.4 37.3 37.1 36.6 36.7 Tomatoes, processed 94.6 96.8 94.4 93.0 93.1 Wine 92.7 91.8 91.3 91.5 91.7 Almonds 100 100 100 100 100 Walnuts 100 100 100 100 100 Pistachios 100 100 100 100 100

Finally, Table 4.5 presents the destination of key California’s agricultural exports. As these data show, most California grown agricultural exports are destined for Asia-Paciﬁc countries.

Ramezani-Carr Intermodal Chassis Availability Page 21 Table 4.5: Share of California Agricultural Exports (%) by Destinations Source: University of California, Agricultural Issues Center https://aic.ucdavis.edu/california-agricultural- exports-year-2000-through-latest-available-2/

Commodity (Rank) Destinations 2014 2015 2016 2017 Almonds (1) European Union 38.6 38.4 36.0 34.8 India 9.7 14 19 14.7 China/HK 8.9 13 11.5 11.2 Canada 5.8 5.9 6.0 5.7 Japan 5.8 6.2 5.2 5.1 United Arab Em 7.3 7.3 5.3 4.7 Other destinations 24.0 21.5 25.1 23.9 Pistachios (2) China/HK 32.3 29 46.3 43.7 European Union 39.8 55 33.2 34 Canada 6.7 8.0 5.1 5.2 Other destinations 21.2 25 15.3 27 Walnuts (5) European Union 31.7 29.9 31.3 35.9 Japan 7.4 7.9 7.3 9.6 Turkey 7.6 13 14.1 9.1 Korea 8.4 7.7 7.0 6.8 Canada 6.6 5.5 4.9 5.6 United Arab Em NA <5 4.5 4.9 China/HK 12.6 9.7 5.8 4.7 India NA NA <5 4.5 Other destinations 26.0 24.0 23.0 19.0 Wine (4) European Union 37.1 41.3 43.5 37.2 Canada 29.5 25.7 24.1 26.8 China/HK 11 9.9 18 13.2 Japan 6.0 6.8 5.4 6.1 Other destinations 17.4 16.4 16.2 16.6 Rice (8) Japan 35.0 37.0 32.7 29.8 Korea 4.8 17.6 14.9 13.4 Jordan 12 16 1 14.0 European Union NA <5 4.9 5.2 Canada 9.3 7.7 8.0 8.5 Saudi Arabia NA NA 5.4 5.1 Other destinations 41.0 27.0 24.2 24.1 Tomatoes, processed (9) Canada 34.2 52.9 39.8 41.9 Mexico 11 <5 12.3 12.4 Japan 4.6 22 5.3 7.2 European Union 17.6 13.5 19 7.8 Other destinations 33.5 13.0 31.7 37

Ramezani-Carr Intermodal Chassis Availability Page 22 4.1 Containerized Agricultural Exports

As the preceding analysis shows, U.S. agricultural exports have experienced secular growth over the past decades. Moreover, this growth has been accompanied by a major shift away from bulk commodities towards HVPs that are well suited to containerized shipping. Both dry and refrigerated container trade have beneﬁted from increasing global afﬂuence, and enhanced preferences for a variety of high quality and fresh foods, year-round. Accordingly, public and private investments in logistic infrastructure and the global transportation network, have contributed to and promoted intermodal transport and containerized trade. The following are additional factors that drive agricultural exporters to utilize containers to access international markets:

• Traceability: Containerized shipping can help buyers maintain a traceable link between the point of origin, the seeds used, and the designated overseas buyer. This process is very difﬁcult to trace in bulk moves. Crops that can be traced often command a higher price.

• Quality: Bulk shipments by rail or barge increase the risk of contamination or mixing of one crop with another. In fact, even containerized shipping can be contaminated and may require the cleaning and inspection of each container used.

• Buyer Intake Issues: Grain bulk terminals in China and other countries are less efﬁcient than container terminals, where there has been more modernization to support their export growth. Containerized cargo, on the other hand, can also be certiﬁed and better moved intact to “interior markets,” especially when storage facilities at receiving ports are unavailable.

Increased reliance on containers, and in turn trucks and chassis, leads to important challenges:

• Agricultural commodities handled at inland terminals and dryports must conform to federal, state and local truck size and weight rules so they can move on public highways without damaging transportation infrastructure.

• Agricultural commodities for export are often located in rural areas that are not destinations for containerized imports, resulting in a “matchback” problem. This is where market demand creates “headhauls” of the import to the consumer (with the container and chassis moving with the load) and “backhauls” of that equipment are then needed to help return the

Ramezani-Carr Intermodal Chassis Availability Page 23 equipment back to its originating marine port, dryport or inland terminal. Ocean carriers seek to shift the costs associated with re-positioning these equipments to other supply chain stakeholders.

• The seasonal nature of agricultural production concentrates high demand during particular harvest periods, and must be balanced against variable import demand for consumer goods. Crop yields also rise and fall depending upon weather related events that impact agricultural supply.

• Timing issues regarding vessel schedules, container free time allowances, and rail cut-offs to the West Coast put a premium on the ability to share information electronically on the location and status of equipment.

To summarize, containerized agricultural exports require specialized containers meeting strict regulatory standards. Such containers are needed at specific locations and specific times; they must be available in proximity, in sufficient quantities and be of a suitable size. Other issues involve container preparation, such as the requirement that a container is thoroughly cleaned before loading, that it has a specific liner, that it provides a required level of air circulation, and it is cleaned once unloaded, so it can be used for other purposes without contaminating the next shipment. This study provides a careful examination of how these factors impact the provision of appropriate containers and chassis for agricultural exports.

Ramezani-Carr Intermodal Chassis Availability Page 24 5. Containerized Agricultural Exports Through California Ports

A large portion of worldwide container shipments are bound to or from the United States. Con- sequently, domestic demand for intermodal chassis is principally a function of the volume of containerized trade. During peak months of September through December, the ports under consideration handled over a million TEUs. Indeed, as our analysis will show, container traffic to and from California ports has grown at a rapid rate in recent years, resulting in a significant rise in vessel, truck, and rail movement in and around these ports and the surrounding regions. Accordingly, the domestic railroads and trucking lines have expanded their intermodal services at these ports. In this section we examine the dynamics of containerized imports and exports at three key ports in California. The Port of Los Angeles and neighboring Port of Long Beach comprise the San Pedro Bay Port complex. Together, the San Pedro Bay Ports handle more containers than any other port in the United States. In Northern California, the equally important Port of Oakland serves as a major ocean gateway for containerized cargo movements. Together, these ports serve a critical role in facilitating containerized U.S. agricultural exports. As we show in this section, these ports mostly handle imports destined for regional and national markets. As the world economy recovered from the “Great Recession” of 2007-09, these ports experienced a large influx of containers. Increased container volumes at these ports has resulted in rising demand for chassis at the port terminals and inland intermodal facilities. Moreover, because of the large and growing trade imbalance with Asia-Pacific regions, there is increased movement of empty export containers at these ports, which further impacts demand for chassis. Finally, the trend toward mega-vessels is placing additional pressures on available supply of chassis, while forcing port operators, Intermodal Equipment Providers (IEPs), and other stakeholders to efficiently handle the increasing cargo volumes. Next we focus on understanding the seasonal pattern for both dry and refrigerated container movements through these ports. Rather than describe the physical developments, organizational structure, and operations of these ports, our aim is to understand the statistical properties of monthly inbound (import) and outbound (export) container movement in these ports. We then undertake a similar analysis for containerized agricultural exports. Seasonal patterns generally arise from heightened demand during the holiday season, as well as production cycles and the timing of agricultural harvest. Moreover, refrigerated trade tends to run in north-south directions due to seasonal reversals that enable countries in the southern hemisphere

Ramezani-Carr Intermodal Chassis Availability Page 25 to supply a variety of fresh produce to countries in the northern hemisphere during their winter months. As a consequence, both types of seasonality are expected to result in increased demand for containers and chassis during the ﬁrst and the fourth quarters of the year. The analysis presented provides insights about the peak and trough periods for imports (loaded and empty inbound), and exports (loaded and empty outbound) of dry and refrigerated containers movements at these ports. That information, in turn, provides insights regarding the peak and trough in chassis demand, and potential opportunities to avoid tight market periods that are accompanied by chassis and container shortages, and high shipping costs.2 To ease the presentation of a large amount of data, we use “candlestick graphs” to show the range of monthly variations in container movements through the ports under consideration.3 On each graph, the candlestick shows the minimum, the 1st quartile, the mean (line graph), the median (solid horizontal line inside the boxed area), the 3rd quartile, and the maximum. Solid dots represent large outliers. The boxed area shows the interquartile range, also called the midspread, which is the middle 50%. The interquartile range is a useful measure, as it show where the bulk of data values lie. The data underlying the plots presented with candlestick graphs and their distribution (mean, variance and the range for all variables) are tabulated and presented in Appendix A.

2 For example, by shifting the timing of agricultural exports. 3 These graphs are also called “Box and Whisker” plots.

Ramezani-Carr Intermodal Chassis Availability Page 26 5.1 Port of Los Angeles

The Port of Los Angeles was established in 1907. For the past 20 years, the Port of Los Angeles, which is a landlord port, has been the busiest container port in the United States. The Port of Los Angeles consists of 4,200 acres of land, 43 miles of waterfront, 25 cargo terminals, 82 container cranes, and seven container terminals, all expediting goods to 14 major U.S. freight hubs.4

Port of Los Angeles

Source: iStock Photo

In 2019 the Port of LA handled 9.3 million TEUs (twenty-foot equivalents). The top ﬁve containerized exports in 2019 were paper/waste-paper (240,623 TEUs), pet/animal feed (181,639 TEUs), fabrics/raw cotton (103,871 TEUs), scrap metal (100,787 TEUs) and soybeans (96,148 TEUs). Its top trading partners in 2019 were China/Hong Kong ($128 billion), Japan ($38 billion), Vietnam ($21 billion), Taiwan ($15 billion) and South Korea ($15 billion). Its top ﬁve trade routes

4 It is reasonable to treat the Ports of Los Angeles and Long Beach as one consolidated port, given their close proximity, and the similarity of their operations and clientele. In fact, like other ports, cargo may shift from one terminal to the other based on alliance conﬁgurations, infrastructure development (e.g., the completion of the Long Beach Container Terminal) or changes in facility ownership, all of which are independent of trade ﬂows. We separately treat each port given our focus on agricultural exports.

Ramezani-Carr Intermodal Chassis Availability Page 27 were Northeast Asia (74%), Southeast Asia (19%), India Sub-continent (2%), Northern Europe (2%) and Mexico/Central America (1%).5

Figure LA.1: Port of Los Angeles Monthly Export Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.portoflosangeles.org/business/statistics/ container-statistics

Figure LA.1 presents the distributional characteristics of monthly containerized exports – all goods, dry and refrigerated, outbound, full and empty containers – through the Port of Los Angeles during the period 1995 to 2020.6 The ﬁgure shows monthly seasonality in exports, with the trough generally occurring during the month of February and the peak occurring during the month of August. As the ﬁgure also shows, the largest variation occurs during the months of October and November. It is during these months that large spikes in container exports take place (widest range,

5 For details on the Port of Los Angeles and its operations see https://www.portoflosangeles.org/ and https://explore.dot.gov/views/PortPerformance-temp-view2/ProfileDashboard? Port%20ID=4120&:isGuestRedirectFromVizportal=y&:embed=y. 6 The data used to generate these ﬁgures is summarized in Table LA-2A in Appendix A.

Ramezani-Carr Intermodal Chassis Availability Page 28 deﬁned as the gap between the minimum and the maximum), where nearly 450,000 containers are shipped to their destinations. Figure LA.2 presents similar data but for containerized imports (total container volume) through the Port of Los Angeles for the same period. The ﬁgure shows monthly seasonality in imports, with the trough again occurring during the month of February. The peaks again occur during the month of August. The largest variation occurs during the October through December period. It is during these pre-holiday season months that largest spikes in imported containers take place.

Figure LA.2: Port of Los Angeles Monthly Import Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.portoflosangeles.org/business/ statistics/container-statistics

Figure LA.3 presents the distributional characteristics of net monthly containerized movement (imports minus exports, full and empty) through the Port of Los Angeles for the same period. This ﬁgure shows that monthly net imports are mostly positive, i.e., most months there are far more inbound than outbound container movements. This imbalance is most pronounced during the April through September months.

Ramezani-Carr Intermodal Chassis Availability Page 29 Figure LA.3: Port of Los Angeles Monthly Net Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.portoflosangeles.org/business/ statistics/container-statistics

Similarly, Table LA-2A in Appendix A presents data on the volume of empty container movement. The table provides information about the fraction of outbound and inbound containers that are empties. The data indicates that over 50% of containers exported and less than 4% of containers imported are empties. It is important to note that the highest proportion of empty exports occur during the months of August through November, coinciding with the seasonal peak of containerized agricultural exports. Figure LA.4 shows the monthly average of empty containers relative to total exports and imports. Again, it is important to note that the peak period for exported empties coincide with the peak season for agricultural exports. However, the rush to return empties to serve the import market means there are fewer containers available for agricultural exporters during the peak of their season.

Ramezani-Carr Intermodal Chassis Availability Page 30 Figure LA.4: Port of Los Angeles Average Monthly Empty Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.portoflosangeles.org/business/ statistics/container-statistics

Table LA.1 provides annual historical date on total containerized agricultural exports through the Port of Los Angeles. The table also shows the volume (in TEUs) of all exports through this port. These data show that roughly 30% of outbound containers carry agricultural exports, which is a testament to the role agriculture plays in U.S. exports. Note also that while the volume of agricultural exports declined prior to 2015, there has been a clear upward swing in recent years.

Ramezani-Carr Intermodal Chassis Availability Page 31 Table LA.1: Port of Los Angeles Total Agricultural Exports (TEUs and % of Total) Source: Port of Los Angeles and USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Year Agricultural Exports (TEU) Loaded Exports (TEU) Agriculture (%) 2010 548364 1841274 29.78 2011 628022 2109394 29.77 2012 595558 2043076 29.15 2013 579591 1921069 30.17 2014 523845 1932014 27.11 2015 468465 1656677 28.28 2016 526967 1818502 28.98 2017 557897 1899934 29.36 2018 587593 1904054 30.86

Table LA.2 provides information about the composition of agricultural exports through the Port of Los Angeles for the most recent year (2018).7 The table lists the top 10 commodities for each month. As can be seen, there is little variation in the rankings of the top 10 commodities by month. Considering the top three export items, we see strong seasonality, with peak exports occurring during the August through November months, which also coincides with the peak period for exported empty containers. Note that with the exception of small quantity of edible nuts, no wine, processed tomatoes, or rice were exported through the Port of Los Angeles in 2018. We observe very similar patterns for the prior years (2010-17), suggesting that the agricultural exporters relying on this port have established relationships and long term contractual agreements with counter parties in destination countries and with stakeholders within the export logistics chain.

7 Similar tables for years 2010-2017 are available from the authors.

Ramezani-Carr Intermodal Chassis Availability Page 32 Table LA.2: Port of Los Angeles Top 10 Containerized Agricultural Exports (TEUs) Period: Jan 2018 - Dec 2018 Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Rank January TEUs February TEUs March TEUs 1 Animal Feed 11944 Animal Feed 13344 Animal Feed 14617 2 Soybeans 6290 Soybeans 8464 Soybeans 10255 3 Raw Cotton 6048 Raw Cotton 7498 Raw Cotton 9158 4 Meat 3174 Meat 3364 Meat 4393 5 Grocery Items 3163 Grocery Items 2755 Grocery Items 3097 6 Bulb & Seeds 1376 Grain Products 1498 Grain Products 1944 7 Hides And Skins 1203 Oranges 1268 Oranges 1493 8 Grain Products 1122 Bulk Grains 1100 Bulk Grains 1115 9 Bulk Grains 879 Hides And Skins 1045 Bulb & Seeds 1010 10 Oranges 851 Bulb & Seeds 989 Dairy Products 1010 Total 36050 41325 48092 April May June 1 Animal Feed 12331 Animal Feed 17132 Animal Feed 14134 2 Raw Cotton 7529 Soybeans 9493 Soybeans 8061 3 Soybeans 7053 Raw Cotton 8604 Raw Cotton 6139 4 Grocery Items 3631 Grocery Items 5071 Grocery Items 3781 5 Meat 2416 Meat 3433 Bulb & Seeds 3517 6 Grain Products 2248 Bulb & Seeds 3416 Meat 2932 7 Bulb & Seeds 1977 Grain Products 2456 Grain Products 1415 8 Bulk Grains 1330 Dairy Products 1336 Dairy Products 1381 9 Oranges 1152 Hides And Skins 1195 Vegetables 882 10 Dairy Products 882 Vegetables 927 Hides And Skins 666 Total 40549 53063 42908 July August September 1 Animal Feed 15776 Animal Feed 17158 Animal Feed 19174 2 Soybeans 9345 Soybeans 8828 Soybeans 10142 3 Grocery Items 4598 Meat 3791 Grocery Items 4047 4 Raw Cotton 4581 Grocery Items 3701 Meat 3517 5 Meat 3673 Raw Cotton 3002 Raw Cotton 2825 6 Bulb & Seeds 3578 Bulb & Seeds 2019 Bulb & Seeds 2234 7 Grain Products 1638 Grain Products 1967 Grain Products 1743 8 Dairy Products 1076 Fruit 1194 Fruit 1421 9 Coffee 999 Dairy Products 1058 Coffee 1345 10 Hides And Skins 943 Coffee 928 Dairy Products 1220 Total 46207 43646 47668 October November December 1 Animal Feed 20065 Animal Feed 17053 Animal Feed 13740 2 Soybeans 8599 Soybeans 6053 Soybeans 5762 3 Meat 4247 Meat 3807 Meat 3527 4 Grocery Items 3464 Grocery Items 3391 Grocery Items 3147 5 Fruit 2204 Raw Cotton 2641 Raw Cotton 3005 6 Raw Cotton 2007 Bulb & Seeds 1997 Bulb & Seeds 1477 7 Grain Products 1855 Fruit 1966 Hides And Skins 1051 8 Bulb & Seeds 1634 Edible Nuts 1629 Dairy Products 959 9 Edible Nuts 1363 Hides And Skins 1413 Edible Nuts 935 10 Hides And Skins 1033 Vegetables 790 Fruit 579 Total 46471 40740 34182

Ramezani-Carr Intermodal Chassis Availability Page 33 Next, we consider the four commodities that are of particular interest in this study: edible nuts, rice, processed tomatoes, and wine. Figure LA.5 shows the monthly average (TEUs) exported for these commodities through this port. Considering edible nuts, the data suggest peaks in March and the October-November months. For processed tomatoes, the peak occurs March through May. The export of rice and wine show little seasonal variation. For these commodities, the volume of export through this port is generally very low. As Table LA.2 indicates, small volumes of edible nuts, rice, processed tomatoes, and wine are exported through this port.8

Figure LA.5: Port of Los Angeles, Containerized Agricultural Exports (TEUs, Monthly Average) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Focusing on edible nuts, Figure LA.6 provides candlestick plots of the monthly exports through

8 Clearly, some of the top ten commodities are arriving by rail at these California ports. However, we were unable to separate the volume of containers shipped on rail.

Ramezani-Carr Intermodal Chassis Availability Page 34 the Port of Los Angeles for the 2010-2018 period. Note the large spikes during the months of October and November. These patterns are indicative of the seasonal harvest cycle, as well as variations in shipping costs and availability of chassis and available space on vessels for speciﬁc export destinations.

Figure LA.6: Port of Los Angeles Containerized Edible Nuts Exports (TEUs, Monthly Variation) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Ramezani-Carr Intermodal Chassis Availability Page 35 5.2 Port of Long Beach

The Port of Long Beach opened in 1911. Also a landlord port, it is the second-busiest container seaport in the U.S., behind the Port of Los Angeles. It consists of 3,520 acres of land, 31 miles of waterfront, six container terminals, and 2,000 yearly vessel calls. It does more than $170 billion in cargo and 7.6 million TEUs each year. Top containerized exports for the Port of Long Beach tend to be waste paper, agriculture products, and plastics.9

Port of Long Beach

Image Source: Port of Long Beach

Figure LB.1 presents the distributional characteristics of monthly containerized exports (all goods, outbound, full and empty containers) through the Port of Long Beach during the period

9 For details on the Port of Long Beach and its operations see https://www.polb.com/ and https://explore.dot.gov/views/PortPerformance-temp-view2/ProfileDashboard? Port%20ID=4110&:isGuestRedirectFromVizportal=y&:embed=y.

Ramezani-Carr Intermodal Chassis Availability Page 36 1995 to 2020. The ﬁgure shows monthly seasonality in exports, with the trough generally occurring during the month of February and the peak occurring during the month of August. In contrast to the Port of Los Angeles, the largest variations occur during the months June and December. It is during these months that large spikes take place (widest range, deﬁned as the gap between the minimum and the maximum), where occasionally 350,000 containers maybe exported.

Figure LB.1: Port of Long Beach Monthly Export Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.polb.com

Figure LB.2 presents similar data but for containerized imports (all goods, inbound, full and empty containers) through the Port of Long Beach for the same period. The ﬁgure shows monthly seasonality in imports, with the trough occurring during the month of March. The peak occurs during the month of August. The largest variations occur during May-July and December periods. In general, the 4th quarter of the year is dominated by high volume pre-holiday imports, resulting in the largest container volume spikes.

Ramezani-Carr Intermodal Chassis Availability Page 37 Figure LB.2: Port of Long Beach Monthly Import Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.polb.com

Figure LB.3 presents the distributional characteristics of net monthly containerized movement (imports minus exports, full and empty) through the Port of Long Beach for the same period. This ﬁgure shows that monthly net imports are mostly positive, i.e., most months there are more inbound than outbound container movements, though the magnitude is smaller than the Port of LA. However, there is also signiﬁcant negative net container movement during the month of March (more containers are exported than imported). The imbalance at the Port of Long Beach though smaller, is still relatively large and most pronounced during the later months of the year.10

10 Table LB-1A in Appendix A presents the data underlying these candlestick plots. The table provides information about the distribution of exports, imports, and net imports by month for the period 1995-2020. Again, the data show signiﬁcant and persistent imbalance between imports and exports at the Port of Long Beach.

Ramezani-Carr Intermodal Chassis Availability Page 38 Figure LB.3: Port of Long Beach Monthly Net Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.polb.com/business/port- statistics/#latest-statistics

For the Port of Long Beach, the data indicate that for most months, over 50% of the containers exported and less than 3% of containers imported are empties. It is important to note that the highest proportion of empty exports occurs during the months of August through September. However, there is less overlap with the seasonal peak of containerized agricultural exports.11 Figure LB.4 shows the monthly average of empty containers relative to total exports and imports (Table LB-2A in Appendix A). It is important to note that the peak period for exported empties coincide with the peak season for agricultural exports. Again, the rush to return empties to serve the import market means there are fewer containers available for agricultural exporters during the peak of their season. 11 Table LB-2A in Appendix A presents data on the volume of empty container movement at the Port of Long Beach. The table provides information about the fraction of outbound and inbound containers that are empties. We note that the Port of Long Beach does not report the volume of empties for imports or exports. We extrapolate the number of empties for the Port of Long Beach by assuming that the fraction of empty volume (import and export) is the same as at the Port of Los Angeles for each month.

Ramezani-Carr Intermodal Chassis Availability Page 39 Figure LB.4: Port of Long Beach Monthly Empty Container Movement Period: July 1995 to May 2020 (25 observations per month) Source: https://www.polb.com

Table LB.1 provides annual historical data on total containerized agricultural exports through the Port of Long Beach. The table also show the volume (in TEUs) of all exports through this port. These data show that roughly 25% of outbound containers carry agricultural exports, which though signiﬁcant, is 5% smaller than the Port of LA. Note also that the volume of agricultural exports through this port has continued to decline since 2010. This may represent an opportunity to shift agricultural exports toward this port, possibly by providing economic incentives to ship through this port.

Ramezani-Carr Intermodal Chassis Availability Page 40 Table LB.1: Port of Long Beach Total Agricultural Exports (TEUs and % of Total) Source: Port of Long Beach and USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Year Agricultural Exports (TEU) Loaded Exports (TEU) Agriculture (%) 2010 453476 1562398 29.02 2011 355799 1506692 23.61 2012 369700 1540188 24.00 2013 454446 1704930 26.65 2014 428319 1604395 26.70 2015 405821 1525556 26.60 2016 399146 1529499 26.10 2017 373622 1470517 25.41 2018 396357 1547131 25.62

Table LB.2 provides information about the composition of agricultural exports through the Port of Long Beach in 2018. The table lists the top 10 commodities for each month. It shows that there is little variation in the rankings of the top 10 commodities by month. In fact, the top items on this table are nearly identical to those in Table LA.2. The top 5 commodities in this table are the same as items exported from the Port of Los Angeles. Considering the top three export items, we observe a different seasonal pattern, with peak exports occurring during the earlier months of the year. Note that as with the Port of Los Angeles, edible nuts are frequently exported from this port. However, no wine, processed tomatoes, or rice were exported in 2018. We observe very similar patterns for the prior years (2010-17), again suggesting that the agricultural exporters relying on this port have established relationships and long term contractual agreements with counter parties in destination countries and with stakeholders within the export logistics chain.

Ramezani-Carr Intermodal Chassis Availability Page 41 Table LB.2: Port of Long Beach Top 10 Containerized Agricultural Exports (TEUs) Period: Jan 2018 - Dec 2018 Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Rank January TEUs February TEUs March TEUs 1 Animal Feed 8809 Animal Feed 11834 Animal Feed 12971 2 Raw Cotton 4220 Raw Cotton 3474 Soybeans 4712 3 Soybeans 2785 Soybeans 2871 Raw Cotton 3859 4 Grocery Items 2657 Meat 2755 Grocery Items 2896 5 Meat 2126 Grocery Items 2391 Meat 2821 6 Bulb & Seeds 1302 Oranges 1655 Bulb & Seeds 2337 7 Grain Products 1174 Hides And Skins 1372 Bulk Grains 2085 8 Edible Nuts 1026 Fruit 1324 Grain Products 2023 9 Hides And Skins 866 Bulk Grains 1290 Edible Nuts 1564 10 Dairy Products 699 Bulb & Seeds 1106 Fruit 1342 Total 25664 30072 36610 April May June 1 Animal Feed 8785 Animal Feed 11200 Animal Feed 11516 2 Soybeans 3719 Soybeans 4838 Soybeans 4432 3 Grocery Items 3536 Bulb & Seeds 3898 Grocery Items 4002 4 Raw Cotton 2833 Grocery Items 3501 Bulb & Seeds 3260 5 Bulb & Seeds 2613 Meat 3031 Meat 2479 6 Meat 2429 Raw Cotton 2904 Raw Cotton 2259 7 Grain Products 2026 Grain Products 2204 Grain Products 1432 8 Beer & Ale 1193 Beer & Ale 1755 Beer & Ale 1155 9 Bulk Grains 1178 Edible Nuts 1317 Hides And Skins 1043 10 Edible Nuts 1162 Hides And Skins 1070 Edible Nuts 797 Total 29474 35718 32375 July August September 1 Animal Feed 8292 Animal Feed 8085 Animal Feed 9706 2 Soybeans 4250 Soybeans 4005 Grocery Items 3462 3 Grocery Items 2533 Grocery Items 3382 Soybeans 3186 4 Bulb & Seeds 2247 Meat 1960 Meat 2066 5 Meat 1775 Bulb & Seeds 1920 Bulb & Seeds 1978 6 Grain Products 1498 Raw Cotton 1388 Fruit 1107 7 Raw Cotton 1366 Hides And Skins 1301 Hides And Skins 1092 8 Beer & Ale 1272 Beer & Ale 1096 Raw Cotton 998 9 Edible Nuts 869 Edible Nuts 998 Edible Nuts 967 10 Hides And Skins 756 Grain Products 913 Grain Products 693 Total 24858 25048 25255 October November December 1 Animal Feed 10070 Animal Feed 8244 Animal Feed 5811 2 Soybeans 3878 Soybeans 6212 Soybeans 2684 3 Grocery Items 3303 Grocery Items 2870 Grocery Items 2254 4 Meat 2471 Meat 2498 Meat 1957 5 Bulb & Seeds 1743 Bulb & Seeds 2161 Raw Cotton 1273 6 Fruit 1282 Edible Nuts 1507 Bulb & Seeds 1068 7 Edible Nuts 993 Fruit 1389 Grain Products 1068 8 Raw Cotton 955 Grain Products 1312 Edible Nuts 960 9 Hides And Skins 892 Raw Cotton 1008 Beer & Ale 550 10 Bulk Grains 738 Hides And Skins 727 Oranges 474 Total 26325 27928 18099

Ramezani-Carr Intermodal Chassis Availability Page 42 Next, we consider the four commodities that are of particular interest in this study: edible nuts, rice, processed tomatoes, and wine. Figure LB.5 shows the monthly average (TEUs) exported for these commodities through this port. Considering edible nuts, the data suggest a similar pattern as the Port of LA: peaks in March and the October-November months. For processed tomatoes and rice, the peak occurs in March. The export of wine shows little seasonal variation. For these commodities, the volume of export through this port is generally very low.12

Figure LB.5: Port of Long Beach, Containerized Agricultural Exports (TEUs, Monthly Average) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Focusing on edible nuts, Figure LB.6 provides candlestick plots of the monthly exports through the Port of Long Beach for the 2010-2018 period. Note the large spikes during the months of March 12 As Table LB.2 in Appendix A indicates, small volumes of edible nuts, rice, tomatoes, and wine are exported through this port.

Ramezani-Carr Intermodal Chassis Availability Page 43 and November. These patterns, which are similar to the Port Los Angeles, are indicative of the seasonal harvest cycle, as well as variations in shipping costs and availability of chassis and space on ocean vessels for speciﬁc export destinations.

Figure LB.6: Port of Long Beach Containerized Edible Nuts Exports (TEUs, Monthly Variation) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Ramezani-Carr Intermodal Chassis Availability Page 44 5.3 Port of Oakland

The Port of Oakland, which is also a landlord port with three international container terminals, is unique in that it encompasses a seaport, rail terminals, an airport, and a portfolio of commercial buildings and parks. Founded over a century ago, the Oakland Seaport within the Port of Oakland serves as the principle ocean gateway for international containerized cargo shipments in Northern California. The Seaport consists of 1,300 acres of maritime-related facilities serving a local market of over 14.5 million consumers, 34 million of them within a seven-hour drive, and 50% of the U.S. population by rail.13

Port of Oakland Seaport

Image Source: iStock Photo.

Figure O.1 presents the distributional characteristics of monthly containerized exports (all

13 For details on Port of Oakland and its operations see https://www.oaklandseaport.com/ and https://explore.dot.gov/views/PortPerformance-temp-view2/ProfileDashboard? Port%20ID=4345&:isGuestRedirectFromVizportal=y&:embed=y.

Ramezani-Carr Intermodal Chassis Availability Page 45 goods, outbound, full and empty containers) through the Port of Oakland during the period 1997 to 2020. The figure shows monthly seasonality in exports, with the trough generally occurring during the month of February and the peak occurring during the month of August. As the figure also shows, the largest variation occurs during the months of August and September. It is during these months that large spikes take place (widest range, defined as the gap between the minimum and the maximum), where as much as 130,000 containers are exported.

Figure O.1: Port of Oakland Monthly Export Container Movement Period: July 1997 - May 2020 (23 observations per month) Source: https://www.oaklandseaport.com/performance/facts-figures/

Figure O.2 presents similar data but for containerized imports (all goods, inbound, full and empty containers) through the Port of Los Angeles for the same period. The ﬁgure shows monthly seasonality in imports, with the trough again occurring during the month of February. The peak occurs during the months of January, July and August. The largest variations occur during the months of Jauary, July, August, and December. This pattern is very different than that of Ports of LA and LB. The largest spikes in imported containers take place in December and January.

Ramezani-Carr Intermodal Chassis Availability Page 46 Figure O.2: Port of Oakland Monthly Import Container Movement Period: July 1997 to May 2020 (23 observations per month) Source: https://www.oaklandseaport.com/performance/facts-figures/

Figure O.3 presents the distributional characteristics of net monthly containerized movement (imports minus exports, full and empty) through the Port of Oakland for the same period. This ﬁgure shows that unlike the Ports of LA and LB, monthly net imports are mostly negative, i.e., most months there are many more outbound than inbound container movements. This imbalance is most pronounced during January and October.14

14 Table O-1A in Appendix A presents the data underlying these plots. That table provides information about the distribution of exports, imports, and net imports by month for the period 1997-2020. The data show signiﬁcant and persistent favorable imbalance, more exports than imports, at the Port of Oakland.

Ramezani-Carr Intermodal Chassis Availability Page 47 Figure O.3: Port of Oakland Monthly Net Container Movement Period: July 1997 to May 2020 (23 observations per month) Source: https://www.oaklandseaport.com/performance/facts-figures/

For the Port of Oakland, the data indicates that over 27% of containers exported and roughly 24% of containers imported are empties. It is important to note that the highest proportion of empty exports occur during the months of March and October through December period, which again coincides with the seasonal peak of containerized agricultural exports.15 Figure O.4 shows the monthly average of empty containers relative to total exports and imports (see Table O-2A data in Appendix A). We were informed that empties brought into Oakland by vessels are not necessarily “imported” from other countries, but are repositioned primarily from Southern California. Again, it is important to note that the peak period for exported empties coincides with the peak season for agricultural exports. Again, the rush to return empties to serve the import market means there are fewer containers available for agricultural exporters during the peak of their season.

15 Table O-2A in Appendix A presents data on the volume of empty container movement at this port. The table provides information about the fraction of outbound and inbound containers that are empties.

Ramezani-Carr Intermodal Chassis Availability Page 48 Figure O.4: Port of Oakland Monthly Empty Container Movement Period: July 1997 to May 2020 (23 observations per month) Source: https://www.oaklandseaport.com/performance/facts-figures/

Table O.1 provides annual historical date on total containerized agricultural exports through the Port of Oakland. The table also shows the volume (in TEUs) of all exports through this port. These data show that roughly 35% of outbound containers carry agricultural exports, which is a much larger fraction of containerized agriculture exports through this port than the Ports of LA and LB. Note also that while the volume of agricultural exports signiﬁcantly declined during 2014-2016 period, in recent years the volume has recovered to its previous levels.

Ramezani-Carr Intermodal Chassis Availability Page 49 Table O.1: Port of Oakland Total Agricultural Exports (TEUs and % of Total) Source: Port of Oakland and USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Year Agricultural Exports (TEU) Loaded Exports (TEU) Agriculture (%) 2010 346693 955579 36.28 2011 368524 993826 37.08 2012 384223 986452 38.95 2013 403747 1014796 39.79 2014 357936 1815188 19.72 2015 307701 1702380 18.07 2016 370875 1831716 20.25 2017 379654 930826 40.79 2018 342684 897804 38.17

Table O.2 provides information about the composition of agricultural exports through the Port of Oakland for the most recent year (2018). The table lists the top 10 commodities for each month. It shows there is little variation in the rankings of the top 10 commodities by month. Considering the top two export items (edible nuts and meat), we observe strong seasonality, with peak exports of edible nuts occurring during October through December and during June and July for meats. It is clear that the largest volume of exports through the Port of Oakland is edible nuts. Wine, processed tomatoes, and rice are also important items for this port, though the volume of other commodities, particularly meats and animal feed, are signiﬁcantly larger. Again, the prior years (2010-17) show very similar patterns for containerized agricultural exports at this port, suggesting that the commodity exporters relying on this port have established relationships and long term contractual agreements with counter parties in destination countries and with stakeholders within the export logistics chain.

Ramezani-Carr Intermodal Chassis Availability Page 50 Table O.2: Port of Oakland Top 10 Containerized Agricultural Exports (TEUs) Period: Jan 2018 - Dec 2018 Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Rank January TEUs February TEUs March TEUs 1 Edible Nuts 6300 Edible Nuts 6484 Edible Nuts 6340 2 Meat 4903 Meat 4546 Meat 4467 3 Animal Feed 2375 Oranges 3880 Oranges 3817 4 Rice 2352 Animal Feed 2765 Animal Feed 3404 5 Grocery Items 2265 Grocery Items 2458 Grocery Items 2705 6 Oranges 2044 Rice 2113 Wine 1826 7 Wine 1286 Wine 1456 Rice 1523 8 Tomatoes (Prep.) 1271 Tomatoes (Prep.) 1394 Tomatoes (Prep.) 1494 9 Dairy Products 942 Dairy Products 1053 Dairy Products 1216 10 Grain Products 920 Beverages 1014 Grain Products 938 Total 24658 27163 27730 April May June 1 Edible Nuts 4142 Meat 3989 Meat 4834 2 Oranges 3322 Edible Nuts 3738 Edible Nuts 3728 3 Animal Feed 3105 Animal Feed 3286 Animal Feed 2898 4 Grocery Items 2167 Grocery Items 2464 Grocery Items 2424 5 Meat 2132 Wine 1638 Wine 1302 6 Wine 1443 Oranges 1528 Tomatoes (Prep.) 1033 7 Dairy Products 1040 Tomatoes (Prep.) 1212 Vegetables 1004 8 Tomatoes (Prep.) 921 Beverages 960 Beverages 936 9 Grain Products 714 Dairy Products 841 Dairy Products 828 10 Beverages 703 Vegetables 789 Fruit 552 Total 19689 20445 19539 July August September 1 Meat 4985 Meat 5929 Meat 5352 2 Edible Nuts 2841 Animal Feed 3372 Edible Nuts 4444 3 Animal Feed 2571 Edible Nuts 3261 Grocery Items 2822 4 Grocery Items 2144 Grocery Items 2441 Animal Feed 2447 5 Wine 1325 Fruit 1900 Fruit 1664 6 Vegetables 1161 Vegetables 1371 Vegetables 1492 7 Tomatoes (Prep.) 1103 Wine 1347 Wine 1270 8 Beverages 1079 Beverages 1206 Beverages 1233 9 Fruit 942 Tomatoes (Prep.) 976 Tomatoes (Prep.) 1044 10 Rice 672 Rice 752 Poultry 535 Total 18823 22555 22303 October November December 1 Edible Nuts 9112 Edible Nuts 10438 Edible Nuts 8544 2 Meat 5895 Meat 5505 Meat 4863 3 Grocery Items 2918 Grocery Items 2737 Animal Feed 2582 4 Fruit 2527 Fruit 2579 Grocery Items 2521 5 Animal Feed 2107 Animal Feed 2568 Tomatoes (Prep.) 1347 6 Wine 1441 Wine 1387 Rice 1227 7 Tomatoes (Prep.) 1222 Tomatoes (Prep.) 1217 Wine 1116 8 Beverages 1002 Rice 1173 Fruit 903 9 Rice 957 Dairy Products 708 Oranges 737 10 Vegetables 826 Grain Products 600 Beverages 736 Total 28007 28912 24576

Ramezani-Carr Intermodal Chassis Availability Page 51 Figure O.5 shows the monthly average (TEUs) for edible nut, processed tomatoes, rice and wine exported through this port. The ﬁgure shows that the peaks for edible nut exports occurs in February-March and again in October-November months. Relative to edible nuts, there is no discernible seasonal pattern for processed tomatoes, rice and wine.16

Figure O.5: Port of Oakland, Containerized Agricultural Exports (TEUs, Monthly Average) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Focusing on edible nuts, Figure O.6 provides candlestick plots of the monthly exports through the Port of Oakland for the 2010-2018 period. Note the large spikes during the months of October and November. These patterns are indicative of the seasonal harvest cycle, as well as variations in shipping costs and availability of chassis and available space on vessels for speciﬁc export

16 As Table O.2 in Appendix A shows, for these commodities, the volume of export through this port is much larger that Ports of LA and LB.

Ramezani-Carr Intermodal Chassis Availability Page 52 destinations.

Figure O.6: Port of Oakland Containerized Edible Nuts Exports (TEUs, Monthly Variation) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by- Commodity/hpfj-zhfg

Ramezani-Carr Intermodal Chassis Availability Page 53 6. The Rise of Mega Ships and Chassis Shortages

According to the World Bank, global container traffic has increased from 224 million TEUs in 2000 to over 793 million TEUs in 2018, of which approximately 55 million were handled by U.S. ports.17 Transportation of containerized cargo has proven to be fast, safe, and efficient. Today, the global container ship fleet consists of more and larger vessels than ever before. As carriers continue to exploit economies of scale by increasing vessel size, the entire land-side logistics chain has been forced to adapt to handling ever larger vessels, in the shortest time possible, and at competitive handling charges.

The Rise of Mega Ships

Image Source: Port of Los Angeles

17 By contrast, ports in China handled nearly 226 million TEUs in 2018. See https://data.worldbank. org/indicator/IS.SHP.GOOD.TU and https://tcdata360.worldbank.org/indicators/IS.SHP.GOOD.TU?countryCHN& indicator=1739&countries=USA&viz=line\chart&years=2000,2018 .

Ramezani-Carr Intermodal Chassis Availability Page 54 The global container ship fleet consists of a wide range of ships from below 500 TEU in capacity to Ultra Large Container Vessels (ULCV) with a capacity of over 20,000 TEUs. At the top end of the scale are the “Deep Sea” container ships that service the east-west trades. These are designated as ULCV, Post-Panamax or Panamax, according to their capability to transit the Panama Canal given their physical dimensions. The “Intermediate” size ships serve the north-south and intra-regional trade. The smaller “Feeder” ships operate on an intra-regional basis, often feeding cargo within a region from or to larger ports that handle international trade. Tables 6.1A and 6.2A in Appendix A contain historical data on the number and capacity of the global container fleet by vessel type and size in TEUs. Considering the fleet size, it appears that the number of vessels has nearly doubled over the past 15 years. The growth in the fleet size is clearly driven by the number of large and mega-size ships (10,000+ TEUs). For example, the fleet of ULCV ships has grown by eight-fold since 2013. Turning to capacity, Table 6.2A shows that the overall TEU capacity has experienced a cumulative annual growth rate of over 8% since 2005. Furthermore, a large proportion of the growth in container ship capacity in recent years has been in the Panamax and Post-Panamax category.18 Table 6.3A in Appendix A presents information about the capacity and number of container vessels calling on U.S. ports in 2016. The data presented show that the annual number of ships and the average vessels size calling on the ports in the Western United States are the largest among the U.S. ports. Moreover, these ports were visited by especially large vessels (∼18,000+ TEUs) in 2016. Since that time, even larger container vessels have called on these ports. The growth in vessel capacity accompanied by higher frequency of calls from multiple mega ships have contributed to spikes in container volume at the California ports, leading to chassis dislocations and unanticipated, but severe, equipment shortages. While the growth in container vessel size and capacity has resulted in significant stress on congested port facilities and inland transportation modes, it appears that, growth in fleet size may have contributed to more stable freight rates. Figure 6.1 provides a graphical presentation of the dynamics of monthly container freight rates from the Port of Los Angeles to the Port of Shang- hai over the period 2012-2020 (Table 6.4A in Appendix A presents the distribution for the same data). As Figure 6.1 demonstrates, freight costs for 20 and 40 foot containers have declined since

18 Intermodal container charter companies are playing an increasingly larger role in the container shipping industry. Historically, a large portion of the world’s container ship capacity was owned by the ocean carriers. Today, a larger proportion of the capacity is owned and operated by charter companies.

Ramezani-Carr Intermodal Chassis Availability Page 55 2013, and the cost differential between 20-ft and 40-ft containers have narrowed in recent years. This shrinking gap in shipping costs, together with higher availability of 40-ft containers provides strong economic incentives for agricultural exporters to utilize the larger containers.

Figure 6.1: Monthly Container Freight Rates (20-ft and 40-ft $) Origin: Port of Los Angeles Destination: Port of Shanghai Period: Jan 2012 to April 2020 Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel- Fleet-Data/n3eq-jw8f

Figures 6.2 and 6.3 show the monthly variability of freight costs by container size. It appears that for the 20-ft containers (Figure 6.2) shipping costs are lowest during the months of August and September (August also has the lowest cost variation).

Ramezani-Carr Intermodal Chassis Availability Page 56 Figure 6.2: Distribution of Monthly Container Freight Rates ($ per 20-ft container) Origin: Port of Los Angeles Destination: Port of Shanghai Period: Jan 2012 - April 2020 (8 monthly observations) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel- Fleet-Data/n3eq-jw8f

Turning to Figure 6.3, we note that freight rates are lowest and least variable during the months of August through November.19 This is not surprising as the volume of outbound empty containers are the highest during these months, when ocean carriers push to return containers to Asia-Paciﬁc destinations in an attempt to satisfy U.S. import demand during the holiday season.20

19 Both freight rates also show occasional large increases (outliers) that correspond to export volume spikes at the San Pedro Bay ports. 20 As Table 6.4A shows, these freight rate patterns also hold for shipments that originate from Chicago. Comparing the shipping costs by the origination point, we note that the land-side component of the total shipping costs (Chicago to LA-LB) generally exceeds 50% of total freight costs for exports originating from the U.S. hinterland.

Ramezani-Carr Intermodal Chassis Availability Page 57 Figure 6.3: Distribution of Monthly Container Freight Rates ($ per 40-ft container) Origin: Port of Los Angeles Destination: Port of Shanghai Period: Jan 2012 - April 2020 (8 monthly observations) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel- Fleet-Data/n3eq-jw8f

The differential in import and export freight rates (20-ft or 40-ft containers) is perhaps the strongest driver of container movement and chassis shortages in California ports. Figure 6.4 shows the asymmetric nature of freight rates between the Port of Los Angeles and Port of Shanghai during the past year. The freight rate gap is reﬂective of the trade imbalance between the United States and the countries in the Asia-Paciﬁc region.

Ramezani-Carr Intermodal Chassis Availability Page 58 Figure 6.4: Asymmetric Container Freight Rates ($ per 40-ft container) Period: Oct 2019 to Oct 2020 (Weekly observations) Source: Journal of Commerce Container Pricing Data (as of 10/30/2020) https://www.joc.com/market-data-landing/container-pricing

Export Rates: Port of Los Angeles to Port of Shanghai

Import Rates: Port of Shanghai to Port of Los Angeles

Historically, freight rates for import shipments from Asia (Trans-Paciﬁc eastbound) are on av-

Ramezani-Carr Intermodal Chassis Availability Page 59 erage 2-3 times higher than the rates for export shipments to that region (Trans-Pacific westbound). However, this ratio can vary widely over the year, depending on spikes in volume of container imports and/or exports through these ports. Figure 6.4 provides a vivid demonstration of the impact of spikes in container volume, in this instance caused by the COVID crisis, resulting in import freight rates that are nearly eight times higher than the export rates. Generally, summer through fall is the slowest period of the year for U.S. exports to Asia. As section 5 illustrated, this is particularly true for agricultural exports because the harvest season has not started yet and the shipments of many high-value crops, such as edible nuts, will not reach their peak till late fall. By contrast, U.S. imports from Asia are highest at the same time that agricultural exports reach their peak. This mismatch widens the gap in import and export freight rates, which counter intuitively, can adversely impact agricultural exporters. Ocean carriers are likely to base their capacity and pricing decisions on demand for imports because at the Ports of Los Angeles and Long Beach, imports outnumber exports by a large margin (often more than 2 to 1). When import freight rates are significantly higher than export rates, ocean carriers have greater incentive to quickly return empty containers to Asia-Pacific and take advantage of higher freight rates, than delay empty returns in search of export loads. This outcome clearly disfavors containerized agricultural exporters because of their distance to distribution centers where empty containers are available and meeting other time consuming requirements associated with agricultural shipments (i.e., container cleaning, regulatory inspections, and other issues). The rush to return empties also places immense pressure on chassis supply, reducing agricultural exporters’ access to chassis, even if they have secured empty containers for their exports.

Ramezani-Carr Intermodal Chassis Availability Page 60 6.1 Mapping Container Volume to Chassis Demand and Supply

In this section we consider the determinants of demand and supply for chassis at the three Califor- nia ports. As the previous sections suggests, over the last decade, as ocean carriers divested from chassis ownership, they increased investment in more efficient mega ships, which discharge and load a greater number of containers per port terminal visit. There is near unanimous agreement among the various port stakeholders, that chassis shortages principally occur during the spikes in the volume of containers moving through the ports, which is mostly due to the growth in vessel size and frequent episodes of “ship bunching” resulting from simultaneous port calls by multiple mega vessels. In fact, the arrival of mega ships often create peak stress periods for the land-side infrastructure, causing massive chassis dislocation and shortages. While public and private investment in infrastructure and automation has enabled the California ports to meet some of the challenges resulting from growing vessel size, persistent chassis shortages may be indicative of insufficient growth in chassis supply. This is not surprising, as determining the optimal stock of chassis has proven to be a daunting challenge for the ocean and motor carriers, beneficial cargo owners (BCOs), terminal operators, chassis leasing companies, policy makers and public transportation agencies.

Critical Assets: Truck, Chassis, and Container

Containers and chassis are critical components of the intermodal transport system. From our conversation with many stakeholders, we learned that the biggest challenge for meeting the chassis needs of agricultural exporters occurs during peak volume cycles, during which having chassis in the right place at the right time can be a difﬁcult and costly task. The most prevalent reasons

Ramezani-Carr Intermodal Chassis Availability Page 61 for chassis shortages include seasonal peaks in container volume, coupled with volume spikes arising from inaccurate projections, extended dwell times at distribution centers, shortage of truck manpower, and chassis use terms and return policies, all of which contribute to the dislocation of chassis during high volume cycles. The availability of intermodal chassis has become problematic in recent years because of major changes in the way ocean carriers operate and optimize their business model. The Great Recession of 2007-09 resulted in unprecedented disruptions in global trade, leading to significant decline in demand for ocean freight. Fall in demand and excess supply due to overcapacity brought about by the arrival of the mega vessels resulted in major declines in shipping rates and great economic challenges for both ocean carriers and shippers. The recession, and the subsequent financial crisis, prompted major changes starting with ocean carriers’ divestiture from chassis ownership. After the Great Recession, the key to ocean carriers’ ability to survive volatile trade – including unexpected shocks such as trade wars and a pandemic – is to optimize the number of ships, control costs, and ensure the stability of shipping rates. To achieve these objectives, ocean carriers formed various alliances and a wave of consolidations followed and continues today. In short, historically large swings in capacity and shipper demand resulted in a turbulent business environment for ocean carriers. Consolidation and the formation of alliances helped mitigate these issues by enabling ocean carriers to optimize their operation and enhance their profitability. However, logistics industry participants have attributed several systemic inefficiencies to arrival of mega-ships and carrier consolidation/alliances. These include, terminal congestion, chassis dislocations and its associated costs, and ship bunching that resuls in delays in securing intermodal equipment.21 Chassis leasing companies emerged after the ocean carriers’ exited from that line of business. Since their emergence, chassis provisioning has experienced many improvements in its business structure and processes have been developed to help fill the supply void created by the ocean carriers’ exit (for example, chassis pools). As is the case with ocean carriers, chassis leasing companies

21 For a detailed analysis see “The Implications of Mega-Ships and Alliances for Competition and Total Supply Chain Efﬁciency: An Economic Perspective,” Global Shippers Forum (2016) available at https://globalshippersforum.com/media/1267/gsf-mega-ships.pdf, and “The Impact of Mega-ships and Carrier Alliances on Ports and Terminals,” Tosca Bonardi Pinder, California Maritime Academy (2016), https://csum-dspace.calstate.edu/bitstream/handle/10211.3/173270/PINDER% 20Impact%20of%20Mega-Ships%20and%20Carrier%20Alliances.pdf?sequence=1.

Ramezani-Carr Intermodal Chassis Availability Page 62 (IEPs) operate in manner that optimizes their operations and maximizes their proﬁtability, rather than enhance the efﬁciency of the overall intermodal logistics chain. Appendix B provides a survey of current chassis provisioning models in the United States. Figure 6.5 provides a summary of the advantages and shortcomings of various chassis provisioning structures in the United States.

Figure 6.5: Advantages and Disadvantages of Chassis Supply Models Source: Samaneh Shiri and Nathan Huynh (2018), “Assessment of U.S. chassis supply models on drayage productivity and air emissions”, Transportation Research Part D, pp 174-203.

Ramezani-Carr Intermodal Chassis Availability Page 63 While the dynamics of container movements and the frequency of ship bunching at sea ports is the most important determinants of chassis demand at the port and inland terminals, the efﬁciency of the truck drayage system is also of critical importance. Figure 6.6 shows all possible marine container and chassis movements – truck dray and rail - at a marine terminal at a port facility (solid green arrows). As the ﬁgure suggests, a chassis is involved every time a container moves by truck, irrespective of the origin or destination.22

Figure 6.6: Use of Chassis in Import and Export of Containerized Freight Source: NCFRP Report, Guidebook for Assessing Evolving International Container Chassis Supply Models

22 Domestic chassis, which are not the focus of this report, are involved when 53-ft domestic containers are moved (the dotted green arrows).

Ramezani-Carr Intermodal Chassis Availability Page 64 It is important to note that in the United States, chassis also provide a storage function, in addition to their role in drayage operations. Storage of containers on chassis, for example at a “wheeled” terminals or a shipper’s facility for a prolonged period of time (upward of 30 days of free time) contributes to chassis dislocation and has a significant impact on available supply. Other factors that influence chassis use efficiency (for example, the number of times a chassis can be used to move containers to and from a port per day) are the distance between the port and container’s destination, congestion in and around port facilities, wait times and the speed of chassis movement within the port terminal and IEP facilities, ocean carriers’ chassis requirements, the quality condition and age of the chassis, technology used for chassis visibility (GPS, RFID), and federal and state regulatory requirements that impact container and chassis moves (roadability requirements). Figures 6.7 and 6.8 show the types of container movement between the port’s container terminal, importers and agricultural exporters. Figure 6.7 shows possible patterns of container movement, in this instance at a port without on-dock rail terminals – i.e., no train loading at the vessel’s terminal. The first pattern presented, labelled Pattern A, represents the most typical move, where a loaded container is delivered to the importer (the consignee), and subsequently the empty is returned to the port and loaded on outbound ships to expedite future imports. This move, which is the most common at the Ports of Los Angeles and Long Beach, and to a lesser degree the Port of Oakland, typically occurs when an Asian import container is moved to the importer’s facilities, unloaded while the chassis remains with the container and is transported back to the port terminal on the original chassis and the empty returns to Asia to begin a new cycle. Note that this may be the most inefficient type of move since the container is returned empty and the chassis is removed from circulation for the entire duration of the time the container is in transit. Pattern B involves the storage of empty containers at intermediary depots (off-port container yards), potentially in close vicinity to exporters. Under this pattern, congestion and wait times at the port terminals may be avoided and the empty chassis may become available for another pick up at the port. The empty containers at the depot may be returned to the port at a later date or sent to exporters for their use.

Ramezani-Carr Intermodal Chassis Availability Page 65 Figure 6.7: Container Movement Patterns - Without On-Dock Rail Terminal Source: Authors’ creation.

Legend

Under Pattern C, which is the most common in California ports, the empty is returned to the port’s empty container yard, later moved to an exporter, and ﬁnally the loaded container is returned to the port and placed on a ship. Patterns D is called a “match-back” or “street-turn” operation, where an emptied import container is matched with an export movement.23 Pattern D is similar to B but rather than returning the empty container to the port, it is stored at a depot and subsequently

23 In rare cases the match-back occurs at the port rather than a depot, resembling Pattern C.

Ramezani-Carr Intermodal Chassis Availability Page 66 forwarded to an exporter, and once loaded it moves back to the port. Hence, the difference between C and D is the location where the empty container is stored before being reused in an export move. Pattern E, called a “street-turn”, is the most interesting container move – the “holy grail” in terms of efficient container and chassis movement — from the perspective of most stakeholders in the intermodal logistics chain. This pattern is a special match back operation, where the import container, once unloaded at the consignee’s facility, directly moves to the exporter’s facility to be loaded again. This operation, however, requires a high degree of information sharing and coordination among various stakeholders. Obviously, this is the most efficient type of container movement, as it saves transport time and avoids temporary storage of empty containers. However, in practice, street-turns are very difficult to implement, because such moves require significant level of coordination among carriers, trucker, chassis providers, and importers and exporters. For example, container types, the shipping company and its location, and other import and export operation requirements must be similar and coincide in time. This is particularly difficult for agricultural exporters, because in most instances, the container may need intermediate care (for example, cleaning and repairs) before it can be reused. From an economic perspective, street-turns offer the opportunity to minimize the land-side movement costs, which include all transportation costs between terminals, depots, consignees and shippers, chassis costs, plus storage costs at the depots and the port. From an informational and coordination perspective, the underlying logistics network structure linking consignees, ocean and motor carriers, shippers, IEPs, container depots, and ports must share real time information and be willing to coordinate their operational plans. Finally, Pattern F captures the possibility that import containers are unloaded at the port facility, and the containers are returned to the ship empty, or are loaded with exports before being placed on the ship. This pattern can occur at some ports in export oriented economies, which have invested in modern distribution centers at their ports and are able to sort and ship freight in a timely and efficient manner.

Ramezani-Carr Intermodal Chassis Availability Page 67 Figure 6.8: Container Movement Patterns - With On- or Off-Dock Rail Terminals Source: Authors’ creation.

Legend

Ramezani-Carr Intermodal Chassis Availability Page 68 Figure 6.8 shows similar patterns for a port with on- or near-dock rail facility, where a container is mounted on a chassis and transferred by truck between the marine terminal and the railroad ramp. With the near-dock facility, a container is transferred, with or without a chassis (by a stevedoring company) between a marine terminal and an adjacent, but external rail loading facility. Both on- and near-dock rail facilities are available at the California ports; however, rail movements often involve shipping of cargo over longer distances. To summarize, understanding and estimation of chassis demand at California, and other ports, require information about the following:

• Data on the dynamics of inbound and outbound container movements, including information about the empty and loaded container volume on arriving ships, the timing, the expected duration of loading and unloading, the frequency of port calls by mega vessels, and the resultant volume spikes from ship bunching.

• The relative prevalence of various types of container and chassis moves, as depicted in Fig- ures 6.7 and 6.8, and the resultant chassis dwell time. Such information is critical for pre- dicting chassis dislocation and shortages. As an example, consider Pattern C in Figure 6.7. Note that under the right circumstance, the moves depicted could be performed using a single chassis over a short time period. Alternatively, the container moves involved may require four (4) chassis over a much longer time interval. Hence, a detailed characterization of the types of container-chassis moves, and their impact on chassis dwell time and chassis circulation is critical to understanding chassis dislocation and its impacts on the supply of this critical equipment.

• There is an acute need for the type of information noted above for port facilities nation- wide. The U.S. Department of Transportation publishes the annual Port Performance Freight Statistics, which reports a consistent set of metrics for America’s ports.24 However, no information about chassis demand and supply is collected for U.S. ports. As industry associations have noted, information about the number of chassis in good working order, needing repairs, and out of order (by size- 20ft or 40ft), chassis utilization rates at local IEPs, and chassis to container ratio at the ports are critical for the logistic planning of both importers and exporters.25

24 See https://www.bts.gov/ports. 25 See https://www.bts.gov/archive/port_performance/Jennifer_Safavian.

Ramezani-Carr Intermodal Chassis Availability Page 69 6.2 Chassis Supply at California Ports

Intermodal chassis in the U.S. have a fixed size to support a specific container size; that is, a 20-ft container needs to be transported with a 20-ft chassis and a 40-ft container needs to be transported with a 40-ft chassis. In the U.S., the ratio of 20-ft to 40-ft to 45-ft chassis is 25:65:10 (NCFRP Report 20); this ratio suggests that the majority of containers and chassis used in the U.S. are 40-ft in length. In addition to standard chassis, there are specialty chassis, such as chassis equipped with generator sets used to haul refrigerated containers. Rodrigue (2020), states that “Shipping commodities such as grain tends to rely on 20-ft (one TEU) for the simple reason that they can each load around 26 to 28 tons while a 40-ft, because of structural integrity issues, has a loading capacity of about 30 tons, but this load is occupying twice the shipping volume. Consequently, the commodity sector mostly relies on a load unit (20 footer) which is different than many containerized supply chains, such as retail, that are relying on the 40-ft, particularly the high cube.” Our analysis of data from the California ports indicate that over 80% of containers used by agricultural exporters are the 40-ft size. This is because the imports arriving at these ports are primarily shipped in 40-ft containers, creating an over supply of these containers. Accordingly, chassis providers hold a larger inventory of 40-ft chassis. Moreover, as shown in section 5, relative to 20-ft containers, the additional freight costs associated with 40-ft containers are small, the chassis rental rate is the same, while the available physical space is doubled (not the weight limit). Indeed, depending on the commodity being exported, the shipping costs per unit weight can be lower than the 20-ft container. For these reasons, California agricultural exporters prefer the 40-ft containers, though many grain exporters in the Midwest prefer 20-ft containers. Furthermore, our interviews with California agricultural exporters indicate that they are most concerned with 40-ft chassis shortages. Chassis logistics is a bottleneck at California ports and source of delay for drayage and port operations for similar reasons as other U.S. ports. First, delivering container and chassis to two different locations – chassis yard and port or consignee – increases the travel and waiting time. Second, there is an insufficient inventory of chassis available during the peak periods. Finally, often a large fraction of available chassis are out-of-service forcing motor carriers to search for a serviceable chassis, causing further delays. These developments resulted in an increase in demand for chassis pooling schemes, and a move toward chassis ownership and long term lease arrange-

Ramezani-Carr Intermodal Chassis Availability Page 70 ments. Chassis provisioning at California ports, is primarily managed by third-party leasing companies, under a single or hybrid structures (chassis pools) that resemble the provisioning models detailed in Appendix B, with one important exception: not-for-proﬁt cooperative chassis pools are not present at California ports. While chassis management differs among the California ports, chassis shortages at peak times has been one of the single most important impediments for containerized agricultural exports in recent years.

6.2.1 San Pedro Bay Ports

The Pool of Pools (“POP”) is the largest supplier of chassis at the Port of Los Angeles and Port of Long Beach, controlling approximately 70+% of estimated inventory. The POP is an arrangement among three major chassis providers. Under the POP, an authorized user of any of the Participating Pools may acquire, and return, any of the chassis in the combined fleet from any of the locations. By creating a large “gray” fleet of chassis that are available across the port complex, the POP attempts to increase overall efficiency and availability while eliminating “chassis splits,” which occur when a chassis must be picked up or returned to a different location from where the container is picked up or returned. 26 Recent estimates suggests that the POP provides 81,500 chassis of the approximately 100,000 used in the port complex and the nearby rail yards. It appears that TRAC contributes the largest number of chassis, some 37,000 units, to the POP. The interoperable chassis environment created by POP creates flexibility by permitting multiple requisition and drop-off points, potentially eliminates chassis splits and repositioning moves, and permits truckers to use the chassis for multiple trips throughout the two ports.27 Our interviews with several stakeholders suggest that under the POP, perhaps the biggest impediment to making more turns (pick-up and drop-off) is the long wait-time at the maintenance and repair area, performed with union labor. Many expressed frustration with the roadability inspection process, as trucker owned chassis must be approved for roadability when exiting the ports. The question of jurisdictional authority over chassis inspections will need to be resolved. That resolution may enhance the incentives for truckers to invest in their own equipment or enter into long-term chassis leases. Finally, most stakeholders see technology as a way to manage chassis

26 LA/LB Pool or Pools, FAQs: http://www.pop-lalb.com/reports/POP_FAQ.pdf. 27 See pop-lalb.com.

Ramezani-Carr Intermodal Chassis Availability Page 71 demand and supply imbalances more efﬁciently.

Other Chassis Providers: Additional chassis providers at the San Pedro Bay operate outside the POP. These include small chassis companies, trucker owned chassis, and motor carrier organizations. For example, in May 2015, the Harbor Trucking Association (HTA) announced that it would own and operate its own pool of chassis for member trucking companies. The HTA chassis can be used at any marine terminal and truckers are billed by the day. The equipment is inspected for “roadability” and veriﬁed before being turned over to the trucker for use at the ports.28

28 See Mitigating Urban Freight Through Effective Management of Truck Chassis, Thomas O’Brien, Tyler Reeb, and Annette Kunitsa (2016) https://dot.ca.gov/-/media/dot-media/programs/research-innovation-system- information/documents/f0017160-ca16-2813-finalreport.pdf.

Ramezani-Carr Intermodal Chassis Availability Page 72 6.2.2 Port of Oakland

Oakland is heavily dependent on drayage, with up to 90 percent of containers leaving the port on trucks. The following are the chassis providers at Port of Oakland:29

The Bay Area Chassis Pool (BACP): This “pool” is 100 percent controlled by Flexi-Van. This pool has been around for a number of years. It is estimated to have been started with roughly 1,000 chassis, over time it grew to roughly 10,000 chassis, and now operates approximately 8,400 chassis.

The West Coast Chassis Pool (WCCP): This “pool” is run by SSA Marine, the largest terminal operator in Oakland. WCCP operates approximately 9,000 chassis.

The DCLI Pool: DCLI has its own chassis pool and it also appears to manage the chassis owned by the ocean carrier Evergreen. Evergreen previously sold its chassis in Los Angeles-Long Beach to TRAC, and to DCLI in the Oakland area and Paciﬁc Northwest. These two pools operate approximately 5,200 chassis.

The TRAC Northern California Pool: TRAC also has its own chassis “pool”. The number of chassis it operates is approximately 1,000.

Matson Shipping Line: Matson is an ocean carrier that owns and operates approximately 4,000 chassis. Matson is mainly a domestic carrier with few international routes.

Motor Carrier Owned or Leased: In Oakland is it estimated that at least 20% of the total container movements in and out of the marine terminals are now performed with trucker owned/leased chassis. Several stakeholders noted this percentage may be higher and closer to 30%.

29 The below chassis data are based on various stakeholder interviews.

Ramezani-Carr Intermodal Chassis Availability Page 73 7. Proposed Chassis Solutions for California Ports

Agricultural exporters have three primary concerns with respect to the movement of their export products: total transportation costs, length of transit time, and freight reliability. Their supply chain and transportation decisions are made on the basis of the trade-offs among these three metrics and related risks.30 While transportation costs, transit time, and freight reliability are important metrics, we dis- covered that agricultural exporters also assign importance to other commercial considerations, as summarized in Table 7.1. These concerns arise whether growers directly negotiate with ocean carriers, or alternatively rely on intermediaries such as third-party logistics providers (3PLs) and freight forwarders – henceforth referred to as “transportation service providers” – to move their products to their target international destinations.31 Agricultural transportation service providers include exporters, motor carriers, ocean carriers, chassis leasing companies, the ports, and the marine and rail terminal operators. Each stakeholder group has distinct interests, which at times may conﬂict with others’ interests. For example, BCOs are focused on chassis cost, availability, and service. They tend to view chassis and containers together, not as separate items. Agricultural BCOs need an ample supply of containers and chassis at the right place and the right time, in order to minimize transit delay. Motor carriers are concerned with maximizing driver productivity, which includes minimizing turn times. Their interests tend to line up well with those of BCOs.

30 These considerations remain the same if the consignee is the BCO covering the transportation costs. 31 Larger transportation service providers are able to negotiate preferred terms but the smaller entities may use split shipments managed by third-party logistics providers (3PL) or non-vessel operating common carriers (NVOCC), which in turn contract with ocean carriers for the best container and chassis terms. See Transportation Research Board, National Cooperative Freight Research Program (NCFRP Report 20), Guidebook for Assessing Evolving International Container Chassis Supply Models, p. 40 (2012).

Ramezani-Carr Intermodal Chassis Availability Page 74 Table 7.1: Transportation Concerns of Agricultural Exporters

Service Risk Can the transportation service provider secure the right container and chassis, at the right place, at the right time? Service Terms Can the transportation service provider obtain favorable delivery terms, including the ability to choose between live-load versus drop and pick, and “free time”? Cost As applicable, what are the explicit and implicit costs associated with the container and chassis use, including penalties related to ex- ceeding free time allowances (We note that many agricultural exporters receive a “bundled shipping rate,” rather than an explicit break down that shows container and chassis costs separately.) Quality & Safety What are the container and chassis service terms that a transportation service provider must meet? Will the service terms for meeting federal and state regulatory requirements (for example agricultural inspections, or roadability requirements) result in shipment delays? Liability What are the risks associated with speciﬁc transportation service providers?

A number of possible paths for alleviating chassis shortages have been proposed and widely discussed by the stakeholders in the intermodal logistics value chain.32 The solutions put forth essentially recommend: 1. Increased investment in chassis primarily by motor carriers and BCOs, and other stakeholders. 2. Major improvements implemented by IEPs, including investment in technology, increased repairs and maintenance, and expanded chassis inventory to enhance the efﬁciency of the current chassis provisioning system. 3. Enhanced access to port facilities (appointment and information sharing systems) and the development of additional chassis depots in the vicinity of the ports. 4. Creation of new chassis pooling arrangements, such as the “chassis utility model” and the “open choice pools,” that offer full interoperability and remove the current system of preferential access to chassis. Taking the cumulative data and ﬁndings of this report into consideration, we showed that chassis

32 See Difﬁcult solutions to US chassis chaos emerge, Journal of Commerce, Feb. 6, 2019, https: //www.joc.com/port-news/port-equipment/difficult-solutions-us-chassis-chaos- emerge_20190206.html .

Ramezani-Carr Intermodal Chassis Availability Page 75 shortages may be avoided by shifting agricultural exports to the days, weeks or months with low volume of container movement at these ports. The details of this time-series solution is worthy of further study. Additionally, we propose the following two feasible solutions that could reduce the impact of chassis shortage on agricultural exporters, and subsequently reduce transportation costs and transit times, and improve freight reliability.

7.1 Incentivize Chassis Ownership and Long-Term Leases

An important solution to the perennial chassis shortages at California ports is to provide additional incentives for motor carriers to own chassis or enter long-term lease arrangements. This can be achieved by providing targeted subsidies, including low interest rate loans and other direct financial incentives. Likewise, it is important to provide incentives for BCOs to secure their own dedicated chassis fleet through long term leases under favorable terms. Even a small increase in chassis ownership among the motor carriers and BCOs will enable these stakeholders to better manage peak demand surges, while they continue to rely on commercial chassis pools to handle their normal business operation. Financial incentives can also be directed towards reducing the adverse costs of chassis ownership. Truckers and BCOs need space to store chassis, as well as resources to cover costly maintenance and repairs, and high insurance premiums. At the margin, even small subsidies that reduce these costs may provide sufficient incentives for ownership and long-term leases. Finally, there is supporting precedent for this recommendation. A number of existing federal agencies already provide credit facilities, including subsidized loans, in support of other “key industries” and can serve as a model for this approach. Detailed development of this proposed solution, including the institutional structure, incentive design and implementation method, is outside the scope of the present report, but should be pursued in future studies.

7.2 Develop a Dedicated Chassis Pool to Serve Agricultural Exporters

As the analysis in section 5 showed, the volume of containers transiting through the California ports is highly volatile and difficult to predict. Volume uncertainty leads to difficulties in determining the “optimal inventory” of chassis, both at the aggregate and an IEP level. Various stakeholders manage container volume uncertainty differently. For example, ocean carriers and IEPs seek forward contracts that fix the number of chassis and the rental rate over a specified time period. In

Ramezani-Carr Intermodal Chassis Availability Page 76 fact, long-term leases are simply a forward contract that permits these economic entities to share the risk due to uncertain demand and supply of chassis. This form of uncertainty is the norm within agriculture, where weather and environmental unpredictability in conjunction with random shocks to demand and supply create a highly risky business environment. A variety of risk sharing and risk pooling structures have been developed to reduce the impact of such uncertainties both on farmers and the firms that use agricultural products as inputs in their production process. These same concepts provide the basis for agricultural exporters and their transportation service providers to pool their resources and collectively manage the risks arising from the volatile container volume movements. The basic idea put forth here is to create a not-for-profit pool that holds and manages a “buffer stock of chassis” that is dedicated specifically to agricultural exporters. Similar pools have been created by truckers, and coalitions of shipping and rail car companies. The existing not-for- profit model can serve as a starting point to design a pool structure that best serves the interests of agricultural exporters and their transportation service providers. Statistical modeling can be utilized to determine the size of the optimal buffer chassis inventory. In the remainder of this section, we further develop this concept and discuss other factors that bear on the development of this chassis provisioning model. The creation of a not-for-profit chassis pool will enable the participating stakeholders to share several benefits. First, agricultural exporters and their transportation service providers will gain the flexibility to respond to uncertain container volume cycles, particularly sudden volume spikes. Second, they will not have to waste time and resources switching out and returning chassis, deal with inspections and other related issues, eliminating supply chain inefficiencies. Third, the indi- vidual capital burden on motor carriers or BCOs is reduced because the pool buys or leases the chassis at favorable rates. Moreover, a chassis management company will operate the pool, reducing operating costs, regulatory costs, invest in technology, undertake maintenance and repair, and by virtue of its size obtain favorable liability insurance. The benefits and costs of operating the pool are shared among the members under a break-even operating model. All of these help the participating stakeholders remain competitive in their own businesses and for the benefit of the agricultural logistics system.

The Pool Focus: The focus of the proposed chassis pool is narrow and strategic - agricultural exporter and their service providers. The product is 40-ft chassis appropriate to agricultural export

Ramezani-Carr Intermodal Chassis Availability Page 77 containers. Agricultural exporters and their service providers would not own the chassis or manage the pool, but they will be the sole beneﬁciaries of the pool. The Pool’s governance is represented by these stakeholders and they set the parameters for the operation of the pool.

Participating Constituency/Stakeholders: Agricultural exporters, motor carriers, chassis leasing companies, ports (Oakland, Los Angeles, Long Beach) and terminal operators, and speciﬁc ocean carriers with large agricultural export business (Evergreen and MSC). Within this frame- work, unionized port labor that performs chassis maintenance and repair (M&R), will become a part of the solution.

Geographic Scope: The pool would mainly serve agricultural exporters, particularly from Cali- fornia’s Central Valley, but also would be open to all (40-ft) containerized agricultural exports out of Los Angeles, Long Beach and Oakland.

Pool Model Parameters-Structure: The pool would mostly operate like a daily usage model, where it charges a daily usage fee and then any overage or underage on that daily usage is dis- tributed back to or from the shippers. For example, if the pool’s chassis charge is $25 per day, and if that exceeds the fixed and operating costs of a chassis, the difference is refunded or becomes a charge (if there is a shortfall) to members, received (paid) on a quarterly or semi-annual basis. Both large and small agricultural exporters can benefit from this structure. The pool can offer daily usage rates, which are attractive to small exporters. The pool can also offer volume discounts and long-term lease to larger shippers and agricultural enterprises, who could agree to a fixed reduced price and commitment to utilize a set number of chassis (both parameters can be adjusted over time). Hybrid contracts can also be used, where the pool users commits to certain volume of chassis at a fixed price and then the higher daily rates in the event they require additional chassis. Thus, there are several potential contractual structures the pool can adopt. For example, chassis rates can be designed to incentivize timely chassis return and discourage idle chassis dwell time. This would act in similar manner to detention and demurrage charges that incentivizes timely movement of containers.

Pool Operator-Manager: An existing not-for-proﬁt chassis provider may be a good starting point. It appears that some ocean carriers may be supportive of the not-for-proﬁt chassis provisioning

Ramezani-Carr Intermodal Chassis Availability Page 78 model, as their interests align with such pools. It is also possible to hire a chassis management ﬁrm to operate the pool. Finally, the three local chassis providers (DCLI, FlexiVan, TRAC) have in-house expertise and may be interested in managing such a pool, at a cost that would be competitive and attractive to agricultural exporters and their transportation service providers.

Pool Contributors: There are three possible sources for chassis contributions for this pool:

1. Existing trucker-controlled chassis that motor carriers may be willing to contribute. 2. Because this proposed pool may take some business away from the current chassis leasing companies at the three ports, those providers may wish to contribute their unused chassis to the new chassis pool. 3. Newer and more modern chassis may be leased from manufacturers, which appear eager to expand into chassis leasing and sales.33 4. Ocean carriers with a large portfolio of agricultural import and export business clearly have incentives to contribute to the proposed pool. Two ocean carriers (Evergreen and MSC) still own and operate chassis at one or more of these ports. Both have signiﬁcant agricultural business and the incentive to divest from the chassis business and assist their major business partners.

Cost and Pricing: Chassis pricing would be based on a break-even model. Prices must minimally cover operating cost of the chassis, including maintenance and repair.

Chassis Depot Location(s): The primary location should be at the ports, with a possible second depot located in the Central Valley, near agricultural exporters. Arranging for depot location, particularly in Central Valley, should not be difﬁcult.

Chassis Utilization Rate: Recognizing there are different deﬁnitions of “utilization”, we deﬁne this term as the number of non-revenue generating to revenue generating chassis. Non-revenue generating chassis include broken, misplaced, and in the process of being repositioned chassis. For the proposed dedicated pool, a future study should be undertaken to determine the optimal utilization rate. However, the chassis stakeholders will collectively determine the operating utilization rate.

33 See Appendix B discussion entitled “The Role of Chassis Manufacturing and Sales in Chassis Supply”.

Ramezani-Carr Intermodal Chassis Availability Page 79 Chassis Dwell Time: The average (revenue generating) chassis dwell time is highly variable. We were advised that the large non-agricultural importers - Walmarts, Targets, etc. - appear to receive 30 free days of dwell time from ocean carriers. For the proposed dedicated pool, a future study should be undertaken to determine the appropriate free time. However, the chassis stakeholders will collectively determine the operating utilization rate.

Seasonality: The proposed chassis pool should determine the size of the chassis pool so as to accommodate the seasonal patterns identiﬁed in section 5 of this report.

Stakeholder Buy-In: Many agricultural exporters and related stakeholders are unhappy with the current situation. This includes the ports and terminal operators, shippers/freight forwarders, unionized labor, and majors motor carriers. Stakeholder interest and buy-in will have to be ad- dressed, but should not be a major obstacle given the narrow role of the buffer chassis pool.

Ramezani-Carr Intermodal Chassis Availability Page 80 8. Conclusions and Directions for Future Research

This study identified the factors that impact the provisioning of containers and chassis suited to agricultural export through the Ports of Los Angeles, Long Beach, and Oakland. We character- ized the variability of monthly container traffic at these ports and conducted similar analysis for containerized agricultural exports. Utilizing recent data and insights from key stakeholders, this study identified key impediments to the efficient movement of containerized agricultural exports. We also formulated potential mitigating strategies, including economic policy tools and incentives to address chassis shortages problem. We proposed three feasible solutions for mitigating chassis shortages for agricultural exporters. First, the potential to shift agricultural exports in time to periods of low container volume (excess chassis supply). Second, public policy and economic incentives, such as targeted subsidies, including low interest rate loans, can play an important role in making chassis ownership or long-term leases more attractive. Third, we suggested the creation of a not-for-profit chassis pool that is dedicated to meeting the needs of agricultural exporters. Such a pool will enable the participating stakeholders to gain chassis supply flexibility, increase efficiency of their operations, and eliminate supply chain uncertainty. There are a number fruitful directions for extending this research. First, the proposed mitigation strategies should be studied in greater detail. For example, it is important to use higher frequency data (daily or weekly) and time series econometric techniques to fit linear and non-linear models that better characterize the dynamics of container volume. Such an exercise may suggest shifting agricultural exports across time by days or weeks rather than months. Similarly, it is important to determine the types of financial subsidies that could induce motor carriers and BCOs to invest in chassis or enter long-term leases. Finally, the ultimate solution to chassis shortages that impede agricultural exports is to create a buffer stock of chassis for their exclusive use. The proposed not-for-profit chassis pool likely offers the best option for agricultural transportation service providers. It is important to undertake a deeper study, engaging all stakeholders, to develop a solution that can potentially improve on chassis ownership and long-term lease contracts.

Ramezani-Carr Intermodal Chassis Availability Page 81 9. Appendix A: Supporting Data Tables

Table 4.1A: U.S. Exports of Bulk and High-Valued Agricultural Products (HVP) Period:1975-2018, Source: USDA, Economic Research Service https://www.ers.usda.gov/webdocs/DataFiles/50441/ XfyHVPBULK.xls?v=1237.8

Total Value of Percent Share of Total Year Agricultural Exports ($B) Bulk HVP 1975 21.817 72.36 27.64 1976 22.742 74.10 29.59 1977 23.974 65.80 34.20 1978 27.289 66.04 33.96 1979 31.979 64.91 35.09 1980 44.670 67.07 32.93 1981 43.783 66.73 33.27 1982 39.097 65.62 34.38 1983 34.769 64.18 35.82 1984 38.027 65.96 34.04 1985 31.201 61.35 38.65 1986 26.312 52.52 47.48 1987 27.876 51.00 49.99 1988 35.316 53.10 46.90 1989 39.674 46.60 59.34 1990 43.480 52.12 47.88 1991 37.864 44.79 55.21 1992 42.555 44.09 55.91 1993 43.058 42.58 57.42 1994 43.893 39.13 68.70 1995 54.613 43.04 56.96 1996 59.786 46.73 53.27 1997 57.305 48.30 59.17 1998 53.662 37.32 62.68 1999 49.118 36.11 3.89 2000 57.620 34.88 65.12 2001 52.717 33.39 66.61 2002 53.319 34.13 65.87 2003 56.014 36.33 63.67 2004 62.400 41.59 58.41 2005 62.516 36.23 63.77 2006 68.593 35.66 64.34 2007 82.220 38.39 61.61 2008 114.911 44.08 55.92 2009 96.296 38.21 61.79 2010 108.529 37.68 62.32 2011 137.465 42.24 57.76 2012 135.907 36.43 63.57 2013 141.139 32.78 67.22 2014 152.326 34.51 65.49 2015 139.757 32.93 67.07 2016 129.603 32.96 67.04 2017 141.840 35.42 64.58 2018 143.367 33.68 66.32

Ramezani-Carr Intermodal Chassis Availability Page 82 Table 4.2A: Composition of High Value Product Exports (% of Total HPV) Period:1990-2017 Source: USDA, Economic Research Service https://www.ers.usda.gov/webdocs/DataFiles/50441/ fyhvpsumexp.xls?v=4130.4

High-value products Year Raw Semi-processed Processed 1990 25.28 32.86 41.86 1991 25.56 30.22 44.21 1992 23.70 29.56 46.75 1993 22.96 27.93 49.12 1994 22.60 27.31 50.09 1995 20.76 29.04 50.21 1996 21.02 26.91 52.07 1997 20.27 28.59 51.14 1998 20.59 27.76 51.65 1999 20.42 24.51 55.07 2000 21.24 24.07 54.69 2001 20.13 25.73 54.14 2002 21.11 25.87 53.02 2003 20.98 24.18 54.84 2004 23.12 24.27 52.61 2005 24.34 22.51 53.15 2006 23.47 22.83 53.70 2007 21.59 23.91 54.51 2008 20.41 25.86 53.73 2009 21.84 24.93 53.23 2010 21.08 26.18 52.74 2011 20.68 24.35 54.97 2012 21.13 24.81 54.06 2013 21.49 24.62 53.89 2014 21.31 23.53 55.15 2015 22.70 23.18 54.12 2016 23.05 21.46 55.49 2017 23.43 20.50 56.07

Ramezani-Carr Intermodal Chassis Availability Page 83 Table LA-1A: Port of Los Angeles Aggregate Container Movement Export (Outbound), Import (Inbound), and Net (Import-Export) Period: July 1995 to May 2020 (25 observations per month) Source: https://www.portoflosangeles.org/business/ statistics/container-statistics

Month Type Mean St. Dev. Min Max January Export 260,069 96,152 92,990 406,719 Import 294,844 105,705 111,494 445,731 Net 34,775 15,786 6,460 74,736 February Export 229,820 77,454 86,535 340,756 Import 252,148 87,648 99,368 392,683 Net 22,328 19,571 (8,218) 67,959 March Export 249,361 84,739 98,118 402,887 Import 264,279 87,533 96,906 439,209 Net 14,918 27,022 (30,181) 86,555 April Export 254,988 82,443 94,451 358,122 Import 295,519 91,375 111,203 381,517 Net 40,531 18,031 16,214 73,779 May Export 270,422 89,420 94,617 388,349 Import 310,039 99,329 114,514 440,313 Net 39,616 16,196 14,054 73,417 June Export 261,116 88,316 92,300 358,953 Import 305,004 96,076 114,467 405,824 Net 43,888 17,359 16,286 82,031 July Export 273,979 96,429 97,186 424,549 Import 322,226 104,660 125,411 487,605 Net 48,246 14,857 20,856 75,795 August Export 288,877 97,020 101,952 411,995 Import 332,323 104,686 122,866 449,086 Net 43,446 14,306 18,226 73,885 September Export 274,743 92,169 93,201 369,954 Import 324,899 102,583 115,473 431,310 Net 50,156 16,731 22,272 78,222 October Export 285,797 93,234 100,570 448,166 Import 327,448 101,001 121,523 504,388 Net 41,651 13,280 19,176 73,115 November Export 280,655 97,639 93,491 448,438 Import 308,580 103,062 104,880 475,788 Net 27,925 12,770 6,388 56,685 December Export 266,137 91,249 89,997 420,905 Import 290,565 96,661 103,821 482,353 Net 24,428 14,127 3,327 61,448 Monthly Export 266,111 90,430 86,535 448,438 (1995-2020) Import 302,012 99,590 96,906 504,388 Net 35,901 19,921 (30,181) 86,555

Ramezani-Carr Intermodal Chassis Availability Page 84 Table LA-2A: Port of Los Angeles Empty Container Volume Percent of Total TEU Exports and Total TEU Imports Period: July 1995 through May 2020 (25 observations per) Source: https://www.portoflosangeles.org/business/ statistics/container-statistics

Month Type Mean St. Dev. Min Max January Export 54 11 24 71 Import 4 3 1 14 February Export 48 10 26 66 Import 4 3 1 12 March Export 46 11 25 61 Import 05 3 1 15 April Export 50 10 29 64 Import 4 3 1 14 May Export 52 10 26 66 Import 4 3 0 10 June Export 53 11 26 67 Import 4 2 1 10 July Export 54 10 33 69 Import 4 3 1 9 August Export 56 10 31 70 Import 4 2 1 9 September Export 57 10 33 72 Import 3 2 1 9 October Export 55 10 33 70 Import 4 2 1 10 November Export 54 11 28 69 Import 4 3 1 13 December Export 53 11 22 67 Import 4 3 2 13 Monthly Export 53 11 22 72 Import 4 3 0 15

Ramezani-Carr Intermodal Chassis Availability Page 85 Table LA-3A: Port of Los Angeles, Containerized Agricultural Exports (TEU, Selected Commodities) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Edible Nuts Rice Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 479 100 296 607 112 98 1 284 February 599 209 334 1,021 158 190 6 565 March 692 280 374 1,217 169 183 11 518 April 567 209 312 925 128 114 12 398 May 532 171 281 851 62 58 7 161 June 547 164 297 768 54 51 8 181 July 498 162 222 751 86 89 5 270 August 669 240 319 1,075 105 116 6 400 September 785 259 449 1,157 58 65 7 228 October 1,170 464 609 1,990 79 52 11 196 November 1,280 452 695 1,901 119 86 4 257 December 829 261 517 1,346 118 102 4 262 Average 721 358 222 1,990 104 110 1 565 Tomatoes(Processed) Wine Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 123 102 19 301 71 49 6 144 February 146 104 29 353 82 38 19 136 March 163 74 36 300 89 51 16 170 April 130 80 18 236 104 50 52 191 May 170 105 27 391 90 52 44 209 June 182 102 37 364 73 40 20 131 July 119 60 29 204 80 55 18 174 August 157 72 44 255 71 46 31 149 September 169 101 60 397 82 46 26 157 October 153 107 47 391 83 36 40 130 November 160 70 65 302 92 54 27 180 December 156 89 58 321 91 56 29 191 Average 152 87 18 397 84 47 6 209

Ramezani-Carr Intermodal Chassis Availability Page 86 Table LB-1A: Port of Long Beach Aggregate Container Movement Export (Outbound), Import (Inbound), and Net (Import-Export) Period: July 1995 to May 2020 (25 observations per month) Source: https://www.polb.com/business/port- statistics/#latest-statistics

Month Type Mean St. Dev. Min Max January Export 214,649 67,199 107,260 328,599 Import 229,991 66,994 107,635 331,504 Net 15,342 12,266 (963) 43,472 February Export 204,304 59,817 110,655 314,936 Import 215,737 65,850 103,099 346,855 Net 11,433 18,995 (30,977) 47,756 March Export 219,946 58,052 109,380 309,059 Import 210,769 51,936 97,058 321,025 Net (9,177) 22,344 (43,198) 38,697 April Export 223,267 59,058 113,849 301,567 Import 242,563 60,461 113,082 326,555 Net 19,296 15,580 (9,085) 52,083 May Export 236,837 64,116 116,709 321,176 Import 257,887 70,335 116,630 366,251 Net 21,050 14,865 (7,116) 45,074 June Export 238,876 71,828 111,561 361,935 Import 260,941 70,155 116,137 390,254 Net 22,065 15,307 (4,003) 59,981 July Export 241,927 69,504 116,737 338,034 Import 268,181 66,060 130,686 384,152 Net 26,255 16,546 (12,085) 58,099 August Export 250,027 71,875 125,494 340,679 Import 272,779 68,078 132,209 362,973 Net 22,752 16,768 7,385) 52,598 September Export 238,748 71,145 123,772 345,215 Import 266,684 69,809 118,681 371,409 Net 27,937 15,916 (5,090) 59,226 October Export 244,875 69,821 129,817 346,090 Import 266,273 66,246 139,424 372,236 Net 21,398 16,141 (4,605) 49,186 November Export 239,208 62,434 122,545 317,902 Import 252,534 64,289 114,994 337,095 Net 13,326 14,249 (14,646) 34,258 December Export 239,831 68,769 124,968 361,434 Import 245,137 68,118 108,898 380,213 Net 5,306 13,431 (16,071) 37,887 Monthly Export 232,496 66,387 107,260 361,935 (1995-2020) Import 248,832 67,672 97,058 390,254 Net 16,336 18,787 (43,198) 59,981

Ramezani-Carr Intermodal Chassis Availability Page 87 Table LB-2A: Port of Long Beach Empty Container Volume Percent of Total TEU Exports and Total TEU Imports Period: July 1995 through May 2020 (25 observations per) Source: https://www.polb.com/business/port- statistics/#latest-statistics

Month Type Mean St. Dev. Min Max January Export 52 11 24 68 Import 2 1 0 4 February Export 47 11 18 63 Import 2 1 1 5 March Export 45 11 19 59 Import 2 1 1 4 April Export 48 11 20 62 Import 2 1 0 4 May Export 50 10 25 63 Import 2 1 0 3 June Export 52 11 25 65 Import 2 1 0 3 July Export 53 10 29 66 Import 2 1 0 3 August Export 54 10 32 67 Import 2 1 0 3 September Export 55 9 34 68 Import 2 1 1 3 October Export 54 10 30 69 Import 2 1 0 3 November Export 53 10 30 66 Import 2 1 1 5 December Export 52 11 25 69 Import 2 1 1 4 Monthly Export 51 11 18 69 1995-2020 Import 2 1 0 5

Ramezani-Carr Intermodal Chassis Availability Page 88 Table LB-3A: Port of Long Beach, Containerized Agricultural Exports (TEU, Selected Commodities) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Edible Nuts Rice Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 727 233 243 1,026 36 62 3 195 February 819 236 411 1,088 44 49 2 129 March 998 334 396 1,564 49 85 2 259 April 856 212 537 1,162 27 31 4 101 May 810 234 564 1,317 25 26 1 75 June 709 189 489 1,094 14 16 1 53 July 708 180 486 960 18 16 3 44 August 752 202 482 1,132 32 28 4 69 September 781 274 506 1,302 31 37 3 117 October 1,101 289 595 1,422 28 37 3 115 November 1,105 331 521 1,507 38 49 2 143 December 979 334 399 1,575 19 15 3 49 Average 862 284 243 1,575 30 41 1 259 Tomatoes(Processed) Wine Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 122 66 22 241 70 55 11 172 February 116 49 44 184 85 81 19 252 March 178 117 32 366 101 89 35 318 April 228 181 76 624 98 88 30 317 May 216 87 118 404 76 36 41 139 June 163 52 98 232 53 24 23 96 July 168 78 45 266 53 31 19 127 August 133 87 34 269 57 41 21 146 September 115 61 46 215 59 24 33 107 October 143 69 62 263 51 26 23 100 November 165 109 52 352 57 31 21 108 December 127 77 33 276 57 19 33 91 Average 156 95 22 624 68 52 11 318

Ramezani-Carr Intermodal Chassis Availability Page 89 Table O-1A: Port of Oakland Aggregate Container Movement Export (Outbound), Import (Inbound), and Net (Import-Export) Period: July 1997 to May 2020 (23 observations per month) Source: https: //www.oaklandseaport.com/performance/facts-figures/

Month Type Mean St. Dev. Min Max January Export 93,594 14,156 67,449 115,119 Import 77,027 17,840 46,267 103,984 Net (16,567) 8,473 (33,127) (2,072) February Export 87,921 12,756 64,599 103,577 Import 69,235 14,479 47,642 90,390 Net (18,686) 4,926 (29,757) (7,396) March Export 98,825 12,424 73,885 118,735 Import 77,758 13,847 55,727 102,842 Net (21,067) 5,611 (29,812) (3,723) April Export 97,472 11,691 75,123 115,649 Import 80,703 13,782 57,137 100,354 Net (16,769) 5,778 (27,989) (2,372) May Export 100,456 13,934 69,355 120,433 Import 83,796 15,113 54,576 104,138 Net (16,660) 6,856 (27,728) (3,493) June Export 100,834 13,338 71,435 116,591 Import 81,995 13,671 57,206 102,568 Net (18,839) 5,325 (27,655) (7,864) July Export 100,729 15,641 71,273 122,916 Import 83,739 15,448 54,036 105,511 Net (16,989) 6,043 (31,186) (7,170) August Export 107,470 16,123 71,025 131,540 Import 86,181 14,790 59,615 105,825 Net (21,290) 5,847 (35,084) (11,410) September Export 100,509 15,248 67,761 123,697 Import 81,269 14,381 58,507 100,846 Net (19,240) 5,280 (33,033) (9,194) October Export 103,251 15,412 65,557 121,693 Import 83,533 13,802 58,028 104,733 Net (19,718) 7,628 (34,858) 728 November Export 97,517 12,203 73,331 117,523 Import 81,597 13,450 57,441 101,602 Net (15,920) 5,961 (26,819) (5,703) December Export 97,143 12,570 71,652 114,214 Import 80,300 14,792 56,001 106,708 Net (16,843) 6,621 (30,753) (2,659) Monthly Export 98,803 14,369 64,599 131,540 (1997-2020) Import 80,589 14,977 46,267 106,708 Net (18,213) 6,400 (35,084) 728

Ramezani-Carr Intermodal Chassis Availability Page 90 Table O-2A: Port of Oakland Empty Container Volume Percent of Total TEU Exports and Total TEU Imports Period: July 1997 to May 2020 (23 observations per month) Source: https: //www.oaklandseaport.com/performance/facts-figures/

Month Type Mean St. Dev. Min Max January Export 26 6 16 35 Import 23 6 15 36 February Export 22 6 13 34 Import 24 6 15 35 March Export 21 6 13 33 Import 27 6 16 37 April Export 24 6 12 36 Import 24 6 17 35 May Export 26 7 13 39 Import 23 6 16 37 June Export 27 7 12 39 Import 21 6 14 36 July Export 27 8 7 41 Import 23 7 14 42 August Export 29 8 13 44 Import 24 8 15 43 September Export 28 8 9 39 Import 22 6 13 41 October Export 23 8 10 37 Import 25 6 17 38 November Export 22 7 11 37 Import 25 6 18 37 December Export 24 7 11 37 Import 25 7 15 43 Monthly Export 25 7 7 44 1997-2020 Import 24 6 13 43

Ramezani-Carr Intermodal Chassis Availability Page 91 Table O-3A: Port of Oakland, Containerized Agricultural Exports (TEU, Selected Commodities) Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Ocean/Port-Profiles-by-Commodity/hpfj- zhfg

Edible Nuts Rice Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 4,653 1,010 3,236 6,300 1,807 624 789 2,781 February 4,985 1,243 3,185 6,666 1,803 572 1,059 2,944 March 4,969 991 2,864 6,340 1,817 594 1,280 3,032 April 4,078 592 2,815 4,692 1,809 623 672 2,596 May 3,845 826 2,259 5,114 1,726 582 679 2,660 June 3,640 623 2,273 4,162 1,353 502 437 2,080 July 3,331 446 2,841 3,995 1,505 548 672 2,061 August 3,249 521 2,205 3,939 1,429 542 738 2,208 September 4,778 658 3,806 5,823 1,270 524 488 2,210 October 9,576 1,718 7,487 12,749 1,116 322 514 1,645 November 9,738 1,219 7,861 11,643 1,217 425 672 1,886 December 7,197 1,336 5,492 9,290 1,712 754 653 3,013 Average 5,336 2,386 2,205 12,749 1,547 588 437 3,032 Tomatoes(Processed) Wine Month Mean St. Dev. Min Max Mean St. Dev. Min Max January 1,113 422 425 1,661 1,714 380 982 2,140 February 1,233 450 467 1,982 2,077 476 1,431 2,778 March 1,270 391 688 1,825 2,193 455 1,467 2,893 April 1,210 488 633 2,329 2,137 391 1,443 2,621 May 1,250 480 580 1,962 2,345 346 1,638 2,702 June 1,143 293 683 1,628 2,203 593 1,302 2,913 July 1,037 345 444 1,548 2,026 487 1,166 2,481 August 1,013 350 375 1,522 2,149 412 1,347 2,602 September 1,097 289 447 1,514 2,097 434 1,270 2,724 October 1,196 355 517 1,808 2,057 417 1,402 2,586 November 1,099 267 595 1,529 1,789 395 1,240 2,336 December 1,227 325 624 1,686 1,670 335 1,116 2,178 Average 1,157 368 375 2,329 2,038 456 982 2,913

Ramezani-Carr Intermodal Chassis Availability Page 92 Ramezani-Carr

Table 6.1A: Number of Container Vessels by Size in TEUs Period: Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel-Fleet-Data/n3eq-jw8fg nemdlCassAvailability Chassis Intermodal

Vessel Type Vessel 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Size in TEU Small Feeder 100- 2,091 2,223 2,367 2,522 2,384 2,287 2,494 2,437 2,382 2,303 2,292 2,282 2,269 2,267 2,320 2,000 Large Feeder 2,000- 574 629 673 719 718 719 716 674 663 645 648 623 618 655 670 3,000 Classic Panamax 3,000- 572 646 711 792 852 912 929 950 930 909 904 836 908 908 900 &wide-beam 5,300 Small neo-Panamax 5,300- 386 484 565 651 701 771 846 888 955 1,006 1,076 1,070 940 930 925 10,000 Large neo-Panamax 10,000- 8 16 34 60 105 161 195 120 147 151 12,500 VLCV 10,000- 194 215 227 14,500 VLCV - Maxi neo- 12,500- 211 222 232 Panamax 14,500 VLCV - Neo post- 13,000- 42 65 83 27 44 57 Panamax 18,000 ULCV 18,000+ 14 34 46 65 92 115 Total Number of 3623 3982 4324 4700 4689 4749 5090 5110 5125 5113 5234 5167 5158 5265 5370 Vessels ae93 Page Annual Growth (%) 9.91 8.59 8.70 -0.23 1.28 7.18 0.39 0.29 -0.23 2.37 -1.28 -0.17 2.07 1.99 Ramezani-Carr

Table 6.2A: Capacity of Container Vessels (TEU, 1,000s) Period:Jan 2010 to Dec 2018 (9 observations per month) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel-Fleet-Data/n3eq-jw8fg nemdlCassAvailability Chassis Intermodal

Vessel Type Vessel 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Size in TEU Small Feeder 100- 1,997 2,148 2,325 2,520 2,462 2,384 2,548 2,491 2,433 2,386 2,384 2,383 2,369 2,361 2,412 2,000 Large Feeder 2,000- 1,432 1,582 1,697 1,820 1,822 1,824 1,818 1,714 1,683 1,638 1,639 1,576 1,566 1,665 1,708 3,000 Classic Panamax 3,000- 2,224 2,534 2,799 3,139 3,416 3,716 3,755 3,873 3,831 3,757 3,743 3,456 3,852 3,849 3,805 &wide-beam 5,300 Small neo-Panamax 5,300- 2,382 3,180 3,737 4,352 4,693 5,249 5,767 6,100 6,640 7,070 7,684 7,744 7,083 7,039 7,021 10,000 Large neo-Panamax 10,000- 105 189 397 753 1,329 2,046 2,524 1,281 1,577 1,629 12,500 VLCV 10,000- 2,395 2,633 2,755 14,500 VLCV - Maxineo- 12,500- 2,870 3,021 3,161 Panamax 14,500 VLCV - Neo post- 13,000- 611 961 1,227 447 707 924 Panamax 18,000 ULCV 18,000+ 257 633 862 1,246 1,793 2,294 Total TEUs (1,000) 8035 9444 10663 12020 12790 13926 15217 16224 17111 18114 19677 20003 20714 22012 22954 ae94 Page Annual Growth (%) 17.54 12.91 12.73 6.41 8.88 9.27 6.62 5.47 5.86 8.63 1.66 3.55 6.27 4.28 Table 6.3A: Capacity of Container Ships Calling on U.S. Ports (TEUs) Period: 2016 Source: U.S. Department of Transportation, Maritime Administration Based on U.S. Customs and Border Protection Entrance Data https://www.maritime.dot.gov/sites/marad.dot.gov/files/docs/outreach/ data-statistics/6756/containership-size-comparison-2015-2016-3.pdf

Port, State Maximum Capacity Average Capacity Number of Calls ANCHORAGE, AK 5,510 3,940 78 BALTIMORE, MD 9,400 5,534 381 BOSTON, MA 8,930 5,760 159 CHARLESTON, SC 10,700 5,791 1,377 CHARLOTTE AMALIE, VI 1,368 1,108 162 CHRISTIANSTED, VI 1,368 1,113 69 EVERETT, WA 2,546 2,303 34 FREEPORT, TX 2,602 2,198 107 GULFPORT, MS 2,602 1,244 130 HONOLULU, HI 3,820 2,109 96 HOUSTON, TX 6,732 4,132 935 JACKSONVILLE, FL 9,040 4,254 432 LONG BEACH, CA 17,859 6,498 927 LOS ANGELES, CA 17,859 6,473 1,169 MIAMI, FL 8,814 3,290 1,056 MOBILE, AL 6,572 4,695 222 NEW ORLEANS, LA 6,732 4,118 546 NEW YORK, NY 8,814 3,608 32 NEWARK, NJ 10,700 5,584 2,296 NORFOLK, VA 10,700 5,901 1,858 OAKLAND, CA 17,859 6,637 1,735 PHILADELPHIA, PA 9,403 3,160 585 PORT EVERGLADES, FL 6,732 2,017 1,633 PORT HUENEME, CA 2,546 1,977 70 PORT MANATEE, FL 2,490 783 66 PORTLAND, ME 724 710 21 PORTLAND, OR 2,118 2,118 12 SAN DIEGO, CA 1,740 1,411 82 SAN JUAN, PR 5,018 1,797 263 SAVANNAH, GA 10,700 5,656 1,992 SEATTLE, WA 17,859 6,761 293 TACOMA, WA 10,106 6,568 495 TAMPA, FL 3,426 2,868 57 WEST PALM BEACH, FL 1,147 720 234 WILMINGTON, DE 2,524 1,661 220 WILMINGTON, NC 8,452 2,821 292

Ramezani-Carr Intermodal Chassis Availability Page 95 Table 6.4A: Average Monthly Container Freight Rates ($) Origin: Port of LA or Chicago via LA-LB Destination: Port of Shanghai Period: Jan 2012 to April 2020 (8 monthly observations) Source: USDA, Agricultural Marketing Service https://agtransport.usda.gov/Container/Container-Vessel-Fleet- Data/n3eq-jw8f

20 Foot Container 40 Foot Container Month Port of LA Chicago via LA-LB Port of LA Chicago via LA-LB January 660.00 1338.75 812.22 1676.25 February 657.78 1412.50 807.78 1737.50 March 670.00 1306.67 818.89 1632.22 April 676.67 1441.43 830.00 1788.57 May 663.75 1358.75 825.00 1700.00 June 672.50 1478.33 832.50 1838.33 July 672.50 1391.25 826.25 1666.25 August 658.75 1476.00 812.50 1818.00 September 650.00 1398.75 796.25 1698.75 October 661.25 1472.00 802.50 1792.00 November 652.50 1388.75 795.00 1716.25 December 672.50 1455.00 810.00 1772.50 Average 664.10 1399.25 814.20 1724.88

Ramezani-Carr Intermodal Chassis Availability Page 96 10. Appendix B: U.S. Chassis Provisioning Models

As noted in section 6, following the Great Recession, ocean carriers began to heavily divest their ownership of chassis. They did so in order to focus on their primary shipping business, avoid chassis related regulatory constraints, and mitigate ﬂuctuations in shipping costs. This transition led to the development of several container chassis provisioning models in the U.S. As of mid-2011 when most carriers began the process that resulted in divestiture, there were approximately 670,000 marine chassis in North America registered with the Intermodal Association of North America’s (IANA) Global Intermodal Equipment Registry, 70% of which were provided by ocean carriers. By 2014, according to the IANA website, there were 640,000 registered chassis in operation, only 32% of which were owned by the ocean carriers. One-ﬁfth of the total chassis were in service in Southern California.34 Below we discuss several chassis provisioning models that emerged in recent decades, with particular emphasis on the ports considered in this report. While the graphics refer to “wheeled” and “grounded” container terminals, we note that size of wheeled container movements with these ports are small, mostly involving refrigerated container (reefers), with specializes chassis requirements.

10.1 Conventional Ocean Carrier Chassis Model

In this model, chassis are owned (or leased) and operated by the ocean carriers. They are also managed and maintained individually by the respective ocean carriers. This means that when a truck driver enters a port to pick up a container for ocean carrier X, he or she must also pick up and use a chassis from ocean carrier X.35

Ocean Carrier Chassis Model

Image Source: IANA Intermodal Factbook p. 15 (2018).

34 See Mitigating Urban Freight Through Effective Management of Truck Chassis, Thomas O’Brien, Tyler Reeb, and Annette Kunitsa (2016) https://dot.ca.gov/-/media/dot-media/programs/research-innovation-system- information/documents/f0017160-ca16-2813-finalreport.pdf. 35 IANA Intermodal Factbook (“IANA Factbook”), p. 15 (2018); Translogic Solutions-USC School of Public Policy Final Report (“Translogic Report”), Chassis Management at the San Pedro Bay Port Complex: Assessing the Viability of the ‘Pool of Pools’ Approach, p. 14 (April 27, 2015); and National Cooperative Freight Research Program Report 20 (“NCFRP Report”), Guidebook for Assessing Evolving International Container Chassis Supply Models, p. 25 (2012).

Ramezani-Carr Intermodal Chassis Availability Page 97 10.2 Regional Cooperative (Co-op) and Alliance Co-op Chassis Pool Model

In this model, chassis ﬂeets are shared between member contributors, who have the responsibility to manage or del- egate the management of the operation. The co-op pool requires joint decision making by the contributors. This is an important distinction because one of the principal challenges co-ops face is speed of decision making and action, as co-ops act on consensus and therefore need time for the democratic process. These pools resulted from the development of the ocean carrier alliances and terminal capacity challenges in the 2000s. The chief example of the co-op chassis pool model is CCM, which was started in 2005 to be the chassis pool operating company of the ocean carrier group OCEMA.36 The CCM pools (for example the South Atlantic Chassis Pool and others) are versions of a “Market” or “Open Choice” pool (described below). Under this arrangement, the pool management is not-for-proﬁt, but contributors compete for business within the grey pool, and truckers and BCOs are able to join the pool.

Co-op Chassis Model

Image Source: IANA Intermodal Factbook p. 15 (2018).

10.3 Neutral/Gray Chassis Pool Model

Under this model, chassis are provided and operated by a third party, which is responsible for assets, managing demand/supply imbalances, repositioning, maintenance and repair, and insurance. Chassis pools allow the drayage companies and “owner-operator” drayage service providers to avoid direct investments in chassis. Users (ocean carriers and motor carriers) are charged a per diem rental rate that includes a single daily rate for all of the preceding items, except repositioning. Users can either rent out chassis on a day-to-day basis for a fee (including maintenance and insurance) or choose a longer-term “triple-net lease” in which they are responsible for their own maintenance, insurance and taxes. These pools are usually domiciled at or near the terminals. Motor carriers who use neutral pool chassis may also use the equipment to move any carrier’s containers, which can lead to enhanced labor and equipment productivity due to time savings from the interchange process. Neutral pools were established by chassis leasing companies as a turnkey product for ocean carriers akin to the rental car business model. Neutral pools enable fast access to chassis to handle demand surges, and allow for quick off-hire when demand falls. Similar to co-op pools, they also usually offer multiple on-hire and drop-off points to allow for commercial ﬂexibility of freight ﬂows without having to physically reposition the chassis, though on a more limited basis.37

36 IANA Factbook, p. 15; Translogic Report, p. 15; NCFRP Report, pp. 25-26. 37 IANA Factbook p. 16 (2018); IANA Factbook, p. 15; Translogic Report, p. 17; NCFRP Report, pp. 26-27.

Ramezani-Carr Intermodal Chassis Availability Page 98 An example of this chassis supply model is the Pool of Pools serving the Ports of Los Angeles-Long Beach, where leasing companies established a neutral pools in order to quickly assist ocean carriers in handling demand surges.

Gray/Neutral Chassis Model

Image Source: IANA Intermodal Factbook p. 16 ( 2018).

10.4 Terminal Pool Chassis Model

Several marine terminals either require or offer their own chassis pools to better control the chassis operation as part of the entire terminal process, or as a commercial convenience for their customers. These terminal-operated pools may be either neutral (the terminal owns/operates) or co-op (the terminal manages on behalf of the steamship lines). The key differentiating factor is that the terminal operates, manages, and is the intermodal equipment provider (IEP) designation for U.S. Department of Transportation roadability regulation purposes. As an example, SSA, one of the largest U.S. marine terminal companies, operates a terminal-controlled chassis pool at the Port of Oakland (called the West Coast Chassis Pool – WCCP).38

Terminal Pool Chassis Model

Image Source: IANA Intermodal Factbook p. 16 ( 2018).

10.5 Motor Carrier Supplied Chassis Model

Here, chassis are owned (or long-term leased) and operated by motor carriers or logistics companies. When picking up a container at a terminal, the motor carrier or logistics company will arrive at the terminal gate with its own chassis. Once the container is loaded onto the chassis at the terminal site, the motor carrier will deliver the container and chassis to the receiver’s facility. Under this model the chassis normally stays hooked to the tractor/truck at all times during its

38 IANA Factbook p. 16 ( 2018); IANA Factbook, p. 15; Translogic Report, p. 18; NCFRP Report, pp. 27-28.

Ramezani-Carr Intermodal Chassis Availability Page 99 operation, the trucker stays with the container while it is loaded/unloaded, there is off-terminal parking of the chassis, and maintenance and repair is performed by the chassis owner.39

Motor Carrier Chassis Model

Image Source: IANA Intermodal Factbook p. 15 (2018).

10.6 Chassis Provider Independent Pool Model

Although some motor carriers are now accustomed to leasing chassis from a neutral or cooperative chassis pool, prior to 2009 motor carriers never had a commercial relationship with the ocean carriers that were exclusive to chassis. This situation began to change around 2009, when one chassis provider (DCLI) began operating chassis on behalf of Maersk and commenced the practice of directly charging motor carriers a rental fee for the use of its chassis. Soon thereafter, other chassis providers followed suit.40 Under this model, the chassis leasing company (IEPs such as Flexi-Van, TRAC, DCLI) rent chassis to truckers or BCOs on a daily, short term or long-term basis. They may even label the chassis organization and offering they operate under as a “pool”. For example, at the Port of Oakland (see Section 6.2.2), the three “pools” operates and controlled by major IEPs may imply that they are a neutral/grey or cooperative pool, but that is not the case. Inserting the word “pool” into the title is technically accurate because other chassis providers may, in fact, contribute a small number of their own chassis to said “pool”. However, in reality, it is not a neutral or cooperative pool, or a true pool in the intermodal sense. This is because the largest contributing chassis provider remains defacto and de jure in control of the “pool” (arrangement). Further, under the terms of these chassis leases, the motor carrier or BCO may (or may not) be responsible for chassis maintenance, repair, insurance and taxes and under this model the chassis provider often invoices the motor carrier or BCO directly for payment. The Port of Oakland is largely an example of this chassis supply model.

10.7 Market Pool

A market pool is one where various chassis providers contribute their chassis to a large ﬂeet, hiring a pool manager to run the pool according to speciﬁc guidelines set by the industry groups. The market pool differs from the Pool of Pools in three principal ways. First, the market pool chassis are marked uniformly and are managed by a third party under contract to a Pool Board that is made up of representatives from various chassis contributors and stakeholders.

39 IANA Factbook p. 15 (2018); IANA Factbook, p. 15; NCFRP Report, pp. 28-29. 40 See National Cooperative Freight Research Program (NCFRP Report 20), “Guidebook for Assessing Evolving International Container Chassis Supply Models”, pp. 29-30 (2012.

Ramezani-Carr Intermodal Chassis Availability Page 100 In the Pool of Pools, each separate leasing company clearly marks each piece of equipment as its own, and there is no single manager for the pool. Instead there is a representative from each of the leasing companies that together manage the pool. Second, the market pool is a completely separate venture of the leasing companies involved. The Pool of Pools consists of three separate and competing chassis leasing companies. Third, the market pool is a simpler venture than the Pool of Pools since the accounting is simpliﬁed and does not require each leasing company to maintain its own operating structure.41

10.8 Not-for-Proﬁt Chassis Pool Cooperative

The North American Chassis Pool Cooperative (NACPC) , a nonproﬁt organization, was formed in 2013 by 12 major motor carriers, and all members of the American Trucking Association (ATA). NACPC is a “gray pool,” where members contribute chassis and users can draw any chassis from the pool regardless of ownership. The contributory pool model thus eliminates duplicative costs and maximizes the use of limited space at port and or inland intermodal locations by obviating the need for a contributor to have its own chassis storage facility. It also ensures and adequate supply of chassis for all users. NACPC pools are managed – logistics, billing, inventory supply, maintenance and repair and the repositioning of the chassis – by the Consolidated Chassis Management (CCM), a pool management company. By pooling resources, NACPC is able to achieve important cost savings with respect to not only the acquisition and leasing of chassis but also on the requisite insurance costs and the costs of chassis modernization and refurbishing which are part of its strategic operations plans. Currently, NACPC does not operateon the West Coast.42

10.9 The Role of Chassis Manufacturing and Sales in Chassis Supply

There are a number U.S. based chassis manufacturers, including CIMC Intermodal Equipment, Cheetah Chassis, Em- poria, Pratt Industries, Pro-Haul, Chassis King, and Hercules Chassis. We found no evidence that shortage of newly manufactured chassis is a contributor to chassis shortages at American ports. For example, CIMC Intermodal Equip- ment (CIMC-IE), the U.S. arm of China International Marine Containers Group Ltd., which is the largest shipping equipment supplier in the world, recently increased its chassis manufacturing in the U.S.43 For years, CIMC-IE’s chassis units were completed in China and shipped directly to U.S. customers, while other models were assembled in the U.S. from kits shipped from China. In early 2020, the ground shifted: CIMC-IE underwent a name change to “CIE Manufacturing” and moved its container chassis production from China to the United States. This move was motivated

41 Mitigating Urban Freight Through Effective Management of Truck Chassis, Thomas O’Brien, Tyler Reeb, and Annette Kunitsa (2016) https://dot.ca.gov/-/media/dot-media/programs/research-innovation-system- information/documents/f0017160-ca16-2813-finalreport.pdf. 42 See https://www.nacpc.org/about/. 43 See Jim Vinosky, CIMC Brings Its Chassis Manufacturing To The U.S., Forbes (January 6, 2010) https://www.forbes.com/sites/jimvinoski/2020/01/06/cimc-brings-its-chassis- manufacturing-to-the-us/#455b032547b8.

Ramezani-Carr Intermodal Chassis Availability Page 101 by the U.S.-China trade war that started in 2018, when U.S. tariffs on imported Chinese made chassis started to kick in at 10%, and then quickly skyrocketed to 25%. At the 10% rate most of CIMC-IE’s customers absorbed the difference, but when the tariffs rose to 25%, the company started losing orders.44 CIE Manufacturing thus moved its China-based chassis production to facilities in South Gate, California and Emporia, Virginia, in order to avoid these tariffs and remain competitive. Its two U.S. factories were tooled up to handle the production of up to 100 chassis per shift. It also hired as many as 275 employees at its two locations. In an American Truckers Association’s (ATA) ﬁling with the U.S. Trade Representative requesting that the U.S. government remove these tariffs, the ATA disclosed that in 2018, the U.S. demand for new chassis ranged between 53,000 and 55,000 units. That same year, CIE Manufacturing’s predecessor (CIMC-IE) alone produced 45,441 chassis units and Hyundai Translead from Mexico supplying another 6,621 units. In early January 2020, CIE Manufacturing projected that its 2020 U.S. chassis production would exceed 60,000 units. The takeaway is that any shortfall in chassis supply does not appear to be driven by a inability of chassis manufacturers to produce and supply them. Rather, it is driven by the fact that the current economics of purchasing or long-term leasing of new chassis does not pencil out for many motor carriers and BCOs.

44 Deborah Lockride, CIMC Intermodal Business Renamed as it Adds U.S. Manufacturing Capabilities, Trucking Info (January 31, 2020), https://www.truckinginfo.com/350097/cimc-intermodal-business-renamed-as-it- adds-u-s-manufacturing-capabilities.

Ramezani-Carr Intermodal Chassis Availability Page 102 11. Additional References

In addition to references listed in the footnotes, we have also consulted the following articles and reports.

1. California Agricultural Exports (California Agricultural Statistics Review 2017-2018). 2. Intermodal Association of North America (IANA) Intermodal Factbook: An Introduction to Intermodal Freight Transportation (“IANA Factbook”) (2018). 3. Eric Jessup, Susan Galinato, Zhazira Alisheva, and J. Bradley Eustice, Pacific Northwest Container Availability Study – West Coast Container Traffic Analysis (report submitted to USDA, Agricultural Marketing Service) (2019). 4. National Cooperative Freight Research Program Report 20 (“NCFRP Report 1”), Guidebook for Assessing Evolv- ing International Container Chassis Supply Models (2012). 5. National Cooperative Freight Research Program Report 11 (“NCFRP Report 2”), Truck Drayage Productivity Guide (2011). 6. Bethany Stich, James Amdal, Ian Butler-Serverson, Dennis Thornton, and Peter Webb, White Paper on Interna- tional Chassis (University of New Orleans Transportation Institute) (2017). 7. Translogic Solutions-USC School of Public Policy Final Report (“Translogic Report”), Chassis Management at the San Pedro Bay Port Complex: Assessing the Viability of the ‘Pool of Pools’ Approach (April 27, 2015). 8. US Department of Transportation (Bureau of Transportation Statistics), Port Performance Freight Statistics Pro- gram - Report Submitted to Congress (2018). 9. USDA (Agricultural Marketing Service), Agricultural Export Transportation Handbook, by Ellen Welby and Brian McGregor (Revised: 2004). 10. USDA (Agricultural Marketing Service), Profiles of Top U.S. Agricultural Ports (Oakland, Los Angeles, Long Beach) (June 2019). 11. Robert C. Leachman and Payman Jula, Estimating flow times for containerized imports from Asia to the United States through the Western rail network, Transportation Research Part E (2011). 12. Samaneh Shiri and Nathan Huynh, Assessment of U.S. chassis supply models on drayage productivity and air emissions,Transportation Research Part D 61 (2018). 13. PORTS OF LONG BEACH/LOS ANGELES TRANSPORTATION STUDY, Meyer, Mohaddes Associates (2001). 14. Tim Vander Beek, Analysis and Optimization of Chassis Movements in Transportation Networks with Centralized Chassis Processing Facilities, PhD Dissertation, Claremont Graduate University and California State University Long Beach (2019). 15. Maged Dessouky, Santiago Carvajal, and Siyuan Yao, Congestion Reduction Through Efficient Empty Container Movement Under Stochastic Demand, A Research Report from the National Center for Sustainable Transportation (June 2020). 16. Theo Notteboom and Jean Paul Rodrigue, Containerisation, Box Logistics and Global Supply Chains: The Inte- gration of Ports and Liner Shipping Networks, Maritime Economics & Logistics (2008). 17. Jean Paul Rodrigue, The Geography of Transport Systems, Fifth Edition, London: Routledge (2020). 18. Qais A. Mahafzah and Mohammad Amin Naser, The Inadequacy of the Existing International Maritime Transport Regimes for Modern Container Transport, Modern Applied Science (2019).

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