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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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Suggested Citation:"Appendix M - Excel Worksheets." National Academies of Sciences, Engineering, and Medicine. 2017. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. Washington, DC: The National Academies Press. doi: 10.17226/24680.
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199 A p p e n d i x M Excel Worksheets

200 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments This file contains the following spreadsheet aids: Step 1: Define the Project Step 2: Determine Scope of the Analysis Step 3: Account for Project Costs Step 4: Identify Benefit Triggers and Metrics Step 5: Develop Forecasts Step 5_diversion modeling_new users Diversion Modeling (3 sheets) Step 5: Delay hours and reliability worksheets Step 6: First Order Benefit Metrics Step 7: Analyze Public Externalities Step 8: Higher Order Benefits Step 9: Conduct the BCA Step 9: Stakeholder Analysis Step 10: Decision Criteria and BCA Step 10: Reporting Table Step 11: Results of Sensitivity Testing, Monte Carlo Simulation and RDM use (3 sheets)Checklist of Assumptions Worksheets Accompanying- National Cooperative Freight Research Project 46 Texas A&M Transporation Institute, Rand Corporation & University of Washington, April 10, 2016.

Calculation of present value of future cash flows Updating Past Values Using an Inflation Factor Calculation of present value of past cash flows using indices: Base Year = 0 Real Discount Rate (Annual) Step 2 3.0% (xx.x%) Annual Interest Rate 2.0% (xx.x%) Index Value of Current Year 150 Year Future Amount Calculated Present Value Number of Prior Years Past Amount Calculated Present Value Prior Years Past Amount Index for Past Amount Year Calculated Present Value Total 382.86 Total 456.99 Total 476.02 00.001051001000.001001000.0010010 94.3964119128.2919190.790011 70.1904158234.8858262.490012 54.5923148341.9848315.190013 4 00.6952108495.68084 5 5 5 6 6 6 7 7 7 8 8 8 9 9 9 10 0101 11 1111 12 2121 13 3131 14 4141 15 5151 16 6161 17 7171 18 8181 19 9191 20 0202 21 1212 22 2222 23 3232 24 4242 25 5252 26 6262 27 7272 28 8282 29 9292 30 0303 31 1313 32 2323 33 3333 34 4343 BCA Conventional Calcuations: Exponential Discounting, Updating Input Values 35 5353 36 6363 37 7373 38 8383 39 9393 40 0404

202 Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor investments Category Status Por N/A Land and Property Purchase Right of way acquisition Opportunity cost of owned or donated land Leaseholds Air/mineral rights Easements Purchases Construction Costs (material, labor, & equipment) Rail: Tracks Sidings Electrification Systems Safety/Security Installations Air: Landing Systems RunwayTaxiway Facilities Table 1 Costs Checklist

excel Worksheets 203 Cargo Terminal Buidlings Access Development Port: Wharf Construction Berth Dredging Shed Construction Landside Access Safety/Security Installations Highway: Road Construction Access Development Safety/Security Installations Capital Costs Equipment Purchase Operating, Maintenance, and Administration Land Rents Staff Labor Note: Include only fixed costs of operations and maintainance and ensure they are corridor specific and can be related to the project. In certain cases, where there are fixed and variable components to operating and maintance costs, including "fixed" variable costs associated with an improvement is justified. These are costs that are not isolated for consideration on the benefit side. INCLUDE FIXED OPERATING COSTS ASSOCIATED WITH THE INVESTMENT. Example: costs of operating and maintaining toll collection systems on a roadway segments or communication systems for rail. Fixed costs of maintaining locks and damns for the sections analyzed. Equipment-Related Costs Material for Renovations and Repairs Utilities Planning/Engineering Plan Development Feasibility Studies

Table 2 Mode Data source Applicable Fixed Operating Costs to Be Examined in the Context of a Project Examples Availability Format Highway Prior Studies, Stakeholder inputs, Estimated Costs associated with toll collections on existing roadway Microsoft Excel formats for download Annual Rail Examine Schedule 410 Form R1 Surface Transportation Board (for Fixed operating costs and variable operating costs). Note- it is aggregate and applicable system wide. It's use must be adapted for the context. The schedule R1 includes fixed and varaible operating expenses. Available: Surface Transportation Board. Costs associated with ways and structures like signal and communications Note: Elements which can be considered "fixed" and justified on the costs side include: Certain components in Ways and Structures Costs associated with track or locomotive maintanenance (unless a precise estimate can be modeled due to changes in specfic factors occuring due to a rail project like grade changes or terrain etc.) Certain components in Repair & Maintenance Certain components in Locomotives Certain components in Frieght Cars and Other Equipment Certain components in Transportation Certain components in Adminsitration Certain components in other costs Waterw ays EPA USACE Guidance Marine Vessels USACE Guidance Air Large Form 41 (Cargo Carriers) and (Passenger Carriers) Schedules P-5.1, P-5.2, P-6 Available via Bureau of Transportation Statistics Direct downlaod from BTS Components of runway and pavement maintenance costs. Components of crew costs Hourly fixed costs and hourly variable operating costs Quaterly in most cases Frequency The following worksheets provide diversion estimation based on a hybrid approach: segmentation of markets by Origin‐Destination Pairs and the Use of Commodity Based Filters. This method can be used in conceptual analysis, when there are no other tools like statewide models with mode share and mode choice models encompassing modes in consideration. These methods are also all mostly suited for intermodal diversion and directed towards long haul movements. They are driven by literature search of applicable guidance documents and academic literature. These are most often observed for truck‐rail and rail‐truck diversions. They have not been documented for pipeline/waterway/marine contexts. These estimates should be vetted for feasibility analysis, preferably by industry experts and/or stakeholders. The Diversion Suite comprises 2 separate sheets. Step 4: Diversion 1 ‐ Segmentation and Step 4: Diversion 2 ‐ Cross Elas. The second worksheet contains the database of reported cross elasticities, for any user to recognize the range and variation.

Electrical Equipment and Appliances General Commodity Group Cross-Price Elasticities Ra il t oT ru ck (F rei dla nd er 19 80 ) Tr uc k t o R ail (F rei dla nd er 19 80 )) Ra il t oT ru ck (A bd elw ah b, 19 98 ) Tr uc k t o R ail (A bd elw ah ab , 19 98 )-S ho rt ru n Int erp ret ati on NA IC S Co mm od ity C ate go ry ST CG co de (F AF ) Ra il-T ru ck (M cC ull ou g, 2 01 3) Tr uc k-R ail (M cC ull ou gh , 2 01 3) Food Products -0.023 0.004 1.4888 1.2612 Positive substition opportunities between truck/rail and rail/truck based on Abdelwahab. 111 Agricultural Prod 2,3 1.234 0.839 Wood and Wood Products -0.05 -0.129 1.293 1.1125 same as above 112 Livestock 1 1.341 0.806 Paper, Plastic and Rubber Products 0.007 0.003 1.2592 1.2812 same as above 311 Food Mnfg. 6,7 1.587 0.872 Stone, Clay and Glass Products 0.025 0.016 0.9525 0.9818 same as above 312 Beverages and Tobacco 8,9 3.091 1.357 Iron and Steel Products -0.053 -0.013 NA NA 317 Textiles and Apparal 30 NA NA Fabricated Metal Products -0.059 -0.099 0.9042 0.9326 same as above 321 Wood Product Manufacturing 26 NA NA Non Electrical Machinery -0.032 -0.01 NA NA 322 Paper Mnfg. 27,28 0.805 0.902 Electrical Machinery -0.151 -0.061 1.1672 1.1991 same as above 323 Printing and Related Activities 29 NA NA Chemical NA NA 1.0421 1.0786 same as above 324 Petroleum and Coal Products 17-19 0.69 0.736 325 Chemical Manufacturing 21-23 0.388 0.473Main Sources 326 Plastic and Rubber Products 24 1.541 1.038 327 Nonmetallic Mineral Products 31 1.56 1.073 331 Primary Metal Manufacturing 32 1.043 0.928 332 Fabricated Metal Manufacturing 33 1.255 0.819 333 Machinery Manufacturing 34 1.117 0.723 334 Computers and Electronic Products 35 0.56 0.419 335 38 NA NA 336 Transportation Equipment 36 NA NA 337 Furniture and Related Product 39 NA NA 339 Miscellaneous Manufacturing 40 NA NA Abdelwahab, Walid. “Elasticities of Mode Choice Probabilities and Market Elasticities of Demand: Evidence from a Simultaneous Mode Choice/Shipment-Size Freight Transport Model.” Transportation Research- Part E: Logistics and Transportation Review, 34(4), 1998. 257-66. McCullough, Gerard. Long-Run Diversion Effects of Changes in Truck Size and Weight (TS&W) Restrictions: An Update of the 1980 Friedlaender Spady Analysis. Dept. Of Appied Economics. Working Paper, Univeristy of Minnesota, 2013. Friedlaender, Ann F. and Richard H. Spady. (1980). “A Derived Demand Function fo Freight Transportation.” The Review of Economics and Statistics, 62(3), 432-41. Note 1: 1. Establish % of cost reduction. Cost reductions can be estimated as either constant for all commodities or variable. In principle, costs vary by commodity as logistical costs vary. 2. Utilize elasticities (Columns by L and M by commodity code) to bound upper end of possible diversion (truck to rail or rail to truck based on context). 3. Update database with truck-water estimates and pipeline related measures many of which do not currently exist. Stakeholder inputs are important in such cases as are thumb rules. Source 4 Summary of S Clark. C., H. Naughton., B. Proulx, P. Thoma. A Survey of the Freight Transportation Demand Literature and a Comparison of Elasticity Estiamtes. IWR Report 05-NETS-R-0, 2005. www.corpsnets.us

1. Segment Analysis by Origin-Destination Pair 2. Then Segment Data b 3. Examine Cross Elast and Column G (this worksheet) to identify Divertible Flows (in the light of base movements Columns E,F) W/o NEW OR DIVERTED USERS-INDUCED DEMAND (HALF THE BENEFIT) Thumb Rules, Segmentation by Commodity Methods Based on Typical Base Freight Flow Patterns (Corridor) Sta nd ar d Co mm od ity Co de (ST CG ) F AF , C FS Co mm od ity De scr ipt ion Ty pic al Se rv ice Cla ss Po ten tia l S afe ty or Se cu rit y B en efi t As so cia tio ns of Se rv ice Cl as s/ BC A Pe rce nt ag e Mo ve me nt by Ra il Pe rce nt ag e Mo ve me nt by Tr uc k Di ve rsi on Po ten tia l Tr uc k t o R ail ( % of tru ck to nn ag e co nv er ted to eq uiv ale nt ra il ton na ge ) Ba se pe rio d (m illi on to ns ) R ail w/ o p ro jec t Fo re ca st Ra il ton na ge w /o pr oje ct Ba se pe rio d + t ( i) 1 Live Animals and Fish 0% High Zero xx xxx2 Cereal Grain (including seed) Unit Trains Truck con�lict/Grade Separations 50-60% 0-10% Signi�icant 40%3 Agricultural Products Except for Animal Feed Unit Trains 20-30% 40-50% Large 80% 4 Animal Feed and Products of Animal Unit Trains 30% 50-60% Large 80%5 Meat, Fish, and Seafood and Their Intermodal Truck reductions 0-5% >90% Small 20%6 Milled Grain Products and Preparations, and Carload Hazmat safety 20-30% 60-70% Signi�icant 40%7 Other Prepared Food Stuffs, and Fats and Oils 20-30% 60-70% Signi�icant 40%8 Alcoholic Beverages 20-30% 60-70% Signi�icant 40%9 Tobacco Products 0-5% 60-70% Zero10 Monumental or Building Stone 0-5% >90% Zero %04 tnacifingiS%08-06%03-02sdnaS larutaN1112 Gravel and Crushed Stone 20-30% 40-50% Large 80%13 Other Non-Metallic Minerals 40-50% 40-50% Large 80%14 Metallic Ores and Concentrates 20-30% 0-10% Small 20%%02 llamS%5-0%09-08laoC51 %02 llamS%5-0%09-08liO muelorteP edurC6117 Gasoline and Aviation Turbine Fuel 30-40% 30-40% Small 20% %04 tnacifingiS%53%01-5sliO leuF81 BCA With project (Subject to Rail Capacity Availability at the State: Unit Trains ) Ad jus ted Fl ow s Ba se pe rio d F low s (to ns ) ( bu ild alt er na tiv e) Ad jus ted Fl ow s w ith alt er na tiv e B as e pe rio d + t( i) Ad jus ted Fl ow s w ith alt er na tiv e B as e pe rio d + (t (I +1 )) Ad jus ted Fl ow s w ith alt er na tiv e B as e pe rio d + (t (i+ n) ) yy yyy= forecasted corridor rail tonnage (xxx) + adjusted % 19 Other Coal and Petroleum Products 30-40% 20-30% Large 80%%08 egraL%03-02%05-04daolraCslacimehC cisaB0221 Pharmaceutical Products 0-5% 60-70% Zero %08 egraL%05-04%05-04srezilitreF2223 Other Chemical Products and Preparations 10-15% 80-90% Small 20%

%04 tnacifingiS%07-06%04-03rebbuR dna scitsalP4225 Logs and Other Wood in the Rough 10-15% 80-90% Small 20%%08 egraL%06-05%05-04daolraCstcudorP dooW6227 Pulp, Newsprint, Paper, and Paperboard %08 egraL%06-05%05-04ladomretnI ,daolraC28 Paper or Paperboard Articles 0-5% 80-90% Small 20%oreZ%08-07%5-0stcudorP detnirP9230 Textiles, Leather, and Articles of Textiles or Leather . 0-1% 70-80% Small 20%31 Non-Metallic Mineral Products 10-20% 70-80% Small 20%32 Base Metal in Primary or Semi-Finished Forms and in Finished Basic Shapes 20-30% 60-70% Signi�icant 40% %02 llamS%58-57%02-01lateM esaB fo selcitrA33 %02 llamS%09-08%5-0yrenihcaM4335 Electronic and Other Electrical Equipment and Components, and Of�ice Equipment 0-5% 70-80% Small 20% 36 Motorized and Other Vehicles (including parts) 20-30% 60-70% Signi�icant 40%37 Transportation Equipment 0-5% 40-50% Zero38 Precision Instruments and Apparatus 0-5% 70-80% Zero39 Furniture, Mattresses and Mattress Supports, Lamps, Lighting Fittings, and Illuminated Signs 0-5% 90-95% Small 20% 40 Miscellaneous Manufactured Products 0-5% 70-80% Small 20%41 Waste and Scrap (except of agriculture or food). 30-40% 30-40% Large 80%%02 llamS%09-08%5-0thgierF dexiM34 Columns 2-4: Developed from Commodity Flow Survey Data 2002 by Bryan et al (2006) Source: Bryan, J., G. Weisbrod., and C. Martland. Guidebook for Assessing Rail Freight Solutions to Roadway Congestion. NCHRP Project 8-42, Task 11 Product, Transportation Research Board, Washington Note 1: Estimate diversion effects from truck volumes diverted subject to sensitivity analysis. Note 2: Convert truck tonnage to equivalent rail tonnage Note 3: Truck to Rail/Rail-Truck: Compare key long haul corridors. Ajdust percentages based on competitive conditions i.e., if rail service is categorized by more than one carrier, then adjus Note 4: This is back of the envelope type of approach. It requires transparaency in data and parameters used. Note 5: Public domain data like FAF can be improved by the use of private domain data. Truck freight data can be improved by access to state level model data. , DC. 2006. t rail share accordingly.

INPUTS for Conceptual BCA 1. Freight Flow O-D tables for the corridor by mode, by commodity (weight- tons) and (O-D pair): Example - A "To" Mode a (example, rail) and and a "From" mode b (example, truck): Work with one O-D pair at a time. Consider directionaly. So, movements from CA-NY is one O-D pair while, NY-CA is another. The O-D paris can vary in granularity based on data sources. FAF will allow state level anlaysis. Waybill will allow analysis at the level of the Bureau of Economic Analysis Zones. 2. Column G % adjustments (based on existing movements Columns E, F) 3. Capacity limits on corridors, terminals to determine if forecasted �lows can be accomodated. ASSUMPTIONS and STEPS in USING INDUCED DEMAND AND RULE OF HALF (CONSUMER SURPLUS) AACCRUES to SHIPPERS and INDUSTRY 1. Assume a time period (t+x) over which the phasing in of diversion occurs after completion. Adjust columns I onwards. 2. Apply �ilters. Recognize that Column H can also be re�ined by suitable cross elasticity estimates. The percent change in transport cost in the target mode is needed (in this case, change in rail costs). A 10% reduction in rail costs can at most induce a 7% increase in rail demand for NAICS 324 (Petroleum and Coal). The cost reductions and implied generations should be examined closely along with column H entries. In this case, they are very 3. Use estimated net forecasted new demand (induced/generated) in a rule of half user bene�it assessment (yyy-xxx) ("to" mode unit (tons). Match unit of forcast to suitable cost measures for valuation. 4. Value or monetize the new demand using the change in modal rates from shiftting from truck to rail, (ie. Truck rate - Rail rate ) per ton. 5. Convert trucks diverted using a tons per truck estimate 6. Use trucks diverted in Step 6 to estimate public bene�its from diverted demand. INPUTS for Feasibility and Investment Grade Analysis 1. Freight Flow O-D tables for the corridor by mode, by commodity (weight- tons) and (O-D pair): Example - A "To" Mode a (example, rail) and and a "From" mode b (example, truck): Work with one O-D pair at a time. Consider directionaly. So, movements from CA-NY is one O-D pair while, NY-CA is another. The O-D paris can vary in granularity based on data sources. FAF will allow state level anlaysis. Waybill will allow analysis at 2. Column G % adjustments based on stakeholder vetted inputs. 3. Same as conceptual. ASSUMPTIONS and STEPS in USING INDUCED DEMAND AND RULE OF HALF (CONSUMER SURPLUS) AACCRUES to SHIPPERS and INDUSTRY 1. Same as conceptual. 2. Modal choice models based on revealed preference data for existing modes. Stated preference mode choice for new modes. These can be logit based models. The actual type of logit model will depend on the context, 4. Same as conceptual. 5. Same as conceptual. 6. Same as conceptual. 7. Same as conceptual.

Step 6 Notes: Not all speed columns must be entered. Be sure all speeds are either mph or kph. Length must correspond (miles or km) Threshold Speed (mph or kph)) 50 Percent Through Heavy Trucks 40.0% Result: Delay Hours per Day 0.0600 Multiply this by appropriate costs per hour by category of cost. 1:00 AM 2:00 AM 3:00 AM 4:00 AM 5:00 AM 6:00 AM 7:00 AM 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 8:00 PM 9:00 PM 10:00 PM 11:00 PM 12:00 AM Segment Length Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed Speed 1 5 20 2 2 50 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Row 14 contains the sum of the calculations for each time of day RELIABILITY BENEFITS Truck Freight Other Modes Truck Freight Reliability in Corridor BCA- O-D pair Freight Reliability BCA (Rail,Ports and Waterways) When to Include If volume to capacity ratios exceed specific thresholds Departures from Specfied Arrival Schedules If a large percentage of volumes is truck freight- typically higher than 12% Percent of cargo flows that rely on ontime arrival 5 sampleAdditional Time per Mile (minutes)_Build Alternative 2 sampleCorridor Length (miles) 60 sampleExisting Users 200 sample Need external models to develop this forecast.New and Generated Users 50 sample These must be full O-D or through users.Average Volume 125 sampleValue of time (trucks) Base Period (per hour) $25 sample Include mode speci�ic values hereReliability Ratio 1.6 sample Include mode specifc ratios, if available here. Use suitable values. Typical range is from 0.8 to 2.0 for truck freight.Alternatively, for other modes- Value of time and Reliability ratio can be replaced by an hourly cost estimate re�lecting the cargo. Reliability Value Base Period ($ per hour) $15,000 Sample Worksheet Year Reliability Estimate_No Build Reliability Estimate_DExisting Users New Users Average Volume Value of Time Reliability Ratio Corridor Lenth (mReliability Benefits ($) 0 5 2 200 50 125 $25 1.6 60 $15,000 Benefit 1 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 2 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 3 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 4 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 5 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 6 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 7 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 8 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 9 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 10 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 11 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 12 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 13 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 14 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 15 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 16 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 17 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 18 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 19 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 20 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 21 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 22 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 23 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 24 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 25 enter forecast value enter forecast value enter forecast valenter forecast valenter forecast value 1.6 60 Total $15,000 Note: Annualize for the periods, times of day in consideration using suitable assumptions on freight travel. Delay Hours (Truck Freight) Additional Time per Mile (minutes)_No Build Alternative Include the percentile (95th or 90th) time here for the base period build scenario at an acceptable speed. External methods discussed in the Guidebook will be needed to develop this estimate. This measure is a plan time measure based on 95th or 90th percentile travel time distributionInclude the percentile (95th or 90th) time here for the base period at an acceptable speed. External methods discussed in the Guidebook will be needed to develop this do-minimum estimate. Same as earlier case

-$ -$ -$ -$ -$ -$ Step 9 Table 1 Highway Rail Water1 NPV TEE metrics--non-business users (less travel costs), if applicable Non-business users, if applicable 2 NPV TEE metrics--business users(less travel costs) Shippers, Carriers, Operators Shippers, Carriers, Operators 3 NPV TEE metrics--asset providers4 NPV tax-related costs, if applicable5 NPV asset provider effects--asset maintenance cost 6 NPV safety7 NPV environmental bene�its, including CO2 8 NPV asset provider--revenues (include, if applicable)9 NPV residual values Input Bene�it Values for Concerned Modes BCA Reporting Table Quanti�iable Metrics (Existing Users and New Users) Revenue Increases Residual Values Optional Bene�its TEE Metrics Tax-Related Cost Reductions Asset Maintenance Cost Reductions Externalities $ Value (Constant Dollars)Item Bene�it Category 10 NPV reliability11 NPV wider bene�its, as applicable12 NPV of costs (including subsidies and net of right-of-way contributions) -9-1 seniL )lanoitpo ssel( stifeneb VPN31 $ -$ -$ 14 NPV with additional bene�its Lines 1-9, 10, 11 as applicable -$ -$ -$ 15 BCR (1) Line13/Line 12 -$ -$ -$ 16 BCR (2) Line 13/Line 12 -$ -$ -$ 17 Net Present Value of the Project (1) Line 13 minus Line 12 -$ -$ -$ 18 Net Present Value of the Project (2) Line 14 minus Line 12 -$ -$ -$ Note: Present uncertainty in bene�its by use of ranges, con�idence intervals, distributions. Cost of Project Computations Pipeline Total Consumer Surplus Shippers, Carriers, Operators Producer Surplus Can be expanded to include noise, health effects, as applicable. Must use with care. Still needs additional research and improvements. Business users, if applicable

Table 2 Bene�its Q1 * (Change in costs build -nobuild) Q1 is a measure of activity Use Rule of Half in conceptual analysis Use Logsums if modes choice models can be calibrated or are part of travel models - integrated, activity or other type. Take stock of scale of the problem, the potential for new demand, and then the nature and type of models that are currently in use for the state and region and thier ability to model that new demand before considering logsums.Change in costs refer to change in generalized costs. Generalized costs include time, distance, access costs, if any, user fees or tolls). .5(Q1+Q2) *(Change in costs build-nobuild). Change in costs refer to change in generalized costs. Generalized costs include time, distance, access costs, if any, user fees or tolls). New Users Include Diverted (and Generated) UsersExisting Users

Sample Checklist of Assumptions for Any level of Analysis Checklist Criteria Breakdown/Comments Checklist Criteria Breakdown Costs Project Costs 1. Year of Each Estimate 2. Updating Assumptions 3. Base year for all costs 4. Contingency parameters or percentages by category 5. Phasing assumptions 6. Construction length Alternatives 1. Descritpion of alternatives 2. Description of timing , if considered. 3. Description of service lives considered. Markets or O-D pairs served 1. Description and breakdown of O-D pairs. O-D pairs for analysis and consideration Analysis Period 1. Analysis period and justi„ication 2. Effect of service lives in relation to analysis period. BCA Area 1. Corresponds to travel model area 2. Custom- Selected key networks (by functional heirarchy) for a corridor model 3. Custom- driven by zones of available freight data. Volumes 1. Volume related assumptions Source of forecasts, models, data and assumptions for all pertinent modes. Assumptions in demand model assignments, if used. Assumptions in use of data as obtained. Assumptions in forecasts, if developed from models Mode choice or share equations, if used Assumptions in capturing multimodal dimensions. Truck/Passenger/Rail/Waterway/ interactions, if any Assumptions in approximating new sers Assumptions in approximating diverted users. User costs,fees 1. Type 2. Assumptions Impedances 2. Type of impedance used Time Source of forecast, assumptions. Distance Source of data. Network distance or other. Speeds Type of tools used for the modes and context. Simulation tools, travel models or other sketch plan methods of approximation. For all Bene its and Modes 1. Valuation method Bene„it type and parameter Models and methods used. 2. Valuation parameters Source of data- surveys, empirical assessment, rev 3. Valuation components 4. Assumptions in use of the parameters. 5. Proxies used, if any Table 1 6. Urban/rural differences, in values if any. 7. Factors, Rates by category Operating Costs 1. Method of approximation Relying on distances or times 2. Components included Relying on individual activity measures Sources, tools, equations, models Units Shipping costs and/or rates, if 1. Data sources and applicability Stakeholder Analysis 1. Assumptions used in apportioning and level of analysis 2. Data sources used in apportioning. 3. Weights used, if any. 4. Differentiation in valuation parameters, if any. Justi„ication Discounting 1. Discount rates by concerned agency 2. Discouting period 3. Discouting method 4. If speci„ic bene„its are discouted differently than others. Assumptions. Exogenous factor/Endogenous/Approximation Exogenouos/Approximation Model based, Exogenous, Methous, Endogenously determined Methods used. Exogenous factor/Endogenous Exogenous factor/Endogenous/Approximation Exogenous factor/Endogenous/Approximation Exogenous factor/Endogenous/Approximation

Step 11 Table 1 of 4 Key Parameter Distribution Trial Number NPV (in 2016 US $, millions) Project Cost Estimate (in 2016 US $, millions) … Key Output Average Sample Population growth rate (%) Normal(0.67,0.5) Sample 1 104.6 129.0 Sample NPV (in 2016 US $, millions) 53.49 Sample Construction material costs (2016 US $, millions) Lognormal(13.25,5.0) Sample 2 37.2 126.4 Sample Project cost estimate (in 2016 US $, millions) 138.43 Sample Property acquisition costs (2016 US $, millions) Lognormal(14.65,8.25) Sample 3 15.8 142.1 Sample … … Sample 4 54.4 142.4 Sample 5 -12.2 157.0 Sample 6 -19.3 144.1 Sample 7 -32.9 157.0 Sample Sample 8 117.4 147.3 Bin Frequency Sample 9 96.9 145.2 -60 to -30 1 Sample 10 30.9 121.2 Sample -30 to 20 Sample 11 134.5 140.9 Sample 0 to 30 2 Sample 12 67.1 120.8 Sample 30 to 60 3 Sample 13 21.7 124.0 Sample 60 to 90 1 Sample 14 132.8 140.7 Sample 90 to 120 3 … Sample 120 to 150 2 Sample Monte Carlo Simulation: Assumptions and Displaying Results (Sample) Uncertain Parameters Simulation Results Distribution of NPV Median Min 1st Quartile 3rd Quartile Max … 45.80 -32.90 17.28 102.68 134.50 141.55 120.78 127.02 144.94 157.00 Table 2 Summary Statistics 0 0.5 1 1.5 2 2.5 3 3.5 -60 to -30 -30 to 0 0 to 30 30 to 60 60 to 90 90 to 120 120 to 150 F r e q u e n c y NPV (in 2016 US $, millions) Histogram of NPV Results

Step 11 Source of Uncertainty (Source Factor or Variable) Use Within BCA Nominal Value Rationale Document Source Factors' Type of Uncertainty for the Project Sample Population growth rate (assumed) Travel demand model 0.67 % per year Historical avg for area, 1980- 2010, based on Census data Aleatory uncertainty Sample Accident costs Benefits calculations - externalities see table in model National Safety Council (2010) Epistemic uncertainty Sample Value of freight travel time savings Benefits calculations - travel times see table in model USDOT VOT Guidnace 2014 Epistemic uncertainty Sample Value of travel time reliability for freight Benefits calculations - travel times 0, not considered/value if included No agreed upon valuation/Research Epistemic uncertainty Sample Induced demand Travel demand model forecasts none, not considered Variations in Travel Demand Models and Ability to Capture Induced Demand Deep uncertainty Sample General Commodity Group Cross-Price Elasticities Diversion model see table in model Research papers cited in model documentation Epistemic uncertainty Sample Mode shift model Travel demand model Multinomial logit model Most commonly used model Deep uncertainty Sample Impedance function Travel demand model trip length, in minutes Most commonly used model Deep uncertainty Sample Travel times (assumed) Travel demand model see table in model GPS-based survey Epistemic uncertainty Sample Operating costs, freight compaBenefits calculations - impacts to freight company see formulation in model Research papers cited in model documentation Epistemic uncertainty … Sample Construction material costs Project cost estimation 13.25 (in 2016 US$, millions) Engineer's notes Epistemic uncertainty (current), Aleatory uncertainty (future) Sample Property acquisition costs Project cost estimation 14.65 (in 2016 US $, millions) Engineer's notes Epistemic uncertainty Sample Results of any contract renogiations Project cost estimation Implicit assumption of no contract renogiation Aleatory uncertainty … Sample Discount rate Benefits calculations - final aggregation of results; Maintenance cost calculations 7 % OMB Circular A-94 Deep uncertainty Cost-Side Other Sources Table 1 Identification of Sources of Uncertainty Benefit-Side yp y Document Source Factor's Nature: Policy (Endogenous) or Exogenous. Natural variability that cannot be ignored or reduced is aleatory uncertainty. Exogenous factor Epistemic uncertainty can be reduced via data collection, meta analysis in lieu of simple updating parameters and values. For example, uncertainty regarding the value of freight travel time reliability for freight can be reduced via survey data and accompanying research. Conceptual study- Can be considered exogenous. More advanced studies (feasibility and investment grade): Determined as part of the study Parameters listed as sources of deep uncertainty cannot be assumed to be random variables with known probability distributions. Conceptual study- Can be considered exogenous. More advanced studies (feasibility and investment grade): Determined as part of the study. Further information is provided in our Guidebook and Report documents. Conceptual study- Can be considered exogenous. More advanced studies (feasibility and investment grade): Determined as part of the study. Note on Population Growth Rate and Travel Times: Exogenous factor Certain parameters like population growth rate and travel times are sometimes an input to analysis and sometimes an intermediate output of an analysis. Exogenous factor/Endogenous A four-step travel demand model may take population and land use as a given, where an integrated model may estimate the population growth rate. Exogenous factor/Endogenous Assumed population growth rates and travel times would be sources of uncertainty, to be listed in a table like this. Exogenous factor/Endogenous Derived population growth rates and travel times would also be uncertain, but the sources of uncertainty would be the assumptions and parameters used to derive these data. Exogenous factor/Endogenous Note on Valuation Methods: Accident costs and some other model parameters can be considered exogenous factors or policy variables, depending on context. Exogenous factor The actual costs of accidents are not set by public policy, but the costs assumed within a BCA can be set by public policy Exogenous factor Exogenous factor Policy variable

Step 11 Key Parameter Use Within BCA Key Outputs Related to Parameter Low Value Considered High Value Considered Value of Key Output @ Lower Limit Value of Key Output @ Upper Limit Observations/Notes Sample Population growth rate Travel demand model; Commodity flow model Overall project benefits 0.5% per annum 1.5% per annum 178.4 (in 2016 US$, millions) 202.7 (in 2016 US$, millions) Parameter is related to many other important outputs. Sample Construction material costs Project cost estimation Project construction cost 9.275 (in 2016 US $, millions, nominal value less 30%) 17.225 (in 2016 US $, millions, nominal value plus 30%) 132.05 (in 2016 US$, millions) 147.95 (in 2016 US$, millions) - Sample Discount Rate Benefits calculations - final aggregation of results; Maintenance cost calculations Overall project benefits 1% 7% 224.2 (in 2016 US$, millions) 165.2 (in 2016 US$, millins) Discount rate is an ideal parameter to study via sensitivity analysis. … Key Parameters Considered Key Outputs Related to Parameters Value of Key Outputs Value of NPV in 2016 US $, millions) Sample Construction material costs, construction labor costs, property acquisition costs Project cost estimate 174.4 (in 2016 US$, millions) 12.8 Sample Emissions rates With project reduction in NOx emissions 1.6 (in tons per year) 30.2 Sample All parameters All outputs -- 12.7 … Results of Sensitivity Testing Results of Purposefully Pessimistic Scenarios

Step 11. Discount Rate Length of Analysis Period Induced Demand, Scenario … NPV (in 2016 US $, millions) (average) NPV (in 2016 US $, millions) (SD) With project reduction in NOx emissions (tons per year) (average) With project reduction in NOx emissions (tons per year) (SD) .. Sample 7% 30 years No Induced Demand 46.2 22.4 1.6 0.4 Sample 5% 30 years No Induced Demand 53.2 22.1 1.6 0.4 Sample 3% 30 years No Induced Demand 61.6 21.4 1.6 0.4 Sample 1% 30 years No Induced Demand 72.8 20.7 1.6 0.4 Sample 7% 20 years No Induced Demand 36.4 23.1 1.3 0.4 Sample 5% 20 years No Induced Demand 43.4 22.2 1.4 0.4 Sample 3% 20 years No Induced Demand 47.1 21.7 1.4 0.4 Sample 1% 20 years No Induced Demand 48.5 21.4 1.4 0.4 … Sample Chart Stakeholder Comments Sample State DOT Most interested in results where discount rate is set to 7%, as this is the value used in internal discussions at this organization. Project appears promising, although the scenario where the NPV is less than 40 is worrying. Sample Environmental NGO Concerned about scenarios where reduction in NOx emissions is less than 1.4. … Results of Robust Decision-Making Study Deeply Uncertain stluseRsretemaraP Initial Feedback on First RDM Results 7% discount rate, 20 year analysis, no inducement30 35 40 45 50 55 60 65 70 75 1.3 1.35 1.4 1.45 1.5 1.55 1.6 1.65 1.7 N P V Reduction in NOx Emissions (tons/year) Results, Plotted in Objective Space

Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FAST Fixing America’s Surface Transportation Act (2015) FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TDC Transit Development Corporation TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S.DOT United States Department of Transportation

TRA N SPO RTATIO N RESEA RCH BO A RD 500 Fifth Street, N W W ashington, D C 20001 A D D RESS SERV ICE REQ U ESTED N O N -PR O FIT O R G . U .S. PO STA G E PA ID C O LU M B IA , M D PER M IT N O . 88 G uide for Conducting Benefit-Cost A nalyses of M ultim odal, M ultijurisdictional Freight Corridor Investm ents N CFRP Research Report 38 TRB ISBN 978-0-309-44625-9 9 7 8 0 3 0 9 4 4 6 2 5 9 9 0 0 0 0

Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments Get This Book
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TRB's National Cooperative Freight Research Program (NCFRP) Research Report 38: Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments explores how to conduct benefit-cost analyses (BCAs). A BCA is an analytical framework used to evaluate public investment decisions including transportation investments. BCA is defined as a collection of methods and rules for assessing the social costs and benefits of alternative public policies. It promotes efficiency by identifying the set of feasible projects that would yield the largest positive net benefits to society.

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