Table 7. MMUTIS Detailed Zoning System. Metro Manila (265) Adjoining Areas (51) 78 zones. Source: MMUTIS, 1996

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1 4. DATA ANALYSIS 4.1 Source of Data The Metro Manila Urban Transportation Integration Study (MMUTIS) has been undertaken from 1996 to A reliable and comprehensive database was established. Most of the data can be plotted or interpreted on a map in a form of an area, line or a point where GIS is appropriate. As such, the data are classified according to their shape of their figure. In this classification, the data classifications are as follows: Zone information data Line information data Point information data 00 information data (Inter-zonal information data) Area information data Other non-geographical data The principal sources of data used in the analysis are the 1996 MMUTIS Household Interview Survey, and digitized zone boundaries on Geographic Information System (GIS). 4.2 Zoning System MMUTIS adopted different zoning systems for different analyses. The lowest level consists of 394 zones as shown in Table 7. The corresponding zones can be aggregated to accommodate different planning levels. Table 7. MMUTIS Detailed Zoning System Study Area External Area Total Metro Manila (265) Adjoining Areas (51) 316 zones 78 zones 394 zones Source: MMUTIS, 1996 For the purpose of this project, the 32-planning zone system was adopted. Figure 4 below shows the zoning system. The study area covers the entire Metro Manila and additional municipalities in the provinces of Bulacan, Rizal, Cavite and Laguna. Zone numbers 1 to 12 comprise Metro Manila, zones 13 to 20 comprise Bulacan, zones 21 to 26 comprise Rizal, zones 27 to 30 comprise Cavite and the remaining zones 31 and 32 in Laguna. 14

2 Figure 4. Zoning System 4.3 Data Structure The 1996 MMUTIS HIS Data is organized into distinct information levels according to the conduct of the interview. There are six levels of data used in the study according to the interview form, namely Form 1 - Household Information Form2 - Household Member Information Form 3 - Trip Information Form 4 - Additional Questions for Vehicles Users Form 5 - Additional Questions for the Specially Abled and Elderly People Form 6 - Additional Questions for 1/10 Households (Holiday Traffic, Living Environment, etc.) More specifically, forms 1 to 3 has been extensively utilized in this study. The household information includes household-specific data like number of household members by age group and gender, total monthly household 15

3 " Economic Impact of Traffic Congestion in Metro Manila income, number of vehicles rented and owned, and ownership of house and land. The household member data includes member-specific data like age, gender, occupation, employment sector, monthly income, driver's license type and number of trips in a typical day. The member trip data contains detailed information on the trips of a household member on a typical day to include origin and destination, trip purpose, travel mode, starting and arrival times, and number of transfer. The Household Interview Survey covered a sampling rate of about 2.5% of the total population in the study area. A total of about 30.4 million trips was gathered for the entire sample. 4.4 Profile of Trip-makers Figure 5 shows the total number of trips by income level of the household. It is observed that a high percentage of households fall within the P3,000 to P15,000 level. Almost 50 percent of the trip-makers have undeclared incomes which consist of students, unemployed and persons who do not declared their incomes. Number of Trips by Income Level ,000,000 :!t 12,000,000 ~ 10,000,000 '0.8 8,000,000 E 6,000,000 :::J Z 4,000,000 2,000,000 1"- i-r '.i!, 'l,l, r! - '~ lfl 'l "I ;,, m,:, n _ o ri' ~~ OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J OJ<f/J <f~.r'i!...,,,:>....,(';)...j:1i. ~. "OJ' fiji',,:>oj' «:,OJ..J:1IOJ ~. O:JOJ, r:!>vj" I...,...,'(- ~ ~ '(' ~ q '(- q~ 4' ~~ v ~~lj5p,f~-k>~ ~~' ~~' ~~' ~~' ~~' ~~' ~~' ~~' A~' '(- '(-,,~,,,(';)'..rs>' p,~' ~. -'b~' ~.~. '(' ~ ~ '(' x: q '(-~" q" "',- Income Level Figure 5. Number of Trips by Income Level Figure 6 shows the number of trips by occupation type. About one-third of the trip-makers are students. Another one-third consists of professionals and workers in government and private sector. The remaining consists of trips made by skilled workers, housewives, and jobless individuals. 16

4 Number of Trips by Occupation 6,000,000 III CL ;::.. 0 5,000,000 4,000,000 3,000,000 ~ E 2,000,000 "z 1,000,000 Occupation Figure 6. Number of Trips by Occupation Figure 7 shows the number of trips by type of employment. A large percentage of trip-makers have classification under undeclared! unemployment which are mostly students. The other larger sectors of employment include wholesale and retail trade and transport and communication, Figure 8 shows the number of trips by trip purpose. A total of 46 percent of the trips are To-Home. The To-Work and To-School trips stand at 16 percent each. Figures 9 and 10 show the number of trips by institution of origin and destination, respectively. The Residence is the single highest institution of origin and destination consisting almost 50 percent of all origins and destinations. The next highest are institutions of learning (i.e. schools, universities), then offices and wholesale and retail shops and factories. It is surprising to note that commercial institutions seem to record low number of trips. On the contrary, a relatively large portion of trips under other institutions types. 17

5 Number of Trips by Employment a 'I: I- o!e =z 18,000,000 "l;r!,,:':'), 16,000,000 +=:----"---'-'-...:.:.c..:.,..:...,.;.,.,.,:.:.-j:~..".:.,.,.,...:..~'~ ';'''~~~~.,...:..----~-: 14,000,000 12,000,000 10,000,000 8,000, , ; 6,000,000 4,000,000 n 2,000,000 I-----~---I r 1... o ~~~~--,I~I~-_.~~~I,~... ~I,... ~~~~~~~... ~~-~n~-~. Emplyment Sector Figure 7. Number of Trips by Employment Sector Number of Trips by Trip Purpose i VI a 't: I- ~ ! E ,. z ,:,::,1 :, ',F' Ii _Ff--- - f--.: :: F \ ",...,I I,...,_ n,..., - Trip Purpose Figure 8. Number of Trips by Trip Purpose 18

6 Number of Trips by Institution of Origin,, f-,! ",,'i!' i,' " ii" ')'i, i i f-, f- i i" f- ~ f- ~... I I I I -- I r, Origin Institution Figure9. Number of Trips by Institution of Origin Number of Trips by Institution of Destination ~ - '- - - i t : :'i i'" i r, -- I I,..., I I - I r Destination Institution Figure10. Number of Trips by Institution of Destination Figures 11 and 12 show the starting and arrival times of the trips, respectively. 19

7 Number of Trips by Starting Time o '.. " mir ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ \:),,\5 \:)".J\5 \:)<f;)\5 ~\5 \:)0:>\5 ",,\5 ~\5,,<f;)\5 ~\5,,0:>\5 "v,,\5 ~\5 \:)\:)\5 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ f;;)\:)\5 n\:)\5 _b.~ r<p\5 &;,\:)\5\:)\:)\5 n\:)\5 b<\:)\5t;o\:)\5 <o\:)\5 ~\:)\5 n\:)\5 b<~ \5 \:)V ~' \5 \S ~ "V ~ ~ ~ ~ 0/ ~ '" n 1"111 n n, Starting Time Figure 10. Number of Trips by Starting Time Number of Trips by Arrival Time :t 'C t '0! E '"z Y";:' _...n, " u,.,!.. nl n n Figure 12. Number of Trips by Arrival Time 20

8 4.5 Analysis and Results Figure 13 below shows the zone assignments of the Metro Manila region for analyzing origin-destination characteristics. Figure 13. Metro Manila Zones The analysis for cost of congestion can be analyzed based on delays experienced in commuting. The delays in commuting can be extracted from actual travel times compared with ideal travel times for major origindestination pairs. It is further argued that the delays experienced in commuting can be utilized to more productive uses. Furthermore, valuation of costs varies from individual to individual depending on the corresponding productivity level or hourly income of the trip-maker. There are 14 major classes of occupations adopted in the MMUTIS HIS. However, for the subsequent analyses, five main occupations are considered, namely: Government Officiall Executive Managers Professionals Technicians Clerical Workers Service Workers Under each occupation type, major origin-destination pairs have been identified and ideal travel times are established by delineating a major route and an idealized travel speed of 35 kph. 21

9 Gov't Official/ Exec. Managers Professionals Technicians Clerical Workers Service. Workers. Figure 14. Desire Lines by Occupation Type 22

10 I Economic Impact of Traffic Congestion in Metro Manila Five 0-0 pairs were considered for detailed calculations, namely: 5-3, 5-4, 7-3, 7-5, and The corresponding major trip-ends are Manila, Quezon City (EOSA), Makati, Mandaluyong/ Pasig and Muntinlupa/ Las Pinas which correspond to trips from the southern part of Metro Manila and trips coming from Cavite and Laguna. These major trip-ends also correspond to major heavily-used corridors like EOSA, South Superhighway, Quezon Avenue and Gil Puyat Avenue. I Table 8 below shows the average actual travel times by mode corresponding to each occupation type. Table 8. Average Actual Travel Times Public Transport Jeepney Mini-Bus Std. Bus Gov't Official Professionals Technicians Clerical Workers Service Workers Taxi Car Taxi HOVTaxi 0.94 :+---~-=+----:--=-=I :t-----:o-::c=t----;--::-;i :t-----:o-::c=t----;--=i :t----::-::c=t----;-~ Table 9 shows the computed average airline distance and ideal travel times for the five identified major 0-0 pairs. A weighted ideal travel time of 0.47 hours is established for the major trip-ends. Table 9. Ideal Travel Times for Major 0-0 Major Trip Pair Airline Distance (km) Pairs Ideal Travel Time (hrs.) I 0.21 c:o---i I ~ 0.51-_... Table 10 shows a summary of travel times and calculated average delays. Across all modes, the average travel time is calculated at 1.15 hours for the identified trip-ends. The average delay is calculated at 0.68 hours. Table 11 shows the calculation of total costs for congestion using average monthly incomes under each occupation type. The congestion costs is evaluated at 50 percent the hourly rate multiplied by the delay. 23

11 Table 10. Calculation of Average Travel Time and Average Delay Actual Travel Time (hrs.) Average Average PT Car Taxi Travel Time Delay Gov't Official (37.9%\ (34.6%) (6.2%\ 0.63 Professionals 1.32 (40.6%\ 1.05 (33.5%) 1.12 (7.6%\ Technicians (51.9%) (21.7%\ (5.9%\ Clerical Workers (57%) (15.8%\ (6.2%\ 0.72 Service Workers (55.7%) (10.1%\ (3.6%) 0.61 Note: Values In parentheses Indicate modal share across occupation Table 11. Calculation of Congestion Cost Ave. Average Ave. Hourly Congestion Total Number Total Cost Delay Income Cost! day of Tripsl day (in Plday) (in P) (in P) Gov't Official ,427, ,693,388 Professionals ,460,326 94,921,190 Technicians ,063 19,504,930 Clerical Workers ,134,083 20,271,734 Service Workers ,194,432 41,793,262 Table 11 indicates the total cost per day under each occupation group. The values multiplied by the number of days in the year (&65 is used in this study) yields a yearly cost of around 100 Billion Pesos. The present calculation is still crude at this stage, however, it presents a good picture of the present congestion levels in Metro Manila. Firstly, actual travel times are more than twice the ideal travel times with delays ranging from 0.6 to 0.73 hours. These levels may hold true for the identified major trip-ends but times should be longer for farther trip-ends. Secondly, the trip-ends of the pre-identified occupation types can be easily established through a visual interpretation of the desire lines. This is because workplaces and residences are easily recognized. Lastly, Taxis and HOV Taxi provide a strong alternative to the private car with modal shares almost uniform across occupation types. 24

12 Table 10. Calculation of Average Travel Time and Average Delay Actual Travel Time (hrs.) Average Average PT Car Taxi Travel Time Delay Gov't Official (37.9%) (34.6%\ (6.2%) Professionals (40.6%) (33.5%\ (7.6%) Technicians (51.9%) (21.7%) (5.9%) Clerical Workers (57%) (15.8%\ (6.2%) 0.72 Service Workers (55.7%) (10.1%) (3.6%) Note: Values In parentheses Indicate modal share across occupation Table 11. Calculation of Congestion Cost Ave. Average Delay Congestion Total Number per Trip Ave. Hourly Cost of Trips Total Cost (hrs) Income (PhP per trip) (per day) (PhP per day) Gov't Official ,427, ,693,388 Professionals ,460,326 94,921,190 Technicians ,063 19,504,930 Clerical Workers ,134,083 20,271,734 Service Workers ,194,432 41,793,262 Total 9,069, ,184,503 0x 365 days 101,172,343,741 Table 11 indicates the total cost per day under each occupation group. The values multiplied by the number of days in the year (265 is used in this study) yields a yearly cost of around 100 Billion Pesos. The present calculation is still crude at this stage, however, it presents a good picture of the present congestion levels in Metro Manila. Firstly, actual travel times are more than twice the ideal travel times with delays ranging from 0.6 to 0.73 hours. These levels may hold true for the identified major trip-ends but times should be longer for farther trip-ends. Secondly, the trip-ends of the pre-identified occupation types can be easily established through a visual interpretation of the desire lines. This is because workplaces and residences are easily recognized. Lastly, Taxis and HOV Taxi provide a strong alternative to the private car with modal shares almost uniform across occupation types. 24

13 5. Recommendations A new methodology has been proposed to establish the cost for congestion in Metro Manila. The model prescribed requires rather detailed and disaggregated data from the MMUTIS Household Information Survey. The model is also sensitive with space data as detailed origin-destination data are required as model inputs. The study attempted to operationalize the model, however, several simplifications and assumptions were made in lieu of time and data processing constraints. Although the study provides some monetary figures to quantify congestion costs, there are still many factors that have to be included in the analysis. A further development of the analytical procedure is therefore proposed. 25