# **4. Data**

The ride-hailing data that we use to implement our event study design comes from _Gojek_ , which, along with _Grab_ , is Indonesia’s biggest ride-hailing company. These two companies each control about half of the ride-hailing market in Indonesia that for the largest part consists of two-wheeled ride-hailing services on motorbike. _Gojek_ is an Indonesian-owned firm that started in 2010 with a fleet of 20 drivers connected to a call-center, but it was only after the launch of its mobile phone application in January 2015 that the company experienced exponential growth.<sup>13</sup> It now has a fleet of over 1 million drivers and, as of November 2019, _Gojek_ had an estimated 29.2 million monthly active users in Indonesia.<sup>14</sup> The ride-hailing data from _Gojek_ has a daily frequency and covers the period from 1 September 2018 to 1 November 2019, which encompasses the staggered opening of the Phase 1 MRT line that took place between 12 March and 13 May 2019. For each day, we have information on the number of, as well as the average distance-traveled on, _Gojek_ trips originating from (pick-ups) and terminating at (drop-offs) both our treatment and (both sets of) control locations as defined using circles of 50 m and 100 m radii.<sup>15</sup> The data further provide a breakdown between rush and non-rush hour trips, where rush hour trips are defined by _Gojek_ as pick-ups and drop-offs that take place between either 5 – 8 am (morning rush hours) or 4 – 8 pm (evening rush hours).<sup>16</sup> In total, our data contains information on more than 17 million ride-hailing journeys between September 1, 2018 and November 1, 2019.

Meanwhile, our data on daily tap-ins and tap-outs into the MRT system at each individual newly opened MRT station comes from <mark>PT Mass Rapid Transit Jakarta. It covers the period from 1 April 2019 onwards, which is the date on which discounted fares started to be charged and therefore tracking of tap-ins and tapouts started.</mark> A preliminary glance of our data is provided in Figure 4, which plots the 7-day moving average of the sum of _Gojek_ pick-ups and drop-offs within 50 m of all actual Phase 1 MRT stations, and similarly for our control locations. In addition, the figure also plots the 7-day moving average of the combined total number

> 13 The app is a “lifestyle app” which offers a wide-range of other products alongside _Gojek_ ’s ride-hailing service. The ride-hailing service is now referred to as _GoRide_ , but, for ease of exposition and to avoid confusion, we refer to the ride-hailing service as _Gojek_ throughout this paper.

> 14 After our sample period, _Gojek_ completed a merger with _Tokopedia_ in May 2021, with both becoming subsidiaries of a new company, _GoTo_ .

> 15 We also have data on the volume of _Gojek_ trips (drop-offs plus pick-ups) for treatment and control locations as defined using circles of 200 m radius. We unfortunately lack data on average trip distance for these 200m radius circles. Moreover, we are unable to distinguish between rush and non-rush hour trips for these circles.

> 16 These hours differ slightly from the regular weekday peak hours of the MRT system, which are 5 – 9 am and 5 – 7 pm.

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