Question

Demand estimation Early in 1993, the Southeastern Transportation Authority (STA), a public agency responsible for serving the commuter rail transportation needs of a large Eastern city, was faced with rising operating deficits on its system. Also, because of a fiscal austerity program at both the federal and state levels, the hope of receiving additional subsidy support was slim. The board of directors of STA asked the system manager to explore alternatives to alleviate the financial plight of the system. The first suggestion made by the manager was to institute a major cutback in service. This cutback would result in no service after 7:00 pm, no service on weekends, and a reduced schedule of service during the midday period Monday through Friday. The board of STA indicated that this alternative was not likely to be politically acceptable and could only be considered as a last resort. The board suggested that because it had been over five years since the last basic fare increase, a fare increase from the current level of $1 to a new level of $1.50 should be considered. Accordingly, the board ordered the manager to conduct a study of the likely impact of this proposed fare hike. The system manager has collected data on important variables thought to have a significant impact on the demand for rides on STA. These data have been collected over the past 24 years and include the following variables. Price per ride (in cents) - This variable is designated P in Table 1. Price is expected to have a negative impact on the demand for rides on the system. Population in the metropolitan area serviced by STA - It is expected that this variable has a positive impact on the demand for rides on the System. This variable is designated T in Table 1. Disposable per capita income - This variable was initially thought to have a positive impact on the demand for rides on STA This variable is designated I in Table 1. Parking rate per hour in the downtown area (in cents) this variable is expected to have a positive impact on demand for rides on the STA. It is designated H in Table Below

Year	Weekly Riders (Y)	Price (P) Per	Population	Income (I)	Parking Rate
	(X1,000)	Ride (Cents)	(T)(x1,000)		(H) (Cents)
1966	1200	15	1800	2900	50
1967	1190	15	1790	3100	50
1968	1195	15	1780	3200	60
1969	1110	25	1778	3250	60
1970	1105	25	1750	3275	60
1971	1115	25	1740	3290	70
1972	1130	25	1725	4100	75
1973	1095	30	1725	4300	75
1974	1090	30	1720	4400	75
1975	1087	30	1705	4600	80
1976	1080	30	1710	4815	80
1977	1020	40	1700	5285	80
1978	1010	40	1695	5665	85
1979	1010	40	1695	5800	100
1980	1005	40	1690	5900	105
1981	995	40	1630	5915	105
1982	930	75	1640	6325	105
1983	915	75	1635	6500	110
1984	920	75	1630	6612	125
1985	940	75	1620	5883	130
1986	950	75	1615	7005	150
1987	910	100	1605	7234	155
1988	930	100	1590	7500	165
1989	933	100	1595	7600	175
1990	940	100	1590	7800	175
1991	948	100	1600	8000	190
1992	955	100	1610	8100	200

9. If the fare is increased to $1.50, what is the expected impact on weekly revenues to the transit system if all other variables remain at their 1992 levels?

Answer 1

Hope this helps

running linear regression in Excel with weekly riders as the dependent variable will tell us how much change of weekly riders is brought about by change in the fare,

for every 1 cent increase in fare, 1655.86 (1.65586 x 1000) weekly riders falls

fare is increased from 100 cents to 150 cents, so 82,793 (1655.86 x 50) weekly riders fall.

weekly revenue in 1992, (955000 x 1$) = $ 955000

weekly riders in 1993 (955000- 82793) = 872207

weekly revenue in 1993, (872207 x $ 1.50) = $1308310.5

therefore weekly revenue increases by $ 353,310.5