Question

You will need to use Excel Regression Data Analysis to estimate the following linear model of Texas Natural Gas Utility Residential Demand: (1) QRES = α + β1*PRES + β2*RES + β3*INCOME where QRES = Quantity demand (mcfs) of residential customers PRES = Price per mcf, RES = number of residential customers, INCOME = per capita income, The data below are actual publicly available residential demand data for city/town natural gas distribution utilities in Texas.

You can copy and paste the data into an Excel spreadsheet to estimate Model (1) in question #3 and Model (2) in question #4 below.

COMP	QRES	PRES	RES	INCOME
ALTO CITY OF	32037	18.742079	692	17,346
BRACKETVILLE MUN GAS	10941	16.903482	218	14,729
CARRIZO SPRINGS CITY OF	13050	28.314789	822	20,173
CITY OF SPUR	11950	10.219414	224	14,549
DAISETTA CITY OF	3026	16.64078	92	17,929
EASTON GAS SYS CITY OF	8142	8.7263572	330	14,188
FALFURRIAS UTIL CITY OF	20098	20.581998	985	13,187
GARRISON CITY OF	11738	10.689981	246	15,468
GEORGE WEST CITY OF	6554	20.22307	294	16,254
GRANDFALLS CITY OF	5802	7.4169252	90	14,263
HEMPHILL CITY OF	8695	14.913053	264	16,103
HEMPSTEAD CITY OF	41162	10.649847	1001	15,119
HUGHES NATURAL GAS INC	240882	20.016128	3788	14,104
JOAQUIN MUN GAS CO	3838	12.279833	104	18,097
NAVASOTA CITY OF	60299	11.268313	1523	15,250
NEW SUMMERFIELD CITY OF	31905	10.440213	697	13,714
PEARSALL CITY OF	21724	15.292396	944	14,102
PINELAND CITY OF	6451	20.500698	268	14,803
PLAINS GAS FARMERS COOP	1723	6.5177017	18	17,801
ROBSTOWN UTIL SYS	101397	15.358995	3068	15,134
ROMA CITY OF	7423	18.336387	1014	11,122
SABINAL CITY OF	5443	24.222488	256	17,166
SPLENDORA CITY OF	8711	9.5006314	237	20,014
STERLING NATURAL GAS INC	335453	0.3659618	177	20,799
STOCKDALE CITY OF	7121	19.407106	242	20,583
SUNDOWN CITY OF	25177	10.200222	413	20,220
UVALDE GAS SYSTEM	45336	11.151204	1872	16,113
WHITEFACE CITY OF	9193	8.3978027	186	21,267
WOODSBORO NAT GAS CORP	245056	0.8036326	311	20,751
WOODVILLE CITY OF	25094	9.7655216	772	18,359

The following questions refer to your estimated regression equation (1) QRES = α + β1*PRES + β2*RES + β3*INCOME. Use the estimated demand function to answer questions 3a-3c.

3a. (2 Points) What are the estimated coefficients for β1 (PRES) and β2 (RES)? At what level (choose one: .01, .05 .10) is each coefficient significant or is it not significant? If not significant at the .01, .05 or .10 levels, write in “NS”. Write your answer in 3a above. 3a. (2 Points) β1 = _____; Significance Level = _____ β2 = _____; Significance Level = _____

Use the estimated demand function to answer the following questions. 3b. (2 Point) Suppose PRES = 11.15, RES = 1,872 and INCOME = 16,113. What is the point price elasticity of demand? 3b. (2 Points) Ep = _______

3c. (1 Point) You have just computed the price elasticity of demand for the Uvalde Gas Utility. Is the Uvalde Utility potentially a profit-maximizing utility? Explain. Write your answer in 3c above. 3c. [Answer yes or no, and say why.] Yes/No; Explain why in one sentence:

Answer 1

The regression results from Microsoft Excel is presented below.

Please note that the numbers provided are up to three decimal points.