Question

Suppose you work for a small company that produces and sells gourmet pierogi-flavored cookies (yum?) called Babushkies in Northwest Indiana. Your boss has never really paid any attention to the demand for your product before, and one day she asks you to conduct a quantitative demand analysis for Babushkies. She provides you with yearly data from 2000 and 2019 on factors that may be important in the demand for Babushkies, including the price (Px ) and number of Babushkies sold (Qx) , the price of a related good (Py) and the average annual income for Northwest Indiana (M ).

The following steps walk you through the process of conducting a quantitative demand analysis:

1. Estimate a demand function using a regression. Download the provided Problem Set 3 data file (PS3-Data.csv) and use it to estimate the following linear demand function using the regression tool (under Data Analysis) in Excel:

Qxd=α0+αXPx+αyPy+αMM

What is the estimated demand function (you can round estimated coefficients to two significant decimals)? Write this out clearly. Include a copy of your regression output from Excel.

Year	Qx	Px	Py	M
2019	173	3.7	3.04	39,010
2018	197	5.58	8.45	37,645
2017	175	5.06	1.95	39,718
2016	182	6.65	6.59	39,208
2015	206	5.85	6.87	39,629
2014	176	5.4	3.77	40,239
2013	158	6.55	3.44	39,717
2012	181	4.79	4.49	39,912
2011	170	6.25	5.61	39,738
2010	197	4.54	5.86	39,779
2009	209	4.64	7.89	39,666
2008	180	4.07	3.97	40,814
2007	168	5.7	3.3	39,218
2006	198	4.09	4.68	40,014
2005	214	3.99	7.12	38,889
2004	209	3.63	7.77	39,535
2003	187	4.08	5.39	41,304
2002	189	4.82	5.62	39,899
2001	205	5.12	7.51	40,345
2000	204	3.86	6.7	40,070

Answer 1

Using Excel, the estimated demand function is

Qxd = 172.76 - 7.25Px + 6.82Py + 0.0004M

Please refer to following two images of excel output:

We have arranged the data in ascending order of years.

The regression results using Data Analysis tool is as follows: