Examining the Impact of Family Ownership Alice wanted to examine the impact of family ownership on t

 
   

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Examining the Impact of Family
Ownership

Alice wanted to examine the impact
of family ownership on the valuation and/or performance of newspaper publishing
companies in Hong Kong for her research project She decided to download data
from a publicly available database on the Internet and base her research
entirely on secondary data

When browsing the Internet, Alice
found that information about family ownership of newspaper publishing companies
in Hong Kong was available for 2003, while the relevant financial statements
could be obtained for every year from 1990 to 2004 Her total sample comprised
10 firms Following an initial analysis, Alice decided to use return on assets
as a measure of each newspaper publishing company’s performance This was
calculated as the ratio of earnings before interest and taxes and average
assets using the formula:

return on assets = ( Earnings
before interest and taxes) / (average assets)

Her independent variable was the
level of family ownership, defined as the percentage of the newspaper
publishing company owned by the family Alice presented her research ideas as a
model using the regression equation:

Equation 1: ROA t = ? + ? Ownership
t

Where:

ROA t = return on assets

Ownership t = percentage of
newspaper publishing company owned by family

? and ? = intercept and slope
coefficients

After entering the data she had
obtained for the 10 companies for 2003 in her statistical analysis software,
Alice performed a regression analysis This analysis calculated values for the
intercept and slope coefficients for her regression equation as well as
providing the following statistics:

Equation 2: ROA t = 005 +
(0002)(Ownership t)

Probability (p) for ?: 001

Probability (p) for ?: 015

R2: 002

Durbin-Watson statistic: 11

F-Statistic: 01

Based on these statistics, Alice
felt that the value of the estimate of the beta coefficient was both
economically and statistically significant Alice’s good friend, Betty, agreed
to take a look at the model and make suggestions regarding the inclusion of
independent variables After looking at the model Betty asked, “Why don’t
you examine this relationship over a longer period of time, rather than just
for the one year In addition, you don’t seem to have included any control
variables in your regression model I think it is generally advisable to control
for firm size, industry affiliation, and other factors that

reflect a change in capital
structure and future growth potential in order to single out the impact of
ownership“

Alice agreed to follow the advice
of Betty and re-examine the model She discovered that she could obtain
ownership data for 2002 if she contacted the Hong Kong Stock Exchange However,
she felt this would not provide sufficient data for longitudinal analysis At
the same time she found data on four more publishing companies, bringing the
total sample to 14

She decided to measure firm size
using data on earnings before interest and taxes that she had already collected
and used to calculate return on assets She justified this to Betty, saying,
“Earnings before interest and taxes seems to be a great proxy for firm
size; big firms will have big earnings” She also decided to include data
on marketable securities, commenting, “These indicate a company with high
liquidity and the fact that it may not be in need to further borrow funds

Their leverage will decline as the
amount of marketable security increases” Based upon her discussion with
Betty, Alice presented her research idea to her professor, presenting Equations
1 and 2 and the following model:

Equation 3: ROA t = ? + ? 1
Ownership t + ? 2 EBIT t + ? 3 Market + ? 4 Dummy

Where:

ROA t = return on assets,
calculated by dividing earnings before interest and taxes by average assets

Ownership t = percentage on
newspaper publishing company owned by family

EBIT t = earnings before interest and
taxes

Market = amount of marketable
securities in millions of Hong Kong dollars

Dummy = dummy variable for
industry It equals one if a company is part of newspaper publishing sector,
otherwise zero

? and ? = intercept and slope
coefficients

Questions

1 After Alice had explained her
model to her professor, she was asked, “What problems can you identify in
testing the initial model in Equation 1 with your data?” Provide a
response for Alice

2 Alice’s next question focused
on the analysis associated with Equation 2 “Why do you believe that the
002 coefficient estimate is both economically and statistically
relevant?” Provide a response for Alice

3 In the meeting Alice had with
her academic advisor she was told the inclusion of the dummy and control
variables in Equation 3 adds nothing to the research Why do you think her
professor made this statement?