University of Amsterdam
Amsterdam Business School
Master of International Finance
Master Thesis
Impacts to Airline Corporations with Committed Purchase
Obligations During Financial Shock
Author: Hok Lee Jennifer Tang
September 2014
Table of Content
Introduction
3
Literature Review
5
Methodology
6
Data and Statistics
8
Analysis-General Analysis
9
Analysis-Regression Analysis
28
Results
41
Conclusion
43
Introduction
In practice, airlines corporations accustomed to have committed purchase years
beforehand but they habitually are impotent to envisage when will financial
shocks, which will disturb their business plans and operations both directly and
indirectly, hit them. The intention of this research paper is to recognize the
measures acquired by airline corporations on their investment arrangement and
tactics to cope with financial distress through financial crunch given they have
committed purchase contract in advance. Those measures may embrace but not
limited to reducing committed purchase substantially in the following years
because of the difficulty receiving new funds throughout economic slump,
diminishing cash on balance sheet, lessening in repurchase of shares, cutting
dividends, cutting research and development budgets, reducing remunerations,
cutting recruiting headcounts, firing workforces, declining in benefits and
corporate welfare, etc.
This paper investigates how firms with committed purchase react to financial
distress and adjustments in terms of new investment strategies during financial
crisis through the period from 2000 to 2012. Industries to be reviewed should be
ones cyclically devoting a huge amount of capital and investments on
substitution and maintenance in machineries, plants, etc. Feasible industries
include oil and gas, mining, airlines, shipping, telecommunication, railroads and
so on. Owing to the obtainability of data, airline industry is preferred as the
target industry of this research paper. As said by the US exchange regulations,
future investments data, which is indispensable for this research paper, under
10-K filings through US Securities and Exchange Commission website.
Consequently, 18 airline corporations from the US exchange pool are designated
as the investigation targets of this research paper. Analysis using
differences-in-differences strategy was performed.
This research paper focused in three dependent variables, namely, cost of good
sold, advertising expenses and expenses on selling, general an administration.
These three dependent variables were tested in regression against some control
variables, like total assets value, stock returns from 1 and 2 years, Tobin’s Q,
presence of treatment, post-crisis and treatment for post-crisis. Regression test
results showed that there is no significant relationship for each dependent
variable to any of the control variables.
The first section is some philosophies, forecasts, pragmatic evidences and
research outcomes from literatures and papers from scholars that provide more
background information and support to this research paper. The subsequent
section is the methodology and hypothesis used in this research paper. This
incorporates the categories of statistics mined, the statistical model used,
examination of variables and corresponding implication, if any. The third section
is the summary of statistics followed by discussion of analysis, which will lead to
the outcomes validation. The finishing section is the conclusion of the entire
research paper.
Literature Review
From the time when majority of the longstanding liabilities, such as committed
purchase obligations, of registered corporations are publicly held, it is of
tremendous nuisance to renegotiate on short notice (Bolton and Scharfstein,
1996). Henceforth, those corporations have high propensity to accomplish the
long term liability obligations although on the other hand taking other short
term measures due to the struggle of getting new subsidy to endure financial
well-being (see Shleifer and Vishny, 1992) whereas assuaging precipitous
financial anxiety because of unforeseen financial tremors (see Whitaker, 1999).
Those short-term measures includes but not limited to reducing short term
ventures (see Almeida, Heitor, Campello, Laranjeira and Weisbenner, 2011),
trimming bonuses and dividends (see DeAngelo and DeAngelo, 1990) and
sinking employment headcounts. Some researches propose that cash and other
liquid assets on the balance sheet customarily captivate the brunt of shocks, e.g.
financial crisis, to peripheral funding (See Almeida, Campello and Weisbach,
2004). Diminution of inventory, as recommended by observations and records, is
demonstrated to be one of the resolutions to alleviate financial distress during
financial crisis (see Fazzari and Petersen, 1993). Nevertheless, there is a
thought-provoking study indicates that it is exceptional to have corporations with bulky
amount of committed purchase obligations tumbling or cutting dividends to
relieve their financial burden (see Brav, Graham, Harvey and Michaely, 2005).
Research papers and numbers mirror that some businesses with weighty
committed purchase obligations capitalized less, accompanied by huge lost in
and Weisbenner, 2011; Hunter, Kaufman and Krueger, 1999; Ongena, Smith and
Michalsen, 2003). Financial restructuring is one of the last resort corporations
under unsolvable financial distress (see Asquith, Robert and Scharfstein, 1994;
Denis and Kruse, 2000).
There are some firm characteristics, such as, profit-generating capability,
debt-to-asset ratio, credit ranking (see Campello, Graham and Harvey, 2010), firm
scope, etc. verified to have correlation while making verdicts among taking short
term and long term debt commitments (see Barclays and Smith, 1995; Guedes
and Opler, 1996; Opler and Titman, 1994; Asgharian, 2003; Bergstrom and
Sundgren, 2002). Aforementioned research advocates that firms with stumpy
debt-to-asset relation may have larger influence, which depends on the maturity
of obligations, on macroeconomic financial shockwaves (see Almeida, Campello,
Laranjeira and Weisbenner, 2011).
Methodology
In the first place, evaluation on which industry to concentrate on had to be made.
The thesis supervisor offered a list of companies, which have elevated likelihood
of participating in committed purchase obligation years in advance. Committed
purchase obligation linked documents of the corporations was extracted from
10-K filing through US Securities and Exchange Committee website. So as to have
an unprejudiced and objective examination on the figures, it would be
corporations with obtainable and comprehensive statistics on committed
purchase obligations from 2000 to 2012. Additionally, this industry necessitates
sizeable forthcoming investments recurrently for replacement of planes and
regular maintenance. Henceforward, airline industry turned out to be the target
industry of this research paper.
Pertinent figures incorporating committed purchase obligation totals with
corresponding years was gathered from 10-K company filing through US
Securities and Exchange Committee website. Likewise, asset values, capital
expenditures and values of physical properties, plants and equipment (PPENT)
each year of each firm were extracted from Compustat database and their annual
reports. Information applicable to the drive of this research paper was of 234
series.
As for dependent variables, they are cost of goods sold, advertising expenses and
selling, general and administrative expenses over total assets correspondingly.
Statistics for cost of goods sold (COGS), advertising expenses and selling, general
and administrative expenses (XSGA) from 2006 to 2011 for each corporation,
excluding 3 firm outliers, were collected from their annual reports.
As for control variables, there are two sorts, binary ones and non-binary ones.
For binary ones, they are treatment, post-crisis and treatment with post-crisis. 1
stands for presence while 0 stands for absence. On behalf of non-binary ones,
they are log of total assets, Tobin’s Q, log of stock return in 1 year and log of
market value with liability market value, divided by corporate net worth, i.e.
equity book value with liability book value. Figures for total assets, stock values,
corporate net worth, stock returns in 1 and 2 years from 2006 to 2012 for each
corporations, ignoring 3 outliers, were collected from their annual reports and
Compustat database.
The aspiration of assembling these data sets is principally to scrutinize how
financial shocks, which lead to a abrupt and unanticipated cash crunch, upsets
the business planning of corporations, which had committed purchase
agreements years in advance that cannot be pull out. Hence,
differences-in-differences strategy is used in the analysis of data. To be more explicit, this
research paper will predominantly be motivated on the committed purchase
agreement created since 2006 and financial shock in 2008. Alternative incentive
is that many people consider that corporations participate regularly on rolling
yearly basis, i.e. from this year to next year. This impression may be elucidated
by the regression of annual investment annual cash flows perceived from some
scholastic research papers. Hitherto, there are corporations, like airline ones,
endowing years in advance.
Data and Statistics
The data assemblage progression generated 234 sets of data amongst 18 airline
corporations from 2000 to 2012 for general analysis. Amid those 18 airline
corporations, there were 3 airline corporations having deficient data for cost of
from 2006 to 2011. To endure advance exploration, comprehensiveness of
dataset is vital. Thus, those 3 corporations were not involved in the advance
discussion nonetheless still in the general analysis in order to stipulate a more
comprehensive portrait for the entire airline industry. Namely, 90 sets of data
among 15 airline corporations from 2006 to 2011 are congenital from general
analysis for further analysis.
Analysis-General Analysis
In the attempt to have a enhanced understanding of committed purchase figures,
committed purchase amounts were assessed in terms of asset values, capital
expenditures and values of physical properties, plants and equipment. All the
figures recorded underneath are in millions.
Committed Purchase in Years/Capex Committed Purchase in Years/Assets Committed Purchase in Years/PPENT Airlines Year 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 Airtran Hldgs Inc 2000 1.93 - - - - 0.17 - - - - 0.31 - - - - 2001 (0.99) 0.19 - - - 0.01 0.19 - - - 0.03 0.05 - - - 2002 3.62 5.05 - - - 0.29 5.05 - - - 0.86 0.61 - - - 2003 1.24 - - - - 0.06 - - - - 0.15 - - - - 2004 0.41 0.18 - - - 0.04 0.18 - - - 0.08 0.02 - - - 2005 0.62 - - - - 0.04 - - - - 0.06 - - - - 2006 0.08 0.05 - - 0.01 0.00 - - 0.01 0.00 - - 2007 5.68 11.16 - - 0.22 0.26 - - 0.36 0.44 - - 2008 5.11 19.59 - - - 0.17 0.23 - - - 0.30 0.39 - - - 2009 5.21 - - - - 0.06 - - - - 0.10 - - - - 2010 - - - - - - - - - 2011 - - - - - - - - - 2012 - - - - - - - - - Alaska Air Group Inc 2000 0.72 2.12 0.71 0.90 0.62 0.11 0.15 0.08 0.05 0.07 0.18 0.24 0.13 0.09 0.13
2001 3.61 0.40 0.54 0.30 0.16 0.25 0.05 0.03 0.03 0.03 0.41 0.08 0.05 0.06 0.05 2002 0.63 0.91 0.51 0.16 - 0.07 0.05 0.06 0.03 - 0.12 0.09 0.11 0.05 - 2003 1.41 0.54 0.16 - - 0.08 0.06 0.03 - - 0.14 0.11 0.05 - - 2004 0.20 0.14 0.05 0.12 0.11 0.02 0.02 0.01 0.01 0.01 0.04 0.04 0.02 0.02 0.02 2005 0.18 0.10 0.20 0.19 0.39 0.03 0.02 0.02 0.02 0.01 0.05 0.03 0.03 0.03 0.02 2006 0.49 0.87 0.43 0.86 0.42 0.09 0.07 0.04 0.03 0.03 0.14 0.11 0.06 0.05 0.05 2007 1.37 0.68 1.04 0.46 0.15 0.12 0.06 0.04 0.03 0.01 0.18 0.09 0.06 0.05 0.02 2008 1.19 2.11 0.49 0.15 - 0.10 0.08 0.04 0.01 - 0.16 0.12 0.06 0.02 - 2009 2.55 0.87 0.24 - - 0.09 0.07 0.02 - - 0.15 0.10 0.03 - - 2010 0.48 0.28 - - - 0.04 0.03 - - - 0.05 0.04 - - - 2011 0.56 - - - - 0.05 - - - - 0.08 - - - - 2012 - - - -
Alaska Airlines Inc 2000 0.58 1.41 0.33 - - 0.09 0.09 0.03 - - 0.14 0.14 0.06 - - 2001 1.42 0.41 - - - 0.09 0.04 - - - 0.14 0.07 - - - 2002 0.16 0.52 0.23 - - 0.02 0.03 0.02 - - 0.03 0.05 0.05 - - 2003 1.20 0.28 - - - 0.06 0.03 - - - 0.11 0.06 - - - 2004 0.14 0.10 - - - 0.02 0.02 - - - 0.03 0.03 - - - 2005 0.18 0.05 0.09 0.09 - 0.03 0.01 0.01 0.01 - 0.05 0.01 0.01 0.01 - 2006 0.53 0.69 0.53 - - 0.08 0.05 0.04 - - 0.13 0.09 0.07 - - 2007 1.30 0.84 - - - 0.09 0.07 - - - 0.16 0.12 - - - 2008 1.13 - - - - 0.09 - - - - 0.15 - - - - 2009 - - - - 2010 - - - - 2011 - - - - 2012 - - - - American Airlines Inc 2000 0.67 0.94 1.21 0.38 0.39 0.07 0.05 0.02 0.01 0.01 0.12 0.07 0.02 0.01 0.01
2001 2.19 3.33 0.88 0.16 - 0.11 0.04 0.01 0.00 - 0.18 0.07 0.02 0.00 - 2002 3.48 2.56 1.31 0.64 0.49 0.04 0.04 0.02 0.01 0.01 0.07 0.06 0.03 0.02 0.02 2003 2.19 - 0.23 0.78 0.61 0.03 - 0.00 0.02 0.02 0.05 - 0.01 0.04 0.04 2004 1.07 0.91 1.33 0.82 0.43 0.02 0.02 0.04 0.03 0.03 0.03 0.03 0.06 0.05 0.05 2005 0.76 0.61 0.26 0.11 0.09 0.01 0.02 0.01 0.01 0.01 0.03 0.03 0.02 0.01 0.01 2006 0.64 0.25 0.10 0.09 0.11 0.02 0.01 0.01 0.01 0.01 0.03 0.02 0.01 0.01 0.01 2007 0.31 0.11 0.09 0.11 0.33 0.01 0.01 0.01 0.01 0.03 0.02 0.01 0.01 0.01 0.05 2008 0.35 0.37 0.10 0.14 - 0.02 0.03 0.01 0.01 - 0.04 0.05 0.01 0.02 - 2009 0.74 0.88 0.27 - - 0.05 0.05 0.02 - - 0.09 0.09 0.04 - - 2010 1.04 0.27 - - - 0.06 0.02 - - - 0.11 0.04 - - - 2011 0.46 - - - - 0.04 - - - - 0.07 - - - - 2012 - - - - - - - - - - - - -
AMR Corp 2000 0.73 0.96 0.88 0.24 0.37 0.08 0.06 0.02 0.01 0.01 0.14 0.09 0.03 0.01 0.01 2001 1.89 2.35 0.88 0.64 0.82 0.12 0.05 0.03 0.01 0.01 0.18 0.08 0.05 0.02 0.02 2002 2.65 1.66 1.76 0.90 0.67 0.06 0.06 0.04 0.02 0.02 0.09 0.09 0.06 0.03 0.03 2003 1.17 1.34 1.61 1.16 0.96 0.04 0.03 0.03 0.03 0.03 0.06 0.05 0.05 0.05 0.05 2004 1.95 1.72 0.74 0.05 0.04 0.03 0.07 0.06 0.11 2005 1.66 0.53 0.12 0.03 0.02 0.01 0.05 0.03 0.03 2006 0.80 0.23 0.09 0.02 0.01 0.01 0.03 0.02 0.02 2007 0.48 0.13 0.10 0.02 0.01 0.01 0.03 0.01 0.02 2008 0.45 0.23 0.40 0.03 0.02 0.03 0.04 0.03 0.06 2009 0.70 0.55 - - 0.05 0.04 - - 0.09 0.07 - - 2010 1.19 0.64 - - 0.08 0.05 - - 0.13 0.09 - - 2011 0.62 - - - - 0.05 - - - - 0.09 - - - - 2012 - - - - - - - - - - - - - Delta Airlines Inc 2000 - - - - 2001 - - - - 2002 - - - - 2003 - - - - 2004 1.17 2.88 1.25 0.55 0.04 0.05 0.06 0.04 0.02 0.00 0.07 0.09 0.11 0.04 0.00 2005 3.05 0.59 1.09 0.43 0.31 0.06 0.02 0.04 0.01 0.01 0.10 0.05 0.08 0.03 0.02 2006 0.28 0.35 0.76 0.41 0.84 0.01 0.01 0.02 0.01 0.02 0.02 0.03 0.04 0.03 0.05 2007 0.48 0.73 0.75 0.59 0.01 0.02 0.02 0.02 0.02 0.00 0.04 0.04 0.05 0.04 0.00 2008 1.21 0.98 0.62 0.03 - 0.03 0.03 0.02 0.00 - 0.07 0.06 0.04 0.00 - 2009 1.33 0.85 0.06 - - 0.04 0.02 0.00 - - 0.09 0.05 0.01 - - 2010 1.18 0.14 - - - 0.03 0.01 - - - 0.07 0.01 - - - 2011 0.22 - - - - 0.01 - - - - 0.02 - - - - 2012 - - - - - - - - - - - - - Expressjet Hldgs Inc 2000 - - - -
2001 - - - - 2002 - - - - 2003 0.70 5.34 3.79 0.05 0.22 0.23 0.10 1.08 1.06 0.85 1.02 2004 0.69 1.54 1.31 6.47 13.58 0.03 0.07 0.11 0.17 0.19 0.06 0.17 0.24 0.30 0.35 2005 0.53 0.75 3.83 8.04 - 0.02 0.06 0.10 0.11 - 0.06 0.14 0.18 0.21 - 2006 0.18 1.11 2.32 - - 0.01 0.03 0.03 - - 0.03 0.05 0.06 - - 2007 - - - - - - - - - - - - - 2008 - - - - - - - - - - - - - 2009 - - - - - - - - - - - - - 2010 - - - - - - - - - - - - - 2011 - - - - - - - - - - - - - 2012 - - - - - - - - - - - - - Hawaiian Hldgs Inc 2000 - - - - 2001 - - - - 2002 - - - - 2003 - 0.09 0.00 0.02 0.02 0.21 0.00 0.00 0.00 0.00 - 0.01 0.00 0.00 0.00 2004 - - - - 2005 - - - - 2006 - - - - 2007 - - - - 2008 0.45 0.07 1.00 0.02 0.01 0.16 0.06 0.07 0.27 2009 0.11 0.26 - - 0.01 0.04 - - 0.04 0.20 - - 2010 0.23 1.12 - - 0.04 0.17 - - 0.09 0.31 - - 2011 0.77 - - - - 0.12 - - - - 0.21 - - - - 2012 - - - - - - - - - Jetblue Airways Corp 2000 - - - - 2001 - - - -
2002 - - - - 2003 0.70 0.44 0.41 0.28 0.30 0.20 0.13 0.09 0.04 0.03 0.26 0.17 0.13 0.05 0.04 2004 0.68 0.76 1.42 1.65 1.97 0.20 0.17 0.19 0.18 0.15 0.26 0.24 0.28 0.24 0.22 2005 0.91 1.55 1.85 2.43 4.05 0.21 0.21 0.20 0.19 0.19 0.29 0.31 0.27 0.27 0.27 2006 1.80 1.92 2.57 4.41 2.54 0.24 0.21 0.20 0.21 0.19 0.35 0.28 0.28 0.30 0.28 2007 1.46 1.87 3.54 2.23 1.41 0.16 0.15 0.17 0.17 0.17 0.21 0.21 0.24 0.24 0.22 2008 1.60 2.86 1.61 1.09 - 0.13 0.14 0.12 0.13 - 0.18 0.19 0.17 0.17 - 2009 1.83 0.85 0.76 - - 0.09 0.06 0.09 - - 0.12 0.09 0.12 - - 2010 0.90 0.93 - - - 0.07 0.11 - - - 0.10 0.14 - - - 2011 0.74 - - - - 0.09 - - - - 0.11 - - - - 2012 - - - - - - - - - Midwest Air Group Inc 2000 0.61 0.56 0.02 0.06 0.03 0.10 0.08 0.00 0.00 0.00 0.14 0.11 0.00 0.00 0.00
2001 0.47 0.02 0.06 0.03 0.05 0.07 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.00 0.00 2002 0.02 0.06 0.03 0.04 - 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 - 2003 0.06 0.03 0.04 - - 0.00 0.00 0.00 - - 0.00 0.00 0.00 - - 2004 0.03 0.04 - - - 0.00 0.00 - - - 0.00 0.00 - - - 2005 0.04 - - - - 0.00 - - - - 0.00 - - - - 2006 - - - - - - - - - - - - - 2007 - - - - - - - - - - - - - 2008 - - - - - - - - - - - - - 2009 - - - - - - - - - - - - - 2010 - - - - - - - - - - - - - 2011 - - - - - - - - - - - - - 2012 - - - - - - - - - - - - - Northwest Airlines Corp 2000 0.48 0.46 0.97 2.25 3.51 0.05 0.06 0.08 0.08 0.10 0.09 0.10 0.14 0.13 0.15
2001 0.81 1.41 4.40 2.92 1.57 0.10 0.11 0.15 0.08 0.06 0.18 0.21 0.26 0.13 0.10 2002 1.79 4.27 3.84 2.49 0.21 0.14 0.15 0.11 0.10 0.01 0.26 0.25 0.17 0.16 0.03
2003 3.74 3.42 2.25 0.55 - 0.13 0.09 0.09 0.02 - 0.22 0.15 0.14 0.07 - 2004 4.54 1.46 0.56 - - 0.12 0.06 0.02 - - 0.20 0.09 0.07 - - 2005 1.81 0.91 - - - 0.07 0.04 - - - 0.12 0.12 - - - 2006 0.57 - - - - 0.02 - - - - 0.07 - - - - 2007 - - - - - - - - - - - - - - - 2008 - - - - - - - - - - - - - - - 2009 - - - - - - - - - - - - - - - 2010 - - - - - - - - - - - - - - - 2011 - - - - - - - - - 2012 - - - - - - - - - Pinnacle Airlines Corp 2000 - - - - 2001 - - - - 2002 - - - - 2003 - - - - 2004 - - - - 2005 0.30 0.02 0.08 0.00 0.00 0.00 0.03 0.01 0.00 2006 0.02 0.05 0.13 0.08 0.03 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 2007 0.05 0.16 0.07 0.03 - 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 - 2008 63.34 1.62 0.02 - - 0.41 0.02 0.00 - - 0.73 0.03 0.00 - - 2009 3.45 9.15 - - - 0.04 0.12 - - - 0.06 0.17 - - - 2010 9.18 - - - - 0.12 - - - - 0.17 - - - - 2011 - - - - - - - - - - - - - 2012 - - - - - - - - - - - - - Republic Airways Hldgs Inc 2000 - - - - - - - - - - 2001 - - - - 2002 - - - - 2003 - - - -
2004 - - - - 2005 4.86 - - - - 0.32 - - - - 0.39 - - - - 2006 2.07 - - - - 0.11 - - - - 0.13 - - - - 2007 7.87 - - - - 0.36 - - - - 0.43 - - - - 2008 20.65 - - - - 0.21 - - - - 0.27 - - - - 2009 1.95 0.20 - - - 0.03 0.01 - - - 0.04 0.01 - - - 2010 0.13 1.09 - - 0.00 0.01 - - 0.01 0.02 - - 2011 5.75 - - - - 0.07 - - - - 0.10 - - - - 2012 - - - - - - - - - - - - - Skywest Inc 2000 - - - - 2001 - - - - 2002 0.86 3.48 - - - 0.42 0.44 - - - 0.75 0.79 - - - 2003 2.98 1.93 0.48 - - 0.38 0.19 0.03 - - 0.68 0.25 0.05 - - 2004 1.14 1.53 - - - 0.11 0.10 - - - 0.15 0.15 - - - 2005 2.04 - - - - 0.13 - - - - 0.20 - - - - 2006 1.68 0.95 - - - 0.15 0.05 - - - 0.23 0.08 - - - 2007 1.57 - - - - 0.09 - - - - 0.13 - - - - 2008 0.30 2.20 0.53 - - 0.03 0.07 0.02 - - 0.04 0.11 0.03 - - 2009 2.39 0.53 - - - 0.08 0.02 - - - 0.12 0.03 - - - 2010 0.53 - - - - 0.02 - - - - 0.03 - - - - 2011 2.98 - - - - 0.05 - - - - 0.07 - - - - 2012 - - - - - - - - - - - - - Southwest Airlines 2000 0.69 0.86 0.42 0.09 0.07 0.08 0.06 0.05 0.01 0.01 0.11 0.08 0.07 0.02 0.01 2001 1.11 0.62 0.27 0.53 0.27 0.07 0.08 0.04 0.05 0.03 0.10 0.10 0.05 0.07 0.04 2002 0.26 0.39 0.57 0.51 0.48 0.03 0.06 0.05 0.05 0.04 0.04 0.08 0.07 0.07 0.06 2003 0.34 0.56 0.51 0.47 0.55 0.05 0.05 0.05 0.04 0.04 0.07 0.07 0.07 0.06 0.05 2004 1.05 0.60 0.53 0.57 0.17 0.09 0.06 0.04 0.04 0.01 0.13 0.08 0.07 0.05 0.01
2005 0.74 0.56 0.61 0.19 0.02 0.08 0.04 0.04 0.01 0.00 0.10 0.07 0.05 0.01 0.00 2006 0.59 0.51 0.16 0.02 0.01 0.05 0.03 0.01 0.00 0.00 0.07 0.04 0.01 0.00 0.00 2007 1.12 1.34 0.99 0.37 0.24 0.07 0.05 0.03 0.02 0.02 0.09 0.07 0.05 0.03 0.03 2008 1.38 1.08 0.39 0.33 - 0.06 0.03 0.02 0.02 - 0.08 0.05 0.03 0.04 - 2009 0.90 0.55 0.39 - - 0.03 0.03 0.03 - - 0.04 0.04 0.04 - - 2010 0.44 0.37 - - - 0.02 0.03 - - - 0.04 0.04 - - - 2011 0.50 - - - - 0.04 - - - - 0.05 - - - - 2012 - - - - - - - - - - - - - United Airliens Inc 2000 - - - - 2001 - - - - 2002 7.63 0.60 1.37 1.65 0.60 0.05 0.01 0.03 0.02 0.02 0.07 0.01 0.05 0.05 0.03 2003 0.79 1.47 1.75 0.62 0.98 0.01 0.04 0.02 0.02 0.02 0.01 0.05 0.05 0.03 0.04 2004 1.36 0.70 - - 2.81 0.03 0.01 - - 0.05 0.05 0.02 - - 0.09 2005 0.92 0.09 0.13 2.97 2.15 0.01 0.00 0.00 0.05 0.03 0.03 0.01 0.01 0.10 0.07 2006 0.38 0.66 1.99 2.69 0.80 0.01 0.01 0.03 0.04 0.02 0.02 0.03 0.06 0.09 0.04 2007 0.67 3.35 4.25 1.21 0.64 0.01 0.06 0.07 0.03 0.02 0.03 0.11 0.14 0.06 0.06 2008 3.72 3.73 2.10 0.94 - 0.06 0.06 0.05 0.04 - 0.12 0.13 0.11 0.08 - 2009 1.73 1.72 1.21 - - 0.03 0.04 0.05 - - 0.06 0.09 0.11 - - 2010 1.51 1.08 - - - 0.04 0.04 - - - 0.08 0.10 - - - 2011 0.53 - - - - 0.02 - - - - 0.05 - - - - 2012 - - - - - - - - - - - - - United Continental Hldgs Inc 2000 1.03 11.46 4.00 - - 0.08 0.08 0.03 - - 0.11 0.11 0.04 - - 2001 15.92 11.33 1.87 - - 0.11 0.08 0.02 - - 0.15 0.11 0.03 - - 2002 8.07 0.55 1.06 0.74 0.06 0.01 0.03 0.02 0.08 0.01 0.04 0.03 0.07 2003 0.37 0.64 1.10 0.61 0.96 0.00 0.02 0.02 0.02 0.02 0.01 0.02 0.03 0.04 0.04 2004 0.21 1.10 0.61 1.20 0.32 0.01 0.02 0.02 0.03 0.01 0.01 0.03 0.04 0.05 0.01 2005 0.28 0.56 1.58 1.08 0.00 0.01 0.03 0.01 0.01 0.03 0.05 0.02
2006 0.15 0.14 0.09 0.00 0.00 0.00 0.01 0.00 0.00 2007 0.31 0.11 0.25 0.01 0.00 0.01 0.01 0.00 0.02 2008 1.37 0.23 0.35 0.02 0.00 0.02 0.04 0.01 0.04 2009 0.62 0.12 - - 0.01 0.00 - - 0.01 0.01 - - 2010 0.29 0.10 - - - 0.01 0.01 - - - 0.01 0.01 - - - 2011 0.42 - - - - 0.02 - - - - 0.05 - - - - 2012 - - - - - - - - - - - - - US Airways Group Inc 2000 3.51 8.21 2.96 1.93 - 1.41 0.90 0.28 0.29 - 2.69 1.99 0.75 0.65 - 2001 7.19 2.18 0.75 12.11 1.51 0.79 0.21 0.11 0.08 0.05 1.74 0.55 0.25 0.26 0.17 2002 2.42 0.01 0.05 0.41 0.63 0.23 0.00 0.00 0.01 0.05 0.62 0.00 0.00 0.04 0.15 2003 1.48 7.11 1.64 1.46 0.56 0.22 0.04 0.05 0.11 0.08 0.49 0.15 0.18 0.35 0.18 2004 51.70 4.74 1.09 0.26 0.34 0.33 0.15 0.08 0.04 0.03 1.10 0.52 0.26 0.08 0.06 2005 2.06 0.46 0.30 1.30 4.95 0.06 0.03 0.05 0.12 0.13 0.23 0.11 0.10 0.24 0.26 2006 4.03 2.16 3.39 14.10 4.59 0.30 0.32 0.31 0.36 0.33 0.98 0.70 0.63 0.75 0.66 2007 2.79 5.05 17.34 5.28 3.64 0.41 0.46 0.45 0.38 0.30 0.91 0.93 0.92 0.75 0.60 2008 1.17 6.32 2.21 1.65 - 0.11 0.16 0.16 0.14 - 0.22 0.33 0.32 0.27 - 2009 6.52 2.26 1.66 - - 0.17 0.16 0.14 - - 0.35 0.32 0.27 - - 2010 0.50 0.65 - - - 0.04 0.05 - - - 0.07 0.11 - - - 2011 0.74 - - - - 0.06 - - - - 0.12 - - - - 2012 - - - - - - - - - - - - -
Regarding gathering of committed purchase figures, the statistics was
characterized as committed in a year and three to five years and summarized in
the table underneath. All the statistics beneath are in millions.
Commitment
Purchase in Commitment Purchase in Airlines Year 1 year 3-5 year Airlines Year 1 year 3-5 year Airtran Holdings Inc 2000 0.31 - Alaska Air Group Inc 2000 0.18 0.35
2001 0.03 - 2001 0.41 0.16 2002 0.86 - 2002 0.12 0.15 2003 0.15 - 2003 0.14 0.05 2004 0.08 - 2004 0.04 0.05 2005 0.06 - 2005 0.05 0.07 2006 0.01 0.00 2006 0.14 0.16 2007 0.36 0.44 2007 0.18 0.13 2008 0.30 - 2008 0.16 0.08 2009 0.10 - 2009 0.15 0.03 2010 - - 2010 0.05 - 2011 - - 2011 0.08 - 2012 - - 2012 - -
Alaska Airlines Inc 2000 0.14 0.06 Airlines Inc American 2000 0.12 0.04
2001 0.14 - 2001 0.18 0.03 2002 0.03 0.05 2002 0.07 0.08 2003 0.11 - 2003 0.05 0.08 2004 0.03 - 2004 0.03 0.16 2005 0.05 0.02 2005 0.03 0.04 2006 0.13 0.07 2006 0.03 0.03 2007 0.16 - 2007 0.02 0.07 2008 0.15 - 2008 0.04 0.03 2009 - - 2009 0.09 0.04 2010 - - 2010 0.11 - 2011 - - 2011 0.07 - 2012 - - 2012 - -
AMR Corp 2000 0.14 0.06 Delta Airlines Inc 2000 - -
2001 0.18 0.09 2001 - - 2002 0.09 0.12 2002 - - 2003 0.06 0.15 2003 - - 2004 0.07 0.28 2004 0.07 0.15 2005 0.05 0.08 2005 0.10 0.13 2006 0.03 0.06 2006 0.02 0.12 2007 0.03 0.06 2007 0.04 0.09
2009 0.09 0.07 2009 0.09 0.01
2010 0.13 0.09 2010 0.07 -
2011 0.09 - 2011 0.02 -
2012 - - 2012 - -
Expressjet Holdings Inc 2000 - - Holdings Inc Hawaiian 2000 - -
2001 - - 2001 - - 2002 - - 2002 - - 2003 0.10 2.79 2003 - 0.01 2004 0.06 0.90 2004 - - 2005 0.06 0.39 2005 - - 2006 0.03 0.06 2006 - - 2007 - - 2007 - - 2008 - - 2008 0.06 0.61 2009 - - 2009 0.04 0.20 2010 - - 2010 0.09 0.31 2011 - - 2011 0.21 - 2012 - - 2012 - -
Jetblue Airways Corp 2000 - - Midwest Air Group Inc 2000 0.14 0.01
2001 - - 2001 0.09 0.01 2002 - - 2002 0.00 0.01 2003 0.26 0.23 2003 0.00 0.00 2004 0.26 0.74 2004 0.00 - 2005 0.29 0.81 2005 0.00 - 2006 0.35 0.86 2006 - - 2007 0.21 0.70 2007 - - 2008 0.18 0.34 2008 - - 2009 0.12 0.12 2009 - - 2010 0.10 - 2010 - - 2011 0.11 - 2011 - - 2012 - - 2012 - -
Northwest Airlines Corp 2000 0.09 0.43 Airlines Corp Pinnacle 2000 - -
2001 0.18 0.48 2001 - - 2002 0.26 0.35 2002 - - 2003 0.22 0.22 2003 - - 2004 0.20 0.07 2004 - - 2005 0.12 - 2005 0.03 0.01 2006 0.07 - 2006 0.01 0.00 2007 - - 2007 0.00 0.00 2008 - - 2008 0.73 0.00 2009 - - 2009 0.06 - 2010 - - 2010 0.17 - 2011 - - 2011 - - 2012 - - 2012 - -
Republic Airways Holdings
Inc 2000 - - Skywest Inc 2000 - -
2001 - - 2001 - - 2002 - - 2002 0.75 - 2003 - - 2003 0.68 0.05 2004 - - 2004 0.15 - 2005 0.39 - 2005 0.20 - 2006 0.13 - 2006 0.23 - 2007 0.43 - 2007 0.13 - 2008 0.27 - 2008 0.04 0.03 2009 0.04 - 2009 0.12 - 2010 0.01 0.02 2010 0.03 - 2011 0.10 - 2011 0.07 - 2012 - - 2012 - -
Southwest Airlines 2000 0.11 0.10 United Airlines Inc 2000 - -
2001 0.10 0.16 2001 - - 2002 0.04 0.20 2002 0.07 0.13 2003 0.07 0.18 2003 0.01 0.13 2004 0.13 0.12 2004 0.05 0.09 2005 0.10 0.06 2005 0.03 0.17 2006 0.07 0.01 2006 0.02 0.20 2007 0.09 0.10 2007 0.03 0.26 2008 0.08 0.07 2008 0.12 0.19 2009 0.04 0.04 2009 0.06 0.11 2010 0.04 - 2010 0.08 - 2011 0.05 - 2011 0.05 - 2012 - - 2012 - - United Continental
Holdings Inc 2000 0.11 0.04 US Airways Group Inc 2000 2.69 1.40 2001 0.15 0.03 2001 1.74 0.68 2002 0.08 0.10 2002 0.62 0.20 2003 0.01 0.11 2003 0.49 0.72 2004 0.01 0.09 2004 1.10 0.41 2005 0.01 0.10 2005 0.23 0.60 2006 0.01 0.01 2006 0.98 2.03 2007 0.01 0.04 2007 0.91 2.27 2008 0.04 0.09 2008 0.22 0.59 2009 0.01 0.01 2009 0.35 0.27 2010 0.01 - 2010 0.07 - 2011 0.05 - 2011 0.12 - 2012 - - 2012 - -
Long-term commitment rates for 3 to 5 years are measured by the average of all
committed purchase amounts for 3 to 5 years ahead from 2000 to 2012 for each
airline corporation in terms of capital expenditures, asset values and physical
properties, plants and equipment correspondingly. The commitment sums are
documented in millions. Table underneath gives a lumpy picture of long-term
commitment rate for 3 to 5 years for each airline corporation in terms of those
three traits. From this table, noteworthy outliers, e.g. US Airways Group Inc, can
directly be spotted and can be overlooked at least some of the outliers in the
forthcoming computation and discussion to reduce the biasness and endure a
reasonable picture.
Corporations Long Term Commitment Rates (3-5 Years) in terms of Capex Assets PPENT Airtran Holdings Inc 1.40 0.02 0.03 Alaska Air Group Inc 0.76 0.06 0.10 Alaska Airlines Inc 0.10 0.01 0.02 American Airlines Inc 0.88 0.04 0.05
AMR Corp 1.37 0.06 0.09
Delta Airlines Inc 0.60 0.03 0.04 Expressjet Holdings Inc 3.73 0.23 0.32 Hawaiian Holdings Inc 0.36 0.04 0.09 Jetblue Airways Corp 3.84 0.21 0.29 Midwest Air Group Inc 0.03 0.01 0.00 Northwest Airlines Corp 6.22 0.14 0.12 Pinnacle Airlines Corp 0.04 0.00 0.00 Republic Airways Holdings Inc 0.08 0.00 0.00 Skywest Inc 0.08 0.01 0.01 Southwest Airlines 0.75 0.08 0.08 United Airlines Inc 2.37 0.07 0.10 United Continental Holdings Inc 1.42 0.03 0.05 US Airways Goup Inc 6.63 0.45 0.71
Once grinding the committed purchase figures in terms of capital expenditures,
which are traditional indicators, the average of committed purchase figures is
0.90. Using this as the breakpoint, distribution of airline corporations with above
and below average committed purchase in terms of capital expenditures is
revealed below.
Above Average Below Average Airtran Holdings Inc Alaska Air Group Inc Expressjet Holdings Inc Alaska Airlines Inc
Jetblue Airways Corp American Airlines Inc Northwest Airlines Corp AMR Corp
Pinnacle Airlines Corp Delta Airlines Inc United Airlines Inc Hawaiian Holdings Inc United Continental Holdings Inc Midwest Air Group Inc
US Airways Group Inc Republic Airways Holdings Inc Skywest Inc
Southwest Airlines
Pondering committed purchase sums in terms of values of physical properties,
plants and equipment, it is recapitulated in the graph underneath. This graph
neglects an outlier, i.e. US Airways Group Inc, whose data sets are drastically
skewed. The committed purchase amounts are gauged in millions. It reveals the
macro economic condition from 2000 to 2012 quite precisely. As for committed
purchase in 1 year, there were two peaks, in 2002 and 2008 respectively, which
were the moment right before the two major financial crises from 2000 to 2012.
As for committed purchase in 3 to 5 years, there was barely one peak, which was
in 2003. Since it is a universal theory that an economic cycle takes approximately
a decade so economy ordinarily recovers within half decades. The period of 2002
to 2003 being an economy trough due to dot com recession, it was
comprehensible that committing some purchase at a comparatively lower price 3
to 5 years beforehand at economy trough may be a rational choice. Additionally,
the economy was of extraordinary prospect getting recuperated so as economy
activities in 3 to 5 years’ time. Accordingly, the investment in 2002 to 2003
would be of noteworthy worth adding to the income sheet and balance sheet of
those corporations in the sense that those committed purchases are
indispensable to have business profitable and preferably in a more efficient way.
In order to further apprehend the committed purchase figures, the outline of
scope and the tendency of such commitment would be crucial. The following
table demonstrations the symptomatic percentile breakdown of commitment
amounts in terms of three classes, i.e. capital expenditures, asset values, and
values of physical properties, plants and equipment respectively, with
corresponding standard deviations.
in terms of years ahead mean median min Q1
Q3 max SD
Capex
1
1.75
1.09
0.09 0.69 2.16 6.47 1.84
2
1.08
0.79
0.05 0.52 1.03 4.02 1.05
3
0.71
0.41
0.01 0.10 0.98 2.42 0.75
4
0.57
0.24
0.00 0.01 0.67 2.96 0.84
5
0.42
0.15
0.00 0.01 0.54 1.76 0.57
2
0.07
0.03
0.00 0.02 0.05 0.45 0.11
3
0.03
0.02
0.00 0.01 0.03 0.16 0.04
4
0.03
0.01
0.00 0.00 0.03 0.17 0.04
5
0.02
0.01
0.00 0.00 0.02 0.12 0.03
PPENT
1
0.12
0.07
0.02 0.04 0.12 0.73 0.16
2
0.08
0.05
0.00 0.03 0.10 0.44 0.10
3
0.05
0.04
0.00 0.02 0.05 0.28 0.07
4
0.04
0.02
0.00 0.00 0.03 0.26 0.06
5
0.03
0.01
0.00 0.00 0.02 0.16 0.04
For better illustration, the statistics overhead is plotted into three percentile
charts as presented underneath.
The following bar chart exhibits the revealing percentiles of committed purchase
quantities in terms of capital expenditures for 1 to 5 years in advance separately.
It is vibrant that all the indicative percentiles have declining trend as
commitment years upsurge. Farther, the scope of committed purchase amount in
terms of capital expenditures shrinks as number of committed years increases.
This is sensible since the lengthier the committed years, the more the
uncertainty it may have and hereafter the littler the amount of investment to
make to minimize the threats.
Equally, the following percentile diagram displays the commitment purchase
amounts in terms of assets values with respect to the number of years in
advance. The committed purchase amounts for short term, say 1 to 2 years, is
considerably greater than those for long term, say 3 to 5 years. Moreover, all the
symbolic percentiles diminish progressively alongside the upsurge of number of
committed years in advance. Equivalent philosophy smears that airline industry
is an industry extremely influenced by economy conditions. If there is an
economy prosperous, business expansion is more probable to happen and
henceforward there are more business trips. Similarly, people are more
enthusiastic to spend money on travelling during economic upturn. With lots of
improbability to the economy development, it is understandable the investment
were majorly emphasized in short term.
Comparable to the commitment purchase figures in terms of capital
plants and equipment shown by all symbolic percentiles as the number of
commitment years escalates. Analogously, this can be enlightened by the
cumulative jeopardy of commitment purchase alongside the growths in
uncertainties along with number of years committed beforehand.
Following analyzing the committed purchase figures collected from 10-K
company filings through US Securities and Exchange Committee website, the
total commitments quantities can be reviewed as the diagram below to have a
clearer picture. The commitment amount reaches the topmost in 2011 and
dwindled progressively from that. The economy boom in mid 2000s can
explicate the snowballing drift of commitment amount and airlines corporations
committed the most in around 2008 for three to five years ahead. After the
financial crisis during 2008, due to the constricted capital sources and all sources
of financial pressure, the investment tactics, counting committed purchase,
cutbacks steadily.
Analysis-Regression Analysis
Regarding having an overall picture of commitment purchase for airline industry
from 2000 to 2012, this research paper would like to emphasize further on the
financial crisis in 2008 and consequently an additional surveillance for pre- and
post – financial crisis on the commercial activities from 2006 to 2011 was
created. As in business activities, there are three areas this research paper would
like to concentrate on, explicitly cost of goods sold, advertising expenses, and
expenses on selling, general and administration.
In order to investigate on these three parts, regression tests were executed.
Dependent variables are the three cited above in terms of total asset values. As
for control variables, there are two sorts, i.e. binary ones and non-binary ones.
Binary ones comprises treatment, post crisis and post crisis with treatment.
Non-binary ones embraces log of assets, Tobin’s Q and log of stock return from 1 and
capital in terms of replacement cost of capital. Market value is corresponding to
the market values of equity and liabilities whereas replacement cost of capital is
comparable to the book values of equity and liabilities. Figures required for
regression was originated in the annual reports of those airline corporations,
disregarding 3 outliers, and Compustat database. All of the regression tests were
generated from eViews.
For each dependent variable, two regression tests were accomplished. One is
with all propositioned control variables and another one is with merely binary
control variables. Therefore, there were six regression tests produced. Due to the
incompleteness of statistics, the amounts of observation for those with all
suggested control variables are smaller than those with barely binary control
variables. However, the number of observation for each case is still large enough
to generate a moderately impartial outcome.
This research paper will focus at 10% confidence level, i.e. 5% of the total
distribution in each side of the tail, as a two-sided test. For t-statistics, the null
hypotheses are the betas of control variables are 0 whilst the alternative
hypotheses are betas of control variables are not 0.
-Cost of Good Sold in terms of Total Assets with All Control Variables
Cost of good sold is expected to have negative relationship with the interaction
term coefficient since cutting cost of good sold will save money for the business
and probably alleviate the financial stress.
When we look at the t-statistics, the required critical value for 61 observations is
around ±1.671. T-statistics of all control variables lay in the rejection region.
Consequently, null hypotheses are rejected. That implies betas of control
variables are not 0.
square and adjusted square are significantly far from 1. Contemplating
R-square, it signifies that just 26% of the dependent variables are enlightened by
the tested control variables. This entails the dependent variables don’t lie much
on the fitted regression and the model doesn’t fit the data well enough.
Dependent Variable: COGS_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:11 Sample: 1 90
Included observations: 61
Variable Coefficient Std. Error t-Statistic Prob.
C 0.932626973 0.49156146 1.897274398 0.063245722 LOG_OF_ASSETS -0.095304714 0.036469188 -2.613294076 0.011645252 LOG_STOCK_RETURN_FROM_1_ -0.195654061 0.084733632 -2.309048434 0.024869675 LOG_STOCK_RETURN_FROM_2_ -0.045294703 0.089135391 -0.508156217 0.613452364 TOBIN_S_Q 0.545411755 0.239627897 2.276077877 0.026908469 TREATMENT -0.134063679 0.126635917 -1.058654468 0.294558363 POSTCRISIS -0.039597158 0.130947768 -0.302388947 0.763539142 TREATMENT_X_POSTCRISIS 0.120337081 0.163255759 0.73710772 0.464307559
Adjusted R-squared 0.173556462 S.D. dependent var 0.341891943 S.E. of regression 0.310810341 Akaike info criterion 0.622445422 Sum squared resid 5.119962618 Schwarz criterion 0.899281339 Log likelihood -10.98458537 Hannan-Quinn criter. 0.730940012 F-statistic 2.80003442 Durbin-Watson stat 1.596503664 Prob(F-statistic) 0.014806017
-Cost of Good Sold in terms of Total Assets with Binary Control Variables Only
Regression result and related graphs from eViews are presented below.
Cost of good sold is expected to have negative relationship with the interaction
term coefficient since cutting cost of good sold will save money for the business
and probably alleviate the financial stress.
When we look at the t-statistics, the required critical value for 87 observations is
around ±1.663. All of the control variables lie in the acceptance region. This
principally advocates that those control variables may explicate the variations of
the dependent variable.
To check if the proposition above is effective, R-square and adjusted R-square
may contribute some insight. R-square and adjusted R-square are suggestively
far from 1. R-square indicates that barely 1-2% of the dependent variables are
illuminated by the tested control variables. On the other hand, adjusted R-square
is even negative. This infers the dependent variables don’t lie much on the fitted
regression and the model fits the data extremely inadequately.
Dependent Variable: COGS_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:17 Sample: 1 90
Included observations: 87
Variable Coefficient Std. Error t-Statistic Prob.
C 0.764976122 0.067599368 11.31632062 1.68E-18 TREATMENT -0.019379968 0.092564247 -0.20936775 0.834674193 POSTCRISIS -0.104270721 0.095599943 -1.09069857 0.278561811 TREATMENT_X_POSTCRISIS 0.064897417 0.133069489 0.487695694 0.627051165
R-squared 0.016790094 Mean dependent var 0.720279305 Adjusted R-squared -0.018747613 S.D. dependent var 0.306915612 S.E. of regression 0.309779221 Akaike info criterion 0.538972726 Sum squared resid 7.96494275 Schwarz criterion 0.652347812 Log likelihood -19.4453136 Hannan-Quinn criter. 0.584625377 F-statistic 0.472458558 Durbin-Watson stat 2.244404769 Prob(F-statistic) 0.702298068
-Advertising Expenses in terms of Total Assets with all Control Variables
Regression result and corresponding graphs from eViews are exhibited below.
Advertising expenses is expected to have negative relationship with the
interaction term coefficient since cutting advertising expenses will save money
for the business and probably alleviate the financial stress.
When we look at the t-statistics, the essential critical value for 46 observations is
around ±1.679. Some of the control variables, more specifically log of stock
return from 1 and 2 years, post-crisis and post-crisis with treatment, lie in the
acceptance region. This predominantly insinuates that the control variables
stated above may illuminate the deviations of the dependent variables.
To investigate whether the idea above is binding, square and adjusted
R-square may offer some understanding. R-R-square and adjusted R-R-square are
somewhat far from 1. Seeing R-square, it signposts that approximately half of the
dependent variables are expounded by the examined control variables. This
denotes the dependent variables may fit abstemiously on the fitted regression
and the model may fit the data in some sense.
Dependent Variable: ADVERTISING_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:13 Sample: 1 90
Included observations: 46
Variable Coefficient Std. Error t-Statistic Prob.
C 0.037123705 0.01191243 3.116383983 0.003478697 LOG_OF_ASSETS -0.004065422 0.0009159 -4.438718195 7.53E-05 LOG_STOCK_RETURN_FROM_1_ -0.001710939 0.001548858 -1.104645513 0.276258827 LOG_STOCK_RETURN_FROM_2_ -0.000385615 0.001499903 -0.257093183 0.798493861 TOBIN_S_Q 0.010515376 0.004133834 2.543734087 0.015157061 TREATMENT -0.008902939 0.002742011 -3.246864661 0.002440021 POSTCRISIS -0.001094755 0.002028889 -0.539583554 0.592632257 TREATMENT_X_POSTCRISIS 0.000604875 0.00242808 0.24911646 0.804612314
R-squared 0.540003839 Mean dependent var 0.007683838 Adjusted R-squared 0.455267704 S.D. dependent var 0.005028422 S.E. of regression 0.003711276 Akaike info criterion -8.198110917 Sum squared resid 0.000523396 Schwarz criterion -7.880086326 Log likelihood 196.5565511 Hannan-Quinn criter. -8.078976999 F-statistic 6.372769293 Durbin-Watson stat 3.031396075 Prob(F-statistic) 5.50E-05
-Advertising Expenses in terms of Total Assets with Binary Control Variables
Only
Regression calculation and related graphs from eViews are publicized below.
Advertising expenses is expected to have negative relationship with the
interaction term coefficient since cutting advertising expenses will save money
for the business and probably alleviate the financial stress.
When we look at the t-statistics, the required critical value for 66 observations is
around ±1.669. All of the control variables lie in the acceptance region. This
principally advocates that the control variables may elucidate the variations of
the dependent variable.
To examine whether the recommendation overhead is acceptable, R-square and
adjusted R-square may provide some insight. R-square and adjusted R-square
are notably far from 1. R-square hints that merely 4% of the dependent variables
are justified by the tested control variables. On the other hand, adjusted
R-square is even negative. This entails the dependent variables don’t lie much on
the fitted regression and the model fits the data very incompetently.
Dependent Variable: ADVERTISING_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:16 Sample: 1 90
Included observations: 66
Variable Coefficient Std. Error t-Statistic Prob.
C 0.007555939 0.001320319 5.72281397 3.26E-07 TREATMENT -0.000239291 0.001686486 -0.14188703 0.887629294 POSTCRISIS -0.000294466 0.001799291 -0.163656602 0.870533806 TREATMENT_X_POSTCRISIS -0.001660685 0.002309671 -0.719013726 0.47483379
R-squared 0.04281061 Mean dependent var 0.006726358 Adjusted R-squared -0.003505006 S.D. dependent var 0.004565724 S.E. of regression 0.004573719 Akaike info criterion -7.878288593 Sum squared resid 0.001296972 Schwarz criterion -7.745582245 Log likelihood 263.9835236 Hannan-Quinn criter. -7.825850008 F-statistic 0.924323456 Durbin-Watson stat 2.524111111 Prob(F-statistic) 0.434413017
-Expenses for Selling, General and Administration in terms of Total Assets with
All Control Variables
Regression outcome and corresponding graphs from eViews are displayed
beneath.
Expenses for selling, general and administration is expected to have negative
relationship with the interaction term coefficient since cutting these expenses
will save money for the business and probably alleviate the financial stress.
When we look at the t-statistics, the necessitated critical value for 51
observations is around ±1.676. All of the control variables lie in the acceptance
region. This largely advises that the control variables may enlighten the
To scrutinize if the proposition above is endorsed, square and adjusted
R-square may give some comprehension. R-R-square and adjusted R-R-square are
appreciably far from 1. R-square indicates that only 16% of the dependent
variables and adjusted R-square indicates merely 2% of those are illuminated by
the tested control variables. This infers the dependent variables don’t lie much
on the fitted regression and the model fits the data scantily.
Dependent Variable: XSGA_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:14 Sample: 1 90
Included observations: 51
Variable Coefficient Std. Error t-Statistic Prob.
C 0.012595877 0.11944592 0.10545255 0.916507116 LOG_OF_ASSETS 0.000179979 0.009594935 0.018757722 0.98512109 LOG_STOCK_RETURN_FROM_1_ -0.022867371 0.016230723 -1.408894187 0.166057085 LOG_STOCK_RETURN_FROM_2_ -0.007846065 0.017835501 -0.439912783 0.662203552 TOBIN_S_Q 0.057859405 0.045910352 1.260269257 0.21436872 TREATMENT 0.025131668 0.026019761 0.965868531 0.339511036 POSTCRISIS 0.005134342 0.022261562 0.230637091 0.818690576 TREATMENT_X_POSTCRISIS 0.010099747 0.027083672 0.372909071 0.711048087
R-squared 0.162439422 Mean dependent var 0.106760763 Adjusted R-squared 0.026092351 S.D. dependent var 0.045050889 S.E. of regression 0.044459262 Akaike info criterion -3.245386878 Sum squared resid 0.084994919 Schwarz criterion -2.942355406 Log likelihood 90.7573654 Hannan-Quinn criter. -3.12958959 F-statistic 1.191367152 Durbin-Watson stat 2.372173333 Prob(F-statistic) 0.328070023
-Expenses for Selling, General and Administration in terms of Total Assets with
Binary Control Variables Only
Regression upshot and related graphs from eViews are presented below.
Expenses for selling, general and administration is expected to have negative
relationship with the interaction term coefficient since cutting these expenses
will save money for the business and probably alleviate the financial stress.
When we look at the t-statistics, the required critical value for 76 observations is
around ±1.665. All of the control variables lie in the acceptance region. This
mostly proposes that the control variables may describe the variations of the
dependent variable.
To inspect whether the proposal above is acceptable, square and adjusted
R-square may give some insight. R-R-square and adjusted R-R-square are ominously far
from 1. R-square indicates that only 6% of the dependent variables and adjusted
R-square indicates that barely 2% of the dependent variables are explicated by
the tested control variables. This denotes the dependent variables don’t lie much
on the fitted regression and the model fits the data feebly.
Dependent Variable: XSGA_TOTAL_ASSET Method: Least Squares
Date: 08/21/14 Time: 15:15 Sample: 1 90
Included observations: 76
Variable Coefficient Std. Error t-Statistic Prob.
C 0.085683798 0.012196795 7.02510783 9.94E-10 TREATMENT 0.022943277 0.015745994 1.457086574 0.149440145 POSTCRISIS 0.017839762 0.017533997 1.017438402 0.312351678 TREATMENT_X_POSTCRISIS -0.004570063 0.022802586 -0.200418612 0.841718242
R-squared 0.06621741 Mean dependent var 0.106456266 Adjusted R-squared 0.027309802 S.D. dependent var 0.049467326 S.E. of regression 0.048787179 Akaike info criterion -3.15150246 Sum squared resid 0.171373594 Schwarz criterion -3.028832284 Log likelihood 123.7570935 Hannan-Quinn criter. -3.102477524 F-statistic 1.70191419 Durbin-Watson stat 2.168405634 Prob(F-statistic) 0.174251721
