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Advances in Social Sciences Research Journal – Vol. 10, No. 2
Publication Date: February 25, 2023
DOI:10.14738/assrj.102.13910. Jarrett, E. J. (2023). The Influence of the Pandemic on Decisions Occuring During the Last Few Years. Advances in Social Sciences
Research Journal, 10(2). 219-229.
Services for Science and Education – United Kingdom
The Influence of the Pandemic on Decisions Occuring
During the Last Few Years
Jeffrey E. Jarrett, PhD
Professor Emeritus, University of Rhode Island (COB)
Abstarct
The notion that presents value of cash flows is often improperly estimated in
financial models concerning capital improvements and abandonments is a
fundamental problem in decision analysis in management and associated
decisions and affects estimation of and valuation of intellectual property.
Previous studies indicate the usefulness of estimation theory in financial in
financial accounting. During the Covid Pandemic of the past few years
decisions by governmental and health authorities in the United States and
the World were often dictatated during the Pandemic by short-term political
influences which included disinformation by some who wished to rake
advantage of the misuse of the health Pandemic for political gain and/or
financial power and short-term financial gain. Previously this was shown to
be true as the media with the aid of self-promotional activities by many who
were attempting this kind of gain. Furthermore, the Pandemic in the United
States and other nations is receding in drfamatic ways and many restrictions
of the Endemic era are nolonger in use. This was the result of Mask
restrictions and increasing but not universal vaccine programs many states
and nations.
Keywords: abandonment, estimation theory, present value of cash flow,
distribution of earnings, normal fiducial deviate, opportunity loss
INTRODUCTION
Financial researchers such as Deschow (1994; Deschow and Strand, 2004) indicated that
employing accrual-based accounting methods creates the capability of accounting-based
earnings projections to control and continuously improve the measures of firm performance
reflected in analysts’ earnings forecasts. The argument was that cash flow accuracy is expected
to suffer from matching, realization, and other timing problems concerning the timing of the
recognition of costs and revenues. Accuracy of financial earnings predictions was studied by
Brandon and Jarrett (1974), Jarrett (1983, 1992), Jarrett and Khumawala (1987), and Lambert,
Matolcsy, and Wyatt (2015). They compared methods of predicting earnings seeking to learn
how forecast models can be compared and possibly improved to produce more accurate results
as to cash flow. Questions posed included sources of accuracy, but accrual accounting alone was
not considered the most important source of inaccurate results. However, no one established a
theoretical link between sources of inaccuracy and the matching principle and the accuracy of
financial analysts’ forecasts although many studied the problem (Jarrett, 1989, 1990); Clement,
1999; Gu and Wu, 2003; Ramnath, Rock, and Shane, 2008; Grosyberg, Healy, Nohria, and
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Serafeim, 2011). Accounting reports containing these forecasts of cash flow and rates of return
are, in addition, subject to fluctuations in the interpretation of timing principles utilized by
accountants. However, Gu and Wang (2005) brought up the possibility of another source of
inaccuracy in the forecast of rates of return, cash flow, and earnings. Beneish, Lee, and Nichols
(2013) created a model that uses financial ratios calculated with accounting data of a specific
company to check if it is likely that the reported earnings for a firm were manipulated—the
goal being to estimate earnings better in financial reports. Last, Lev and Gu (2016) in their study
produced evidence from large-sample empirical analysis that financial documents continuously
deteriorate in relevance to investors’ decisions. Further, they detail why accounting reporting
is losing relevance in today’s decisions related to capital budgeting and the abandonment
option.
Note that decisions about abandonment and salvage utilize normal capital budgeting methods
to determine whether there is a relation among the various capital budgeting options, financial
leverage, and financial estimation by analysts. Illustrating capital budgeting with the
abandonment option; allows us to implement and illustrate how corporations utilizing capital.
Alternatively one learns and understands that budgeting processes are dynamic and subject to
alteration, involving the information flow throughout the organization or agency that
determines the investment and abandonment decisions at individual stages. With this in mind,
one may examine how an abandonment option influences the optimal timing of information. In
particular, one may compare timely information, where the manager acquires perfect
precontract project information. We examine how the future revenues from intangible and
intellectual assets may affect the level of financial leverage of a firm when not all is known about
the monetary value of assets which have not tangible definitions. During a Pandemicthis
information is vital but at the ending of the Pandemic this become less important rapidly.
In the absence of real options, the following trade-off arises: If information is timely the
investment or business decision can be based on perfect information concerning rates of return
and earnings per share, . Alternatively, if information about intangible assets is not considered
in the abandonment option, the timing and decision concerning the abandon option may very
well be estimated incorrectly. The incorrect information is the product of the misreporting of
factual events associated with intangible assets, and the error associated with incorrect
analysts’ forecasts and become poor decisions apply it to the relation of analysts’ forecasts and
the bias in estimating earnings and cash flow present in evaluating capital decisions. This will
increase in the world of misinformation
APPLICATION OF CAPITAL BUDGETING METHODOLOGY
Berger, Ofek, and Swary (1996) established the link among analysts’ forecasts, cash flow, the
expected capital asset pricing model (CAPM) return, and the present value of cash flow, which
includes forecasts of earning rather than the distributable cash flow. In addition, Wong (2009)
examined the relation between the abandonment and other alternatives potential effect on a
firm’s decision analysis and the eventual analytics employed to determine the optimal decision
and operating leverage. Furthermore, mcdonald (2003) analyzed abandonment options,
divestment options, expansion options, and growth options previously examined in a survey by
Triantis and Borison (2001). These and many more studies revealed that they use real options
to the general problems associated with capital budgeting.
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Jarrett, E. J. (2023). The Influence of the Pandemic on Decisions Occuring During the Last Few Years. Advances in Social Sciences Research Journal,
10(2). 219-229.
URL: http://dx.doi.org/10.14738/assrj.102.13910
Analysts’ earnings forecasts enable analysts to estimate the present value of cash flow (PVCF).
According to Berger, Ofek, and Swary (1996), the advantage is that analysts’ forecasts of
earnings do not incorporate the value of the abandonment option. If forecasts of distributable
cash flows, cash flows from non-ongoing concern events would be included in the forecasts.
Thus, earnings may not be the same as cash flows. Hence, we adjust because capital
expenditures are not equivalent to depreciation and the growth in working capital is not
subtracted from earnings. No longer is it required to adjust for capital structure changes in the
environment that such changes cannot be foreseen. Borrowing again from Berger, Ofek, and
Swary (1996), their equation constructs the present value of capital formation (PVCF) that
evolves from the analyst’s discounted forecasts. Included in the equation is the sum of the
present value of analysts’ predicted going-concern cash flows discounted by analyst forecast of
year t after-interest earnings and expected CAPM (capital asset pricing model return),
consensus forecast of five-year earnings growth, the terminal growth rate of earnings, the
number of years for which earnings are forecast, and a year index. The CAPM adjustment
includes the reduction to the present value of analysts’ earnings. The second adjustment to
PVCF is the working capital adjustment, which is a reduction to the present value of analysts’
earnings forecasts to adjust for growth in working capital. Finally, the expected CAPM return is
defined as
R = rf + βe * [rm – rf], (1)
Where rf is the risk-free rate, βe is the firm’s beta or systematic risk (from the CRSP beta file),
and (rm – rf) is the risk premium of the stock market minus the risk-free rate.
In implementing Equation (1), we assume that the relevant investment horizon is short term.
Therefore, a useful solution is to use the one-month Treasury-bm rate as a proxy for the risk- free rate and a risk premium (the arithmetic mean from a long period of time from between the
return on the S&P 500 and the return on Treasury bills).
The problem with the above approach is the variable the analysts’ forecasts of earnings. In part,
this is a solution to the problems noted by Pappas (1977) in response to the work by Brief and
Owen (1968, 1969, 1970, 1977; Barnea and Sadan, 1974; Jarrett, 1983, 1992), who used their
work in developing models to adjust analysts’ earnings forecasts in evaluating the abandonment
option. Studies concerning analysts’ forecasts are well known and include a huge number. In
general, as stated by many in the field of financial accounting, earnings forecasts are dependent
on the principles of financial accounting that produce the data for modeling trends and
seasonality (or modeling components). The accuracy of analysts’ forecasts has a long history
and includes works by Clement (1999), Gu and Wu (2003), Ramnath, Rock, and Shane (2008),
Groysberg, Healy, Nohria, and Serafeim (2011), and Makridakis, Spiliotis, and Assimakopoulos
(2017). The last paper suggested that machine learning models may have better results than
self-prepared models for forecasting. The aforementioned studies focused on a relation
between analysts’ forecasts and the magnitude and value of intangible assets. Intangible assets
were not considered in the forecasting method discussed by the researchers in their many and
detailed studies. The value of intangible assets produces a great source of error if they are not
considered in the forecasting methods utilized by analysts in the production of cash flow, rates
of return and earning per share (EPS) forecasts. When adjustments for intangible assets are
included in the analysts’ forecasts, Gu and Wang (2005, p. 673) stated that“the rise of intangible
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assets in size and contribution to corporate growth over the last two decades poses an
interesting dilemma for analysts. Most intangible assets are not recognized in financial
statement, and current accounting rules do not require firms to report separate measures for
intangibles.” Intangibles include trademarks, brand names, patents, and similar properties that
have value but are generally not listed in the financial reports of firms. Many of these items are
technology based and are very important in financial decisions such as in mergers and
acquisitions (M&A). They are an intricate part of the growth of firms and therefore are shown
to be related in the statistical sense to the overall estimates made by accounting and analysts.
In another study concerning analysts’ forecasts, Matolcsy and Wyatt (2006) found that an
association between EPS forecast, growth rates forecast error, and measures of technological
conditions in the firm’s industry. They found that as the forecast horizon increases, the
technological conditions and current EPS are statistically associated with analysts’ forecasts.
Long horizon creates the conditions for within one to conclude that interactions between
technological conditions and current EPS are associated with analysts’ EPS and growth
forecasts. This conclusion aligns itself with Jung, Shane, and Yang (2012), who suggested that
analysts’ growth forecasts effect efforts to evaluate analysts’ forecasts may produce
optimistically biased long-term forecasts. Because intangible assets that are often technology
based take up more of the balance sheet of many firms, it is likely that analysts’ forecasts may
produce less accurate predictions of earnings, cash flow, and rate of return. The conclusions of
Deschow (1992) become less important. Balance sheets usually have little or no involvement
with the value of intangibles, although there are some practices by accounting that are still used.
Thus, in the remaining portions ofthis analysis, we propose a method by which one can estimate
earnings such that the value of intangible assets is valued and earnings estimate are not biased
by serious errors of omission such that the capital budgeting model expressed earlier in
equations by Berger, Ofek, and Swary (1996, p. 264) are not unduly biased.
INTELLECTUAL PROPERTY AND TRADITIONAL ACCOUNTING
As noted by Brief and Owen (1969, 1970, 1977), Jarrett (1971, 1974, 1983), Roberts and
Roberts (1970), and Barnea and Sadan (1974), the timing of recognition of revenue for
intellectual property rights (IPR) in financial statements of ten are not featured in merger-and- acquisition activity. The Financial Accounting Standards Board (FASB) provides for such
activities; however, they are often ignored due to their evasiveness or are not fully informational
in their normally structured rules. Recognizing future performance is a goal of matching and
timing but are unrelated to recognizing cash flow and similar items in the historical
performance of a firm. Nonprofit entities often do not use accrual rules at all because the goal
of these are related to achieving high rates of return. Often IPR for nonprofits would differ from
the same item for profit-maximizing entities because the goal of seeking high rates of return
does not enter the strategic planning process for nonprofits (World Trade Organization, 2016).
The purpose here is to consider intellectual property (IP) as intangible assets, as a product of
intellect that law protects from unauthorized use by those not responsible for the IPR. Hence,
IPR are characterized as the protection of distinguished signs such as trademarks for goods and
services, patents, and other similar items that are under protection from unauthorized use. This
includes art, music, creations by authors including the authorship of computer software, and
similar items such as discoveries, inventions, phrases, symbols, and design. Obviously, a writer
and conductor of music such as Leonard Bernstein and Daniel Barenboim would have created
IP that differ greatly from physicists such as Lise Meitner, Niels Bohr, or Albert Einstein.