growth Easton 2004; Botosan and Plumlee 2005; Dhaliwal et

growth
companies because they face more uncertainty and hence are risky. Finally, we
control for earnings quality using discretionary accruals (DACC) derived from
XXX greenwashing is lower for firms with more analysts
following. This association is also positive for and We use the number of analyst following a firm, forecast
dispersion (FD), measured as the standard deviation of analysts’ 1-year-ahead
earnings per share (EPS) forecasts as proxies for the information environment, and
long term growth (LTG), hypothesizing that the association between risk premium

Previous studies
show that the implied cost of capital is correlated with a bunch of variables
that might affect the cost of equity capital (such as Gebhardt et al. 2001;
Gode and Mohanram 2003; Botosan et al. 2004; Easton 2004; Botosan and Plumlee 2005;
Dhaliwal et al. 2005; Easton and Monahan 2005; Hail and Leuz 2006). These controls
include: beta (BETA), by regressing 60 monthly excess stock returns ending in
June of year t on the corresponding monthly CRSP value-weighted index excess
returns; leverage (Lev), estimated as the ratio of total debt to the market
value of equity; size (Size) computed as the natural logarithm of total assets;
book to market ratio (BTM); and return on assets (ROA), measured as income
before extraordinary items in year t scaled by total assets at the end of year
t – 1.

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Control Variable:

 

In Ohlson and
Juettner?Nauroth model, the implied cost of equity capital is based on abnormal
earnings growth. The model is a generalization of the Gordon constant growth model
with two growth rates (the 5 year EPS growth rate and 1+terminal growth rate). An
extension of Ohlson and Juettner?Nauroth model, Easton (2004) generates the
Price Earnings Growth (PEG) model. The author estimates the implied cost of
equity premium from the abnormal earnings growth model using only current
prices, expected dividends (divt+1), and earnings estimates. Appendix B provides
details on the implementation of the four models.

Claus and Thomas
(2001), Gebhardt, Lee, Swaminathan (2001) and Easton, Taylor, Shroff and
Sougiannis (2002) use a model of corporate valuation to generate a market implied
cost of equity capital for a particular firm and they do not rely on
historically realized returns.

Claus and Thomas
(2001) and Gebhardt et al. (2001) derive the implied cost of equity capital
based on the residual income valuation model. This measure is a function of
several exogenous variables such as the industry characteristics, the book to
market ratio, the expected long-term interest rate, and analyst forecast dispersion
of future firm’s cash flow. Most of these measures are stable over the long
term and can be valued ex ante, so they can provide a good estimate of the
perceived business risk of investors.

There are
controversies about how to measure cost of equity capital (Hope at al., 2009;
Francis et al., 2004).  We will use four
models: two implementations of the Ohlson (1995) residual income valuation
model, the abnormal earnings growth model of Ohlson and Juettner?Nauroth (2005),
and the PEG model as implemented by Easton (2004).  Each measure identifies the internal rate of
return that equates expected future earnings and current stock price using a
different expectation model. We also use an aggregate measure, which takes the averages
of these four individual measures.

 

Independent Variable:

 

Selective
disclosure magnitude approaches its maximum value of 1 when a company discloses
few of its more harmful indicators and discloses many of its less harmful
indicators. This type of company engages in environmental misleading action and
the impression of transparency while in the real world hiding quite a lot. however,
when a company disclosing only the few relevant indicators that really matter
in terms of its environmental damage will have a selective disclosure magnitude
tending toward the minimum value of .1.

In a further step,
the weighted disclosure ratio includes the extent of environmental impact or
the environmental harm associated with each environmental indicator. In other
words, this ratio will emphasize how much of the most important information was
disclosed. For example, for every dollar of economic output, Trucost estimates
the natural resources consumed and the emission released for each environmental
indicator based on transfer registries and several pollution releases.

Briefly, the
absolute disclosure ratio measures the proportion of relevant environmental
indicators for which a company publicly discloses in a given year (how many did
a company discloses?). The denominator of this ratio is the number of
environmental indicators relevant to a particular company. These indicators
include consumption of natural resources (such as natural gas, oil and water)
and emissions of various pollutants to land, air, and water. Using annual
reports, corporate social responsibility reports, website, Trucost defines the
number of these indicators that the company publicly discloses which constitute
the numerator.

This estimation is
aligned with Lyon and Maxwell (2011), given their conclusion that greenwash is
a form of selective disclosure by disclosing relatively benign environmental
metrics rather than those more representative of their overall environmental
harm. When a company’s symbolic transparency environmental issues exceed the
substantive transparency issues, which indicates that companies have incentives
to exaggerate their environmental accomplishments through their information
disclosure strategies by enjoying talking about symbolic communications of
environmental issues without substantially addressing them in actions.

Our dependent
variable, selective disclosure magnitude, captures the extent to which
companies risk creating a misleading impression transparency about their
environmental image (Delmas and Burbano 2011, Kim and Lyon 2011, Lyon and
Maxwell 2011, Bowen 2014).  Greenwashing
is a form of selective disclosure measured by the difference between two
ratios; that is, absolute disclosure ratio (Symbolic transparency) and weighted
disclosure ratio (substantive transparency).

 

Dependent Variable:

 

These models are
discussed below and summarized in Appendix A.

To examine the
relation between Greenwashing and the level of cost of equity, we begin by
merging four databases: Compustat North America, which provides financial data,
Thomson Institutional Brokers Earnings Services (I/B/E/S), which provides
analyst forecast data, Trucost (created and maintained by Trucost Plc., an
organization established in 2000), which provides environmental impacts of company
operations, supply chains, and investment portfolios, and CRSP monthly return
files, which provide information on stock returns. A key research design issue
in this study is to develop a reliable proxy for greenwashing. To do so, we construct
our measures of selective disclosure and environmental damage, as described
below. Greenwashing (GW), will be measured by the selective disclosure
magnitude. Selective disclosure magnitude represents the extent to which
companies risk creating a misleading impression of transparency and
accountability by disclosing relatively benign environmental metrics rather
than those more representative of their overall environmental harm. This is a
form of greenwashing because it involves a company conveying accurate but
selective environmental information that creates a misleading impression of its
overall environmental performance (Lyon and Maxwell 2011, Bowen 2014). We
follow Gebhardt et al. (2001) and Dhaliwal et al. (2006) and compute the cost
of equity in June of each year. To do so, we extract from the I/B/E/S summary
file forecast data recorded in June for all firms that have positive 1- and 2-year-ahead
consensus earnings forecasts and a positive long-term growth forecast. For
further specification, we require that Compustat report a positive book value
per share and we also require that I/B/E/S provide a share price as of June, and
that the firm belong to one of the Fama and French (1997) 48 industries. We
then follow Hail and Leuz (2006) and Dhaliwal et al. (2006) and estimate the
cost of equity capital using four models.