Alternatives from policies of disclosure of companies’

environmental performance & connections with the reduction of information asymmetry and

signalling

Javier Delgado Ceballos (UGR)Alberto Aragón Correa (UGR)George Kassinis (U. Cyprus)

Motivation 1/2

Spread of Pollutant Releases and Transfer Registers around the world

Governments spend a large amount of money on developing them

Firms have to publish their emissions

Env’ information affects financial performance

Motivation 2/2

Information may be not accurate Small installations escape from pressures Large installations (env’ efforts bad

reputation) Divide installations to escape from the

control Questions:

Do these registers signal installations properly?

Whether these registers include operational dynamics information, would it be sent a more accurate signal?

Introduction 1/4

Literature shows stakeholders influence firms environmental behaviour (Kassinis & Vafeas, 2006)

Regulatory stakeholders appear to play the most influential role (Buysse & Verbeke, 2003).

Introduction 2/4

Growing importance of public disclosure policies - Pollutant Release and Transfer Registers (China, México, UE)

Disclosure of installations’ env. emissions pressures firms to improve their env. performance

SO FAR, LITERATURE has not analyzed the potential implications of the information emerging from these registers!!

Introduction 3/4 Governments

Modify firms’ env’ performance Cost Provide information to s/h’s

Reduce info. asymmetry Increase s/h’s pressure to firms

S/H’s & society Focus their pressure Right-to-know

Introduction 4/4

Managers The extent to which firms respond to

stakeholder pressures is a critical concern (Kassinis and Vafeas, 2006; Bansal and Clealland, 2004).

Financial performance (Klassen & Whybark, 1999)

The competitiveness and innovation benefits (King & Lenox, 2002)

Regulatory S/H and the Environment

Stakeholder theory (Freeman, 1984) Community, regulatory,

organizational s/h, and the media (Henriques and Sadorsky, 1999)

S/H regulatory (governments and legislators) Command-and-control methods Market-based incentives (tradable

permits) Environmental information disclosure

PRTRs

Regulatory S/H and the Environment

Stakeholder theory (Freeman, 1984) Community, regulatory,

organizational s/h, and the media (Henriques and Sadorsky, 1999)

S/H regulatory (governments and legislators) Command-and-control methods Market-based incentives (tradable

permits) Environmental information disclosure

PRTRs

PRTRs background

Willingness to know what was happening within industrial plants Public Right-to-know – Bhopal (India)

Existence of environmental information asymmetry between firms and communities Consumers and community are only

partially aware of installations’ env’ behaviour

PRTRs background

PRTRs send signals to s/h’s and markets about installations performance

Signaling theory suggests that key attributes of the firm provide information that shapes the impression that individuals form of the organizations and it can be used to examine firm reputation and its impact on individual behaviours, attitudes and decision making

PRTRs background

S/H’s are increasingly using PRTRs data to measure organizations’ env’ performance (Toffel & Marshall, 2004)

Community s/h are concerned about installations’ env’ info’ released by PRTRs because of the consequences for env’ impacts and human hazards.

PRTRs background

PRTRs rank installations summing annual emissions of substances released by a facility in a given year.

It may be clear that it is a poor and crude proxy to indicate installations env’ performance as it depends on various factors as the chemical’s characteristics and the medium which is release (Toffel & Marshall, 2004)

As a consequence, some researchers (Karam, Craig and Currey, 1991; Toffel and Marshall, 2004) argue that in order to measure installations’ environmental data, it could be appropriate the use of the weighting emissions data using the each PRTRs standard limits or toxicity estimates so that TRI-based measures more accurately reflect real differences

PRTRs background

PRTRs rank installations summing annual emissions of substances released by a facility in a given year.

It may be clear that it is a poor and crude proxy to indicate installations env’ performance as it depends on various factors as the chemical’s characteristics and the medium which is release (Toffel & Marshall, 2004)

As a consequence, some researchers (Karam, Craig and Currey, 1991; Toffel and Marshall, 2004) argue that in order to measure installations’ environmental data, it could be appropriate the use of the weighting emissions data using the each PRTRs standard limits or toxicity estimates so that TRI-based measures more accurately reflect real differences

Hyphoteses

Hypotheses 1: Toxicity-weighted environmental information classifies installations differently than in an absolute environmental pollution terms.

Further info: Operational dynamics

Importance of operational dynamics to measure installation’s env’ performance (Cairncross, 1992; and others)

To know how efficient firms Need to adjust data from PRTRs

(Karam et al.,1991)

Hyphoteses Hypotheses 2 a: Environmental information

expressed in terms that take into account number of employees and toxicity-weighted environmental information may send a more accurate signal to firm management, regulators or market regarding a firm’s environmental performance.

  Hypotheses 2 b: Environmental information

expressed in terms that take into account number of operating hours and toxicity-weighted environmental information may send a more accurate signal to firm management, regulators or market regarding a firm’s environmental performance.

Methodology

Sample European Pollutant Emission Register

(EPER) Year: 2004 Spain Chemical Industry (90 installations) Energy Industry (50 installations)

Methodology

Creamos tres rankings: Ranking A: Instalaciones clasificadas

por el pollution index Ranking B: Instalaciones ordenadas por

el ratio PI/número de horas de actividad productiva

Ranking C: Instalaciones clasificadas por el ratio PI/número de trabajadores

Comparamos en ambas industrias A vs B A vs C

Methodology

Pollution index (King and Lenox, 2004)PIi = ( ∑ weightc * waste generatedcij )

Reportable quantity

Weighting Examples of chemicals

1 1.0 Brominated diphenylether

10 0.1 Cadmium

100 0.01 Benzene

Methodology

Test no paramétrico Prueba de los rangos con signo de

Wilcoxon

Results

La clasificación de las instalaciones varía si incluimos la información sobre el número de hora operativas (0,1 y 0.05)

No existe diferencia en los rankings si se incluye la información relativa al número de trabajadores en la instalación.

Discussion 1/2

Puede que EPER envíe una información “distorsionada”

Una mayor complejidad en la información m.a. de las instalaciones puede implicar el envío de señales más adecuadas a la sociedad.

Discussion 2/2

Ciertas pequeñas empresas pueden escaparse de la presión por parte de los gobiernos.

Las empresas responsables m.a. pueden tener un incentivo para presentar la información recalculada ya que pueden enviar una señal mejor y, por tanto, mejorar su prestigio y/o imagen.

GRACIAS!!!