Alternatives from policies of disclosure of companies’ environmental performance & connections with the reduction of

1. 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)

2. 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

3. 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?

4. 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).

5. 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!!

6. 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

7. 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). • Financialperformance (Klassen & Whybark, 1999) • Thecompetitiveness and innovationbenefits(King & Lenox, 2002)

8. 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

9. 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

10. PRTRs background • Willingness to know what was happening within industrial plants • Public Right-to-know – Bhopal (India) • Existence of environmental information asymmetrybetween firms and communities • Consumers and community are only partially aware of installations’ env’ behaviour

11. 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

12. 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.

13. 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

14. 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

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

16. Further info: Operational dynamics • Importanceof 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)

17. 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.

18. Methodology • Sample • European Pollutant Emission Register (EPER) • Year: 2004 • Spain • Chemical Industry (90 installations) • Energy Industry (50 installations)

19. 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

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

21. Methodology • Test no paramétrico • Prueba de los rangos con signo de Wilcoxon

22. 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.

23. 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.

24. 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.

25. GRACIAS!!!