Interacción con otros medicamentos y otras formas de interacción Anticoagulantes orales

Grossman and Krueger (1991) were the first to model the relationship between environmental quality and economic growth, and their methodology is worth further description. Grossman and Krueger (1991) which concern urban air quality found that “Economic growth tends to alleviate pollution problems. Meanwhile, it was argued that economic growth and the environment are not necessarily in conflict and revealed that there is controversy even from this early stage of empirical investigation. For instance, Hettegi, et al. (1992) indicated that no evidence to suggest the inverted U-shape relationship exists for toxic intensity from manufacturing industries (Webber and Allenα, 2004). Nonetheless, globally, there are major inequalities in terms of access to basic resources (McKinsey Global Institute, 2011; Sutton et al., 2013). There is a wealth of evidence to suggest that increasing income will not be beneficial to water quality. As the relationship for water quality is not usually found to be either negatively sloped or Inverted-U shaped, most empirical studies identify that the quality of water supplies and income are positively related (Shafik and Bandyopadhyay, 1992; Vincent, 1997; Hettige et al., 2000).

Critics against EKC are profound in both econometric method and conceptual formulation. For instance, Barbier (1997) disparaged the threshold income level which appeared to be unstable, suggesting that EKC may not be accurate representations of environment–income relationships. However, semi-parametric and non-parametric methods have been introduced for detecting the systematic relationship between environment and economic development (Taskin and Zaim, 2000; Millimet et al., 2003; Bertinelli and Strobl, 2005; Azomahou et al., 2006; Zapata et al., 2008). Advantage of these methods is that interaction can be found at local level, with minimal assumptions and no advance specified functional forms. In a semi-

parametric setting and using a panel data, Nguyen (2009) investigates the relationship between energy consumption and economic development. A brief survey on non-parametric EKC can be found at Azomahou et al. (2006). In addition, eight functional form analysis and specification test using semi- parametric and nonparametric models found at Zapata et al. (2008).

According to Stern (2004), the EKC hypothesis is an intrinsically empirical phenomenon, but most studies in the literature are weak in econometrically terms. Generally, little attention has been dedicated to statistical proprieties of data used, such as spatial dependence or stochastic trends in time series. Besides, little consideration has been dedicated to model appropriateness issues, such as the possibility of omitted variable bias. The majority of studies assumes that, if the regression coefficients are individually or jointly significant and their expected signs are obtained, hence the EKC hypothesis exists (Maddison, 2006; Ruphasinga et al., 2004). In this context, Ruphasingha et al. (2004) remember that almost all studies in the literature, which have ignored spatial effects when analyzing this environmental phenomenon. This study has contributed to the EKC literature by providing a more sophisticated econometric model, taking into account statistical proprieties and several controls both for household effects and other pollution determinants in order to improve the model fitness. The spatial relationships and household are very important in EKCs. This due to household’s emissions per capita or income are affected by events occurred in neighboring households (Maddison, 2006).

As the reduced form environmental Kuznets curve is not driven by any particular economic model, there is little theoretical guidance for the correct specification. According to Webber and Allen (2004), there is an aggregate relationship between specific environmental pollutants and income per capita. However, the shape of the relationship is not uniform across pollutants and turning points, when they exist, differ across pollutants. This leads to the conclusion that there is no single relationship between income and environmental quality and the rate of environmental degradation. It is possible to grow out of some types of environmental degradations, but whether this is the case would depend on the type of pollution that is under examination. This study used the binary logistic regression to compute the inequality between household’s green awareness, perception, consumption behaviours along consistent to the household’s monthly income.

2.14 Chapter Summary

This chapter reviewed some basic theoretical literature pertinent to the green environment issues; industry consumption growth and eco efficiency indicator on the company’s production and consumption process. It began from the notion that the world’s growth path is expensive, especially for developing countries, which can ill-afford it (World Bank, 2009). In the study context, greening growth is aimed at creating a safe living and working environment. In principle, competitive markets can contribute to human well-being by matching economic output to human demand, allocating resources to the uses that generate the highest returns (EEA, 2013). This revealed that the task of analysing the well-being implications of resource use is rendered more complex by unequal distribution of environment related costs and benefits across society (WHO, 2012b &2013a).

Ethiopia is a highly rainfall dependent country and the economy relies on the agriculture sector. Exploitation of water resources might be generated a large economic benefit in the short term. However, in the long run, over-use of the groundwater is not only increased environmental degradation but also make economic growth and livelihood opportunities questionable. Ethiopia’s flourishing economy is both a key driver to environmental degradation and at the same time, the economy is negatively affected by environmental problems that the country is phasing (Emelie and Anders, 2013). Particularly, water consumption put an immense pressure on resource degradation and environmental depletion. Consumers such as households and factories were key participants to erode the green environment in the growing industrial cities like Kombolecha.

The water resource is, however, unevenly distributed amongst urban people and factories, and consumed at an accelerating pace. Studies, for instance, WBCSD (2009), ESCAP (2011), and BASF SEE balance by Sailing et al., (2013) used eco efficiency concepts in order to improve the company’s product quality and environment problems. The household’s consumption was not, yet, integrated into the living and working environment in Kombolecha. The “triple bottom” is notably used to capture the whole set of values, issues and processes that companies must address in order to minimize any harm resulting from their activities (Sustainability, 2005; BASF, 2004 & 2009 and Sailing et al.,2013). This study, nevertheless, considered the social, economic and environmental indicators and built the socio- eco efficiency in the water consumption and recycling processes. Meanwhile, this study designed methodologies and derived different econometric models in chapter three

CHAPTER THREE