Estimation with Cross-National Data: Robust and Nonparametric Methods

Dietz, Thomas; Frey, R. Scott; Kalof, Linda

doi:10.2307/2095357

Cited by 74 publications

(30 citation statements)

References 32 publications

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“…We also computed estimates of the log-polynomial model using least median of squares, least trimmed squares, and a robust regression that uses Huber estimates followed by biweighted least squares. These techniques are robust with regard to outliers in residuals and in carriers (37,38). The robust estimates yield substantively identical results to the more familiar, ordinary least squares reported here.…”

supporting

confidence: 65%

“…Deleting the USSR from the analysis did not significantly change the results. ‡ ‡ The results reported are for ordinary least squares, with SE based on 500 replications of case-based bootstrap resampling, which are preferable to normal theory SE in this context (37,38). To reduce colinearity among polynomial terms, we centered the population and gdp variables by using deviations from the mean of the logs instead of raw values for the linear in log terms and in generating the polynomial terms.…”

mentioning

confidence: 99%

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Effects of population and affluence on CO₂ emissions

Dietz

Rosa

1997

Proc. Natl. Acad. Sci. U.S.A.

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1,561

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We developed a stochastic version of the Impact ‫؍‬ Population⅐Affluence⅐Technology (IPAT) model to estimate the effects of population, affluence, and technology on national CO 2 emissions. Our results suggest that, for population, there are diseconomies of scale for the largest nations that are not consistent with the assumption of direct proportionality (loglinear effects) common to most previous research. In contrast, the effects of affluence on CO 2 emissions appear to reach a maximum at about $10,000 in per-capita gross domestic product and to decline at higher levels of affluence. These results confirm the general value of the IPAT model as a starting point for understanding the anthropogenic driving forces of global change and suggest that population and economic growth anticipated over the next decade will exacerbate greenhouse gas emissions.It is certain that the atmospheric concentrations of greenhouse gases (GHGs) are increasing (1, 2). These growing concentrations threaten to produce disruptive changes in global climate. There is widespread scientific agreement that the increased concentrations are the consequence of human activities around the globe. Among these anthropogenic factors, the principal ones (often called ''driving forces'') are (i) population, (ii) economic activity, (iii) technology, (iv) political and economic institutions, and (v) attitudes and beliefs (3). These forces usually are assumed to drive not just GHG emissions but all anthropogenic environmental change.Despite agreement about the list of forces that affect anthropogenic GHG emissions, we have little understanding of the relative importance of each driving force. Thus, our basic knowledge of the biosphere and our ability to choose appropriate policy responses will remain significantly incomplete until we better understand the human dimensions of the system (3-5). Our goals here are to suggest an approach for analyzing anthropogenic environmental changes and to apply that approach to anthropogenic emissions of the principal GHG: CO 2 .To organize our analysis, we adopted the Impact ϭ Population⅐Aff luence⅐Technology (IPAT) framework first proposed in the early 1970s (6) as part of an ongoing debate on the driving forces of environmental change (7-11). It still finds wide use as an orienting perspective (12-20). The framework incorporates key features of human dimensions of environmental change into a model as follows:where I is environmental impact, P is population, and A is affluence or economic activity per person. T is the environmental impact per unit of economic activity, which is determined by the technology used for the production of goods and services and by the social organization and culture that determine how the technology is mobilized. The model is simple, systematic, and robust: simple because it incorporates key anthropogenic driving forces with parsimony; systematic because it specifies the mathematical relationship between the driving forces and their impacts; and robust because it is applicable to a...

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supporting

confidence: 65%

mentioning

confidence: 99%

Effects of population and affluence on CO₂ emissions

Dietz

Rosa

1997

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

1,561

653

View full text Add to dashboard Cite

show abstract

“…Table I presents the means, standard deviations, and zero-order correlations of study variables, while Table II provides the regression results. We used robust regression to test our hypotheses because OLS regression has been shown to perform poorly when used with cross-national data (Dietz, Frey, & Kalof, 1987). A number of the variables in our model suffer from skewness, which persisted after log transformations.…”

Section: Control Variablesmentioning

confidence: 99%

Is internationalization associated with investments in HRM? A study of entrepreneurial firms in emerging markets

Khavul

Benson

Datta

2010

Human Resource Management

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“…Another measure that has been shown to be associated with increased environmental pressure or degradation is urbanization, which is measured as a percentage of total population living in urban areas. While urbanization is important for understanding consumption demands [68] it is particularly important for understanding water usage. As Longo and York [12] (p. 76) explain, "Demographic changes, particularly population shifts to urban areas, are often associated with shifts in water use patterns.…”

Section: Independent Variablesmentioning

confidence: 99%

The Political Economy of the Water Footprint: A Cross-National Analysis of Ecologically Unequal Exchange

Fitzgerald

Auerbach

2016

Sustainability

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Abstract:Water scarcity is an important social and ecological issue that is becoming increasingly problematic with the onset of climate change. This study explores the extent to which water resources in developing countries are affected by the vertical flow of exports to high-income countries. In examining this question, the authors engage the sociological theory of ecologically unequal exchange, which argues that high-income countries are able to partially externalize the environmental costs of their consumption to lower-income countries. The authors use a relatively new and underutilized measure of water usage, the water footprint, which quantifies the amount of water used in the entire production process. Ordinary least squares (OLS) and robust regression techniques are employed in the cross-national analysis of 138 countries. The results provide partial support of the propositions of ecologically unequal exchange theory. In particular, the results highlight the importance of structural position in the global economy for understanding the effects of trade on water resources.

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Estimation with Cross-National Data: Robust and Nonparametric Methods

Cited by 74 publications

References 32 publications

Effects of population and affluence on CO₂ emissions

Effects of population and affluence on CO₂ emissions

Is internationalization associated with investments in HRM? A study of entrepreneurial firms in emerging markets

The Political Economy of the Water Footprint: A Cross-National Analysis of Ecologically Unequal Exchange

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Estimation with Cross-National Data: Robust and Nonparametric Methods

Cited by 74 publications

References 32 publications

Effects of population and affluence on CO2 emissions

Effects of population and affluence on CO2 emissions

Is internationalization associated with investments in HRM? A study of entrepreneurial firms in emerging markets

The Political Economy of the Water Footprint: A Cross-National Analysis of Ecologically Unequal Exchange

Contact Info

Product

Resources

About

Effects of population and affluence on CO₂ emissions

Effects of population and affluence on CO₂ emissions