Abstract
The purpose of this chapter is to advance theory and empirics of the links that connect the environment with trajectories of economic development within the broader framework of ecologically unequal exchange. The chapter draws on physical science and thermodynamic principles to substantiate the central claim that it is the liquidation of resources—not resource abundance per se—that stunts economic growth in the periphery. Moreover, the structure of the world-system and ecologically unequal exchanges therein fuel the appropriation of resources that stymies development in less-developed nations. The theory and cross-national empirics presented indicate clearly that ecologically unequal exchanges and associated environmental losses in poor nations are driving unequal development. Thus, ecologically unequal exchange is a root cause of global inequality, including cross-national differences in economic development. The chapter concludes that perspectives seeking to explain patterns of underdevelopment in peripheral areas would benefit from the incorporation of an interdisciplinary perspective that includes physical (thermodynamic) principles and pays explicit attention to the unequal nature of ecological exchanges the world over. Various implications as well as directions for future research are discussed.
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Regression models implicitly assume zero measurement error, resulting in attenuated coefficients to the degree that error exists. SEM overcomes this limitation by associating an error term that represents random and non-random measurement error with each observed variable and assigning to endogenous latent variables a residual error term that reflects the effects of unmeasured variables in the model. As a result, path coefficients modeled in SEM are unbiased by error terms.
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This time period is chosen based on the generally accepted view that “time lags of several decades” (Wackernagel et al. 2004:271) exist between the ecological changes and subsequent socioeconomic impacts. This value is derived by calculating a change score from 1971 to 2001 using the typical formula: (T2 − T1)/T1. The data are then multiplied by negative one (*−1) to ease interpretation of results such that larger values indicate greater losses.
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See Jorgenson and Clark (2012) for an exemplary illustration.
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Though not presented, results available upon request.
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McKinney, L. (2019). The Entropy Curse. In: Frey, R.S., Gellert, P.K., Dahms, H.F. (eds) Ecologically Unequal Exchange. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-89740-0_6
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