The ecological transition, aimed at curbing the environmental degradation process, has been requiring a structural change in the consumption behavior and production methodologies, with inevitable implications for employment and the emissions of carbon dioxide (CO2).The evaluation of the tradeoff between the CO2 emissions and the unemployment rate is of particular interest for the environmental economists.The relationship between these two variables, which is commonly referred to as the "Environmental Phillips curve" (Kashem and Rahman, 2020), foresees that society needs to pay a certain cost in terms of job loss to obtain a decrease in air pollution. In other words, the emissions of CO2 shrink only in the face of an increase in the unemployment rate (and vice versa).Given the urgent and compelling necessity of providing policymakers with fresh and immediate insights on how to proficiently combat the Global Warming phenomenon, the literature offers several contributions of a purely empirical nature that identify the key variables affecting the relationship between the CO2 emissions and the unemployment rate.Although legitimate, the empirical approach involves some significant criticalities, such as the failure to establish a univocal causal nexus between CO2 emissions and the unemployment rate, the exclusion of potentially relevant factors for the analysis between these two variables, and the specification of an empirical model that is not supported by adequate theoretical foundations.In this paper, the authors struggle to fill this gap by analysing the relationship between the emissions of CO2 and the unemployment rate, taking into account the role of the green investments. More precisely, the objective of their study consists of understanding whether this variable (green investments) has a moderation or amplification effect on the relationship between the emissions of CO2 and the unemployment rate. In particular, the authors evaluate two alternative research hypotheses: the first (H0) is that green investments lower the emissions of CO2, but, at the same time, they imply negative consequences for employment, while the second (H1) is that green investments decrease the emissions of CO2 without entailing job disruption or even leaving room for new employment opportunities.The originality of the authors' study is that they do not rely on a merely empirical approach, but instead they propose a precise identification strategy of the relationship between the emissions of CO2 and the unemployment rate that relies on a version of the new model of imperfect competition of Ferrentino and Vota (2025) augmented with green investments. Such a model represents the first attempt to discover the theoretical foundations of the Environmental Phillips curve.The predictions of this innovative theoretical model are assessed by using time-series data from the USA, the European Union, and China, three large economies with high levels of air pollution (OECD, 2025).The estimators adopted by the authors in the empirical part of their study are the Ordinary Least Squares model (OLS), the Autoregressive Distributed Lag model (ARDL) and the Error Correction model (ECM), which are able to estimate the coefficients of the regression equation involving the emissions of CO2 and the unemployment rate by distinguishing the short-run fluctuations from the long-run deviations of the same two variables from their respective equilibrium values. 2The authors' results indicate that green investments significantly affect the relationship between the emissions of CO2 and the unemployment rate, even if there are important differences between the three countries of interest.Finally, the authors discuss some policy recommendations that can be drawn from their findings on how to balance the fight against the environmental degradation problem with job protection.

The occupational criticalities of the ecological transition: the impact of the green investments on the relationship between the CO2 emissions and the unemployment rate

Luca Vota
Secondo
2025

Abstract

The ecological transition, aimed at curbing the environmental degradation process, has been requiring a structural change in the consumption behavior and production methodologies, with inevitable implications for employment and the emissions of carbon dioxide (CO2).The evaluation of the tradeoff between the CO2 emissions and the unemployment rate is of particular interest for the environmental economists.The relationship between these two variables, which is commonly referred to as the "Environmental Phillips curve" (Kashem and Rahman, 2020), foresees that society needs to pay a certain cost in terms of job loss to obtain a decrease in air pollution. In other words, the emissions of CO2 shrink only in the face of an increase in the unemployment rate (and vice versa).Given the urgent and compelling necessity of providing policymakers with fresh and immediate insights on how to proficiently combat the Global Warming phenomenon, the literature offers several contributions of a purely empirical nature that identify the key variables affecting the relationship between the CO2 emissions and the unemployment rate.Although legitimate, the empirical approach involves some significant criticalities, such as the failure to establish a univocal causal nexus between CO2 emissions and the unemployment rate, the exclusion of potentially relevant factors for the analysis between these two variables, and the specification of an empirical model that is not supported by adequate theoretical foundations.In this paper, the authors struggle to fill this gap by analysing the relationship between the emissions of CO2 and the unemployment rate, taking into account the role of the green investments. More precisely, the objective of their study consists of understanding whether this variable (green investments) has a moderation or amplification effect on the relationship between the emissions of CO2 and the unemployment rate. In particular, the authors evaluate two alternative research hypotheses: the first (H0) is that green investments lower the emissions of CO2, but, at the same time, they imply negative consequences for employment, while the second (H1) is that green investments decrease the emissions of CO2 without entailing job disruption or even leaving room for new employment opportunities.The originality of the authors' study is that they do not rely on a merely empirical approach, but instead they propose a precise identification strategy of the relationship between the emissions of CO2 and the unemployment rate that relies on a version of the new model of imperfect competition of Ferrentino and Vota (2025) augmented with green investments. Such a model represents the first attempt to discover the theoretical foundations of the Environmental Phillips curve.The predictions of this innovative theoretical model are assessed by using time-series data from the USA, the European Union, and China, three large economies with high levels of air pollution (OECD, 2025).The estimators adopted by the authors in the empirical part of their study are the Ordinary Least Squares model (OLS), the Autoregressive Distributed Lag model (ARDL) and the Error Correction model (ECM), which are able to estimate the coefficients of the regression equation involving the emissions of CO2 and the unemployment rate by distinguishing the short-run fluctuations from the long-run deviations of the same two variables from their respective equilibrium values. 2The authors' results indicate that green investments significantly affect the relationship between the emissions of CO2 and the unemployment rate, even if there are important differences between the three countries of interest.Finally, the authors discuss some policy recommendations that can be drawn from their findings on how to balance the fight against the environmental degradation problem with job protection.
2025
Istituto di Studi sul Mediterraneo - ISMed
Environmental Phillips curve, Macroeconomic uncertainty, Mathematical methods in Economics, Pollution, Total factor productivity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/561128
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