This chapter presents the empirical strategy and the main variables involved in the analysis of stochastic and deterministic convergence. It then describes the data source used and the exact data series employed to measure per capita emissions for ten series of annual estimates of anthropogenic emissions that include: aerosol compounds (black carbon, organic carbon), aerosol precursor and reactive compounds (carbon monoxide, nitrogen oxides, ammonia, non-methane volatile organic compounds, and sulfur dioxide), and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The data span over the period 1820–2018 for seven of the pollutants, with the exception of carbon dioxide emissions that span over the period 1851–2018 and methane and nitrous oxide that span between 1970 and 2018. We also describe the different notions of time-series convergence, thereby highlighting some caveats associated with cross-sectional tests of convergence.

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Data and Empirical Strategy

  • Diego Romero-Ávila

摘要

This chapter presents the empirical strategy and the main variables involved in the analysis of stochastic and deterministic convergence. It then describes the data source used and the exact data series employed to measure per capita emissions for ten series of annual estimates of anthropogenic emissions that include: aerosol compounds (black carbon, organic carbon), aerosol precursor and reactive compounds (carbon monoxide, nitrogen oxides, ammonia, non-methane volatile organic compounds, and sulfur dioxide), and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The data span over the period 1820–2018 for seven of the pollutants, with the exception of carbon dioxide emissions that span over the period 1851–2018 and methane and nitrous oxide that span between 1970 and 2018. We also describe the different notions of time-series convergence, thereby highlighting some caveats associated with cross-sectional tests of convergence.