The Lagged Environmental Consequences of Demographic and Economic Change

Quantitative sociologists conducting environmental research often use temporally lagged variables to estimate the social drivers of ecological change. To highlight the relevance of temporal lags for this scholarship, we specifically look at the longitudinal relationship between demographic and economic change and two different environmental outcomes: land development and carbon emissions. For land development, we run longitudinal spatial regression models to assess whether increasing the lag time changes the slope estimates for in-migration and out-migration at the county level across the contiguous United States (n = 3,026). For carbon emissions, we use cross-national data in Prais–Winsten models to assess changes in the lagged estimates for GDP, urbanization, and age structure (n = 146). Results from these analyses indicate that the slope estimates continue to be statistically significant, but the magnitudes of these coefficients change with increased lag time. We propose that scholars use a more systematic approach when assessing the temporal duration of socio-ecological change.