An investigation of factors associated with the ecological footprint in Nepal through statistical modeling

Modeling the Ecological Footprint (EF) has been instrumental in undertaking remedial actions against environmental degradation and identifying factors affecting it. The main aim of this study was to examine the effect of environmental and socio-economic factors on the Ecological Footprint. Annual time series data of Nepal for 33 years (1989 to 2021) were obtained from several reliable sources, including the Global Footprint Network, World Development Indicators, Nepal Rastra Bank, and ministries and departments of the Government of Nepal. A series of sequential methodologies was adopted for statistical modeling. Firstly, the presence of autocorrelation in the annual data was eliminated by taking the first difference. Secondly, the subset regression method was employed to choose the predictor variables in the model. Thirdly, a lack-of-fit test was applied to choose between linear and nonlinear models. Finally, the linear regression model was compared with the gamma generalized linear model and the Autoregressive Integrated Moving Average (ARIMA). Eventually, all the criteria and tests supported the autocorrelation-adjusted linear model. The final selected model was subjected to model adequacy tests, including diagnostic tests. Total Natural Resources Rent (NR) and Energy Use (EU) showed significant positive relationships with the first difference of EF, with a one standard deviation (SD) increase in NR and EU associated with 0.722 SD and 1.269 SD increase in the first difference of EF, respectively. On the contrary, the approved Foreign Direct Investment (FDI) showed a significant negative relationship; with a one SD increase in FDI was associated with a 0.509 SD decrease in the first difference of EF. Approval of FDI not only boosts the economic status of a least developed country but also helps make it more environmentally sustainable.