Economics & Development

This report presents technical recommendations for the Lao People’s Democratic Republic’s Long-Term Low-Emission Development Strategy (LT-LEDS) and its implementation. An LT-LEDS is a strategic document that outlines a country’s plan under the Paris Agreement for low-emission development by mid-century. The recommendations were developed based on Lao PDR’s 2050 net-zero greenhouse gas (GHG) emissions target outlined in its revised nationally determined contributions (NDCs)1 and in close consultation with the Department of Climate Change of the Ministry of Natural Resources and Environment (DCC-MONRE) and the Department of Planning of the Ministry of Planning and Investment as the government’s designated leading agencies. The analysis takes the net-zero emissions target as a given parameter for modelling and recommendations but does not assess this target or its implications for Lao PDR’s development. Similarly, actions included in the NDC Implementation Plan issued by the government are automatically included in the BAU scenario.

The availability of weather data from remotely sensed Earth observation data has reduced the cost of including weather variables in econometric models. Weather variables are common instrumental variables used to predict economic outcomes and serve as an input in modeling crop yields for rainfed agriculture. The use of Earth observation data in econometric applications has only recently been met with critical assessment of the suitability and quality of these data in economics. This paper quantifies the significance and magnitude of the effect of measurement error in Earth observation data in the context of smallholder agricultural productivity. The paper shows that different Earth observation sources use different measurement methods. The findings are not robust to the choice of Earth observation dataset, and the outcomes are not simply affine transformations of one another. Thus, the paper suggests that researchers should exercise caution in using these data and include robustness checks that test alternative sources of Earth observation data.

This paper examines the impact of livelihood diversification on food insecurity amid the COVID-19 pandemic. The analysis uses household panel data from Ethiopia, Malawi, and Nigeria in which the first round was collected immediately prior to the pandemic and extends through multiple rounds of monthly data collection during the pandemic. Using this pre- and post-outbreak data, and guided by a pre-analysis plan, the paper estimates the causal effect of livelihood diversification on food insecurity. The results do not support the hypothesis that livelihood diversification boosts household resilience. Although income diversification may serve as an effective coping mechanism for small-scale shocks, the findings show that for a disaster on the scale of the pandemic, this strategy is not effective. Policy makers looking to prepare for the increased occurrence of large-scale disasters will need to grapple with the fact that coping strategies that gave people hope in the past may fail them as they try to cope with the future.