Assessing welfare in developing countries before, during, and after Covid-19 using actual household data:he case of Mozambique
Bibliographic record
Abstract
In this study we utilise data from two household budget surveys conducted in Mozambique in 2019/20 and in 2022. Our aim is to assess the differentiated impact of Covid-19 on household welfare in this period. To establish a baseline, we use data from the first quarter of the 2019/20 survey, which was unaffected by the pandemic. Considering the varying exposure to Covid-19, we also investigate the distinct dynamics that unfolded across different regions and areas within the country. Employing an inverse probability weighted regression adjustment approach, we compare welfare metrics during different pandemic phases. Our findings reveal that, at national level, consumption levels and poverty rates worsened during the Covid-19 pandemic compared to the pre-Covid-19 period, partially recovering at the end of the pandemic. However, the national dynamics hide strongly diverging trends between, on the one hand, rural areas and the northern region, where consumption and poverty improved in 2022, even with respect to pre-Covid-19, and, on the other hand, urban areas and the southern region, where consumption and poverty were strongly affected during the initial phases of the pandemic but did not recover by 2022, instead worsening after the final and most challenging stages of Covid-19. Remarkably, Mozambique stands out as possibly the only developing country in sub-Saharan Africa with genuine, in-person survey data spanning the entire duration of the pandemic, including the pre- and post-pandemic phases. Our analysis contributes valuable insights into the short- and medium-term welfare implications of Covid-19 in a low-income context. Given the government’s limited fiscal capacity to mitigate pandemic-related negative effects and the country’s underdeveloped social protection policies, we emphasise the critical need for Mozambique to create stronger response mechanisms to temporary and geographically diversified shocks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".