Macroeconomic Policy Effectiveness and the Informal Economy in Nigeria: A DSGE Approach
Bibliographic record
Abstract
Evaluating the approach and conduct of macroeconomic policy is crucial towards the provision of effective economic policies that addresses business cycles. However, to properly evaluate the effectiveness of macroeconomic policies, there is the need to pay attention to the structure of the economy. In Nigeria, there is a particular case for the introduction of informality in macroeconomic models. Hence, this study presents a New Keynesian Dynamic Stochastic General Equilibrium (DSGE) Model featuring an informal sector in order to understand how the presence of informality affects the effectiveness of macroeconomic policies in Nigeria. The Bayesian estimation of the DSGE model provides evidence that the informal economy tends to play a buffer role or an absorbing role in reducing the effectiveness of a monetary policy shock in contracting output in comparison to an economy without informality. Therefore, this study recommends that with the aim of limiting the role of the informal economy towards absorbing some of the effects of shocks to the domestic economy, the government needs to implement market-friendly policies that would help merge the informal economy with the formal economy.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".