Monetary policy in developing countries: lessons from Kenya
Bibliographic record
Abstract
We estimate and then simulate a model of Kenyan economic development from 1965 to 1997 with two objectives in mind. The first is to demonstrate the degree of volatility of cyclical shocks that developing countries experience and to calculate the domestic nominal adjustments required by these shocks under both irrevocably fixed and free exchange rates.A comparison of these counterfactual nominal adjustments identifies the short-run implications for an economy of the choice of exchange rate regime. The second objective is to provide an estimate of the consequences for the economic development of Kenya of the lack of a coherent monetary order (excessive domestic credit expansion and overvalued exchange rate) throughout most of the period since 1965.A neoclassical convergence growth model based on Barro and Sala-i-Martin (1992) is employed and calibrated to represent the long-run growth path of real GDP in Kenya. A short-run four-sector CGE model is constructed that allows for cyclical movements of real GDP about the convergence growth path. The cyclical model focuses on the adjustment of the relative price of non-traded goods that is required to ensure short-run equilibrium in the non-traded goods sector. Given that terms of trade shocks dominated the macro environment of Kenya over the sample period, we find that a free exchange rate regime would have insulated the economy to a greater degree than an irrevocably fixed regime. In the growth decomposition exercise, we estimate that the two largest (and negative) influences on Kenyan economic growth were the decline in the external terms of trade from 100 in 1965 to an average of 79.5 over the 32-year time period, and the overvalued Kenyan shilling represented by a premium on the parallel market for foreign exchange. Overall, we estimate that the overvalued exchange rate reduced economic growth by an average of 0.47 per cent per annum over the 32 years.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".