Migrant remittances, international capital flows, and economic growth: a short-run Keynesian model applied to the emerging economies
Bibliographic record
Abstract
Purpose Economic models highlight that migrant remittances contribute to the “Dutch disease” by appreciating the real exchange rate and reducing export competitiveness. However, empirical evidence demonstrates cases where remittance inflows are associated with exchange rate depreciation. In this study, we develop an economic model showing how remittances can lead to real exchange rate depreciation and promote economic growth when managed through monetary and fiscal policy. Design/methodology/approach We design a short-term Keynesian macroeconomic model incorporating the international bond market and remittances. We demonstrate that remittances may generate real exchange rate depreciation and boost exports through an enhanced international credit flow channel. We also examine the implications of government borrowing, monetary sterilization, and foreign direct investment (FDI) within this framework to understand their influence on remittance flow macroeconomic dynamics. Findings Our model presents four cases that shed light on how our hypothesized remittance-induced credit channel can impact economic growth in an emerging economy under a large value of (a) the international portfolio investment coefficient, f, (b) a small value of f, (c) a complete sterilization in the monetary sector, and (d) a partial sterilization in the monetary sector. We show that government borrowing and FDI are critical in moderating remittance effects on domestic interest and exchange rates. The findings highlight how central bank and government policy responses influence the extent to which remittances impact economic growth. Originality/value We present a new theoretical explanation for how remittances can lead to real exchange rate depreciation through the monetary and financial sectors. By incorporating government financing decisions and FDI, we clarify the macroeconomic effects of remittances for theory. The findings from the four cases have important policy implications, especially for open emerging economies that rely on remittances and seek to mitigate the risks of the Dutch disease while using remittances to promote economic growth.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".