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arxiv: 2605.19401 · v1 · pith:VU23MNQEnew · submitted 2026-05-19 · 💰 econ.GN · q-fin.EC· q-fin.GN· stat.AP

External Demand, Domestic Monetary Conditions, and Remittance Dynamics in Nepal

Sahaj Raj Malla This is my paper

Pith reviewed 2026-05-20 02:22 UTC · model grok-4.3

classification 💰 econ.GN q-fin.ECq-fin.GNstat.AP
keywords remittancesNepalexternal demandmonetary conditionscointegrationARDLerror correctionforecasting
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The pith

External demand from migrant destinations raises Nepal's remittance share of GDP over the long run, while tighter domestic monetary conditions reduce it.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper investigates the drivers of personal remittances as a share of GDP in Nepal using annual data from 1993 to 2024. It identifies a strong positive long-run relationship between external demand in major destination countries and remittance inflows, alongside a negative effect from tighter domestic monetary policy. An ARDL bounds test combined with an error correction model establishes a stable cointegrating link that adjusts by roughly 26 percent each year. Medium-term forecasts under baseline conditions show remittances staying near 28 percent of GDP through 2030 while remaining sensitive to external shocks. These patterns matter for a country where remittances form a large part of the economy and influence policy choices on monetary settings and migration.

Core claim

The analysis reveals a strong positive long-run effect of external demand on remittances and a significant negative impact of tighter domestic monetary conditions. Composite indices constructed via principal component analysis for multi-country external demand and domestic monetary conditions are integrated into an ARDL bounds testing procedure, Engle-Granger cointegration, dynamic OLS, and a two-step error correction model that confirms a stable relationship correcting approximately 26 percent of disequilibria annually, with baseline projections indicating remittances near 28.3 percent of GDP by 2030.

What carries the argument

Principal component analysis to form composite indices for external demand and the monetary conditions index, embedded in an ARDL bounds testing and error correction model pipeline.

Load-bearing premise

The principal component analysis indices accurately represent external demand across countries and domestic monetary conditions without material loss of relevant information in the small annual sample.

What would settle it

Re-estimating the long-run coefficients and error correction speed using raw individual-country demand measures or alternative monetary variables instead of the PCA composites yields insignificant or unstable results.

Figures

Figures reproduced from arXiv: 2605.19401 by Sahaj Raj Malla.

Figure 1
Figure 1. Figure 1: Historical Remittances (% of GDP) and Multi-Model Forecasts to 2030 [PITH_FULL_IMAGE:figures/full_fig_p010_1.png] view at source ↗
read the original abstract

This study investigates the macroeconomic determinants and dynamic behaviour of personal remittances as a share of Gross Domestic Product (GDP) in Nepal, emphasizing external demand in major destination countries and domestic monetary policy. Using annual data (1993-2024), we construct composite indices via Principal Component Analysis (PCA) for multi-country external demand and a domestic Monetary Conditions Index (MCI). Our small-sample econometric pipeline includes Autoregressive Distributed Lag (ARDL) bounds testing, Engle-Granger cointegration, Dynamic OLS (DOLS), and a two-step Error Correction Model (ECM). We also employ Granger causality tests and multi-model forecasting using machine learning and ECM scenarios. The analysis reveals a strong positive long-run effect of external demand on remittances and a significant negative impact of tighter domestic monetary conditions. The ECM confirms a stable cointegrating relationship, correcting approximately 26% of disequilibria annually. Medium-term projections indicate remittances will remain structurally important, reaching around 28.3% of GDP by 2030 under baseline conditions, while exhibiting high sensitivity to external demand shocks. This study advances the literature by integrating PCA-derived external demand and monetary conditions indices within a unified ARDL-ECM framework for small samples. Focusing on one of the world's most remittance-dependent economies, it offers actionable insights for monetary policy calibration, migration diversification, and the productive utilization of remittance inflows.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 3 minor

Summary. The manuscript investigates the macroeconomic determinants of personal remittances as a share of GDP in Nepal, focusing on external demand in destination countries and domestic monetary policy. Using annual data from 1993-2024, it constructs PCA-based composite indices for multi-country external demand and a domestic Monetary Conditions Index (MCI). The analysis employs ARDL bounds testing, Engle-Granger cointegration, DOLS, a two-step ECM, Granger causality tests, and multi-model forecasting (including machine learning and ECM scenarios). Key results include a strong positive long-run effect of external demand on remittances, a significant negative impact from tighter domestic monetary conditions, a stable cointegrating relationship with an error-correction speed of approximately 26% per year, and medium-term projections reaching 28.3% of GDP by 2030 under baseline conditions.

Significance. If the central empirical findings hold after addressing small-sample concerns, the paper offers a useful integration of PCA-derived indices within an ARDL-ECM framework for analyzing remittance dynamics in a highly dependent small open economy. It supplies policy-relevant evidence on monetary conditions and external shocks for Nepal and similar contexts, while the forecasting component highlights sensitivity to external demand. The approach advances applied work on small annual samples by combining multiple cointegration methods, though generalizability remains constrained by data limitations.

major comments (3)
  1. [Data and Methodology] Data and Methodology section: With an annual sample of only T≈32 observations (1993-2024), the ARDL bounds testing, Engle-Granger procedure, and two-step ECM are applied to series that include PCA-constructed indices; these procedures are known to exhibit low power against stationary alternatives and size distortions in small samples, directly undermining the reliability of the reported long-run coefficients and the 26% annual error-correction speed.
  2. [Empirical Results] Empirical Results section, ECM specification: The error-correction term of approximately 26% is presented as evidence of a stable cointegrating relationship, yet no small-sample critical values for the bounds test, sensitivity checks to lag selection, or residual autocorrelation diagnostics are reported; this is load-bearing because the central claim of a 'strong positive long-run effect' and 'significant negative impact' of MCI rests on these estimates.
  3. [Results] Results section, PCA index construction: The composite external demand and MCI indices are derived via principal components in a short annual panel; the manuscript does not quantify the proportion of variance explained or test robustness to alternative weighting schemes, raising the risk that material information loss affects the estimated relationships.
minor comments (3)
  1. [Abstract and Forecasting] The abstract and forecasting subsection mention 'multi-model forecasting using machine learning and ECM scenarios' without specifying the exact ML algorithms, hyperparameters, or out-of-sample validation metrics employed.
  2. [Tables] Tables reporting long-run coefficients and ECM results should include standard errors, t-statistics, and explicit comparison to small-sample critical values for the bounds test.
  3. [Figures] The time-series plots of the constructed indices and remittances/GDP ratio would benefit from clearer axis labels, source notes, and indication of the 1993-2024 sample period.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed comments. We address each major comment below, indicating where revisions will be made to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Data and Methodology] Data and Methodology section: With an annual sample of only T≈32 observations (1993-2024), the ARDL bounds testing, Engle-Granger procedure, and two-step ECM are applied to series that include PCA-constructed indices; these procedures are known to exhibit low power against stationary alternatives and size distortions in small samples, directly undermining the reliability of the reported long-run coefficients and the 26% annual error-correction speed.

    Authors: We acknowledge that small annual samples can lead to size distortions and reduced power in cointegration tests. Our strategy of cross-validating results across ARDL bounds testing, Engle-Granger, and DOLS is intended to mitigate reliance on any single procedure. In the revised manuscript we will expand the discussion of small-sample limitations and qualify the strength of inference accordingly. revision: partial

  2. Referee: [Empirical Results] Empirical Results section, ECM specification: The error-correction term of approximately 26% is presented as evidence of a stable cointegrating relationship, yet no small-sample critical values for the bounds test, sensitivity checks to lag selection, or residual autocorrelation diagnostics are reported; this is load-bearing because the central claim of a 'strong positive long-run effect' and 'significant negative impact' of MCI rests on these estimates.

    Authors: The referee correctly identifies the missing elements. We will add small-sample critical values for the ARDL bounds test, present results for alternative lag specifications, and include residual diagnostics such as the Breusch-Godfrey test in the revised empirical results section. revision: yes

  3. Referee: [Results] Results section, PCA index construction: The composite external demand and MCI indices are derived via principal components in a short annual panel; the manuscript does not quantify the proportion of variance explained or test robustness to alternative weighting schemes, raising the risk that material information loss affects the estimated relationships.

    Authors: We agree that reporting the variance explained and robustness to alternative constructions would increase transparency. In the revision we will state the proportion of variance captured by the first principal component for each index and add checks using equal-weight and simple-sum alternatives. revision: yes

Circularity Check

0 steps flagged

No circularity: standard empirical estimation from observed data

full rationale

The paper's core results (long-run coefficients on external demand and MCI, plus 26% ECM adjustment speed) are obtained by applying PCA to construct indices followed by ARDL bounds testing, Engle-Granger, DOLS, and two-step ECM estimation on the 1993-2024 annual series. These steps fit parameters to the data rather than defining the target quantities into existence or renaming prior results. No self-citations, uniqueness theorems, or ansatzes are shown as load-bearing in the abstract or described pipeline. The 2030 projections are explicit extrapolations, not the central claim. The analysis is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 0 axioms · 0 invented entities

Based on the abstract alone, the central claims rest on standard time-series assumptions and two fitted indices whose construction details are not elaborated.

free parameters (1)
  • Error-correction speed
    The 26% annual adjustment rate is estimated from the ECM applied to the sample data.

pith-pipeline@v0.9.0 · 5781 in / 1233 out tokens · 43624 ms · 2026-05-20T02:22:52.893960+00:00 · methodology

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Reference graph

Works this paper leans on

15 extracted references · 15 canonical work pages

  1. [1]

    Do remittances promote financial development?Journal of development economics, 96(2):255–264, 2011

    Reena Aggarwal, Asli Demirgüç-Kunt, and Maria Soledad Martinez Peria. Do remittances promote financial development?Journal of development economics, 96(2):255–264, 2011

    work page 2011

  2. [2]

    Remittances as insurance: evidence from mexican immigrants.Journal of Population Economics, 19(2):227–254, 2006

    Catalina Amuedo-Dorantes and Susan Pozo. Remittances as insurance: evidence from mexican immigrants.Journal of Population Economics, 19(2):227–254, 2006

    work page 2006

  3. [3]

    Remit- tances and working poverty.The Journal of Development Studies, 50(10):1348–1361, 2014

    Jean-Louis Combes, Christian Hubert Ebeke, Mathilde Maurel, and Thierry Urbain Yogo. Remit- tances and working poverty.The Journal of Development Studies, 50(10):1348–1361, 2014

    work page 2014

  4. [4]

    Work-related migration and poverty reduction in nepal.Review of Development Economics, 14(2):323–332, 2010

    Michael Lokshin, Mikhail Bontch-Osmolovski, and Elena Glinskaya. Work-related migration and poverty reduction in nepal.Review of Development Economics, 14(2):323–332, 2010

    work page 2010

  5. [5]

    Motivations to remit: Evidence from botswana.Journal of political Economy, 93(5):901–918, 1985

    Robert EB Lucas and Oded Stark. Motivations to remit: Evidence from botswana.Journal of political Economy, 93(5):901–918, 1985

    work page 1985

  6. [6]

    The determinants of remittances in latin america and the caribbean.Academy of Business Disciplines Journal, 2(1):86–101, 2010

    Richard A McGowan and JF Mahon. The determinants of remittances in latin america and the caribbean.Academy of Business Disciplines Journal, 2(1):86–101, 2010

    work page 2010

  7. [7]

    Theimpactofremittancesoneconomicgrowth: empirical evidence from south africa.International Journal of Trade and Global Markets, 15(2):254–272, 2022

    SheillaNyashaandNicholasMOdhiambo. Theimpactofremittancesoneconomicgrowth: empirical evidence from south africa.International Journal of Trade and Global Markets, 15(2):254–272, 2022

    work page 2022

  8. [8]

    Bounds testing approaches to the analysis of level relationships.Journal of applied econometrics, 16(3):289–326, 2001

    M Hashem Pesaran, Yongcheol Shin, and Richard J Smith. Bounds testing approaches to the analysis of level relationships.Journal of applied econometrics, 16(3):289–326, 2001

    work page 2001

  9. [9]

    The economics of migrants’ remittances.Handbook of the economics of giving, altruism and reciprocity, 2:1135–1198, 2006

    Hillel Rapoport and Frédéric Docquier. The economics of migrants’ remittances.Handbook of the economics of giving, altruism and reciprocity, 2:1135–1198, 2006

    work page 2006

  10. [10]

    Migration and development brief.World Bank, 24, 2009

    Dilip Ratha, Sanket Mohapatra, and Ani Silwal. Migration and development brief.World Bank, 24, 2009

    work page 2009

  11. [11]

    Workers’ remittances: an important and stable source of external development finance.Remittances: development impact and future prospects, 9:19–51, 2005

    Dilip Ratha et al. Workers’ remittances: an important and stable source of external development finance.Remittances: development impact and future prospects, 9:19–51, 2005

    work page 2005

  12. [12]

    Remittances in nepal: boon or bane?The Journal of Development Studies, 49 (10):1316–1331, 2013

    Chandan Sapkota. Remittances in nepal: boon or bane?The Journal of Development Studies, 49 (10):1316–1331, 2013

    work page 2013

  13. [13]

    Determinants and macroe- conomic impact of remittances in sub-saharan africa.Journal of African economies, 20(2):312–340, 2011

    Raju Jan Singh, Markus Haacker, Kyung-woo Lee, and Maëlan Le Goff. Determinants and macroe- conomic impact of remittances in sub-saharan africa.Journal of African economies, 20(2):312–340, 2011

    work page 2011

  14. [14]

    The new economics of labor migration.The american Economic review, 75(2):173–178, 1985

    Oded Stark and David E Bloom. The new economics of labor migration.The american Economic review, 75(2):173–178, 1985

    work page 1985

  15. [15]

    A simple estimator of cointegrating vectors in higher order integrated systems.Econometrica: journal of the Econometric Society, pages 783–820, 1993

    James H Stock and Mark W Watson. A simple estimator of cointegrating vectors in higher order integrated systems.Econometrica: journal of the Econometric Society, pages 783–820, 1993. 14 A Additional Tables and Figures This appendix presents supplementary materials supporting the empirical analysis in the main text. A.1 Unit Root Test Results Detailed unit...

    work page 1993