Testing cointegration between workers' remittances and human capital formation in Sri Lanka
Purpose: This study investigates the long-run relationship between workers' remittances and human capital formation in Sri Lanka by using the macro-level time series data during the period of 1975–2020. Design/methodology/approach: In this study, the augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test, the forecast error variance decomposition technique and impulse response function analysis were employed as the analytical techniques. Findings: In accordance with the results of unit root tests, the variables used in this study are mixed order. Results of cointegration confirm that workers' remittances in Sri Lanka have both long-run and short-run beneficial relationship with human capital formation. The Granger causality test results indicate that there is a two-way causal relationship between workers' remittances and human capital formation. The results of forecast error variance decomposition expose that innovation of workers' remittances contributes to the forecast error variance in human capital in bell shape. Further, the empirical evidence of impulse response function analysis reveals that a positive standard deviation shock to workers' remittances has an immediate significant positive impact on human capital formation in Sri Lanka for a period of up to ten years. Practical implications: This research provides insights into the workers' remittances in human capital formation in Sri Lanka. The findings of this study provides evidence that workers' remittances help to produce human capital formation. Originality/value: By using the ARDL Bounds cointegration and other techniques in Sri Lanka, this study fills an important gap in academic literature.
Year of publication: |
2021
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Authors: | Aslam, Ahamed Lebbe Mohamed ; Sivarajasingham, Selliah |
Published in: |
Journal of Economic and Administrative Sciences. - Emerald, ISSN 1026-4116, ZDB-ID 2664448-4. - 2021 (21.09.)
|
Publisher: |
Emerald |
Saved in:
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