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Enregistrement W4387695060 · doi:10.20473/vol10iss20235pp443-454

The Impact of MSMEs Financing in Islamic Bank on Unemployment in Indonesia

2023· article· en· W4387695060 sur OpenAlex

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Notice bibliographique

RevueJurnal Ekonomi Syariah Teori dan Terapan · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueIslamic Finance and Communication
Établissements canadiensnon disponible
Organismes subventionnairesGovernment of Jiangsu ProvinceDoğu Akdeniz ÜniversitesiTenaga Nasional Berhad
Mots-clésIslamBusinessUnemploymentFinancial systemFinanceEconomicsEconomic growthGeography

Résumé

récupéré en direct d'OpenAlex

ABSTRACT One of the contributions of the Islamic banking sector to Indonesia’s economy is channeling funds to MSMEs in the form of financing since a number of them could not access financial services. Interestingly, the MSMEs grew as the Islamic Banking sector rose. However, no single study analyzes such an impact on unemployment in both rural and urban areas. This paper aimed to reveal the effect of MSMEs financing in Islamic banks on unemployment in Indonesia. It further aimed to discover such an effect on unemployment in Indonesia's urban and rural areas separately. Dynamic panel GMM two-step analysis is used in this research to estimate cross-province data in Indonesia between 2010 and 2019. The results of the study reveal that MSMEs financing in Islamic Banks contributed significantly to the reduction of unemployment in Indonesia as a whole. It is also found that the unemployment in urban areas is reduced by MSMEs financing in Islamic Banks. On the other hand, there is no significant relationship between MSMEs financing in Islamic Banks and unemployment in rural areas. These findings can be the basis for Islamic banks to increase MSMEs financing and for the government to expand Islamic banks' role in every part of Indonesia to reduce unemployment, especially in rural areas. Keywords: MSMEs Financing, Islamic Bank, Unemployment, Urban, Rural. ABSTRAK Salah satu kontribusi sektor perbankan syariah dalam perekonomian Indonesia adalah penyaluran dana kepada UMKM dalam bentuk pembiayaan, karena beberapa dari mereka tidak dapat mengakses layanan keuangan. Menariknya, UMKM tumbuh seiring dengan bangkitnya sektor Perbankan Syariah. Namun, tidak ada satu studi pun yang menganalisis dampak tersebut terhadap pengangguran di pedesaan dan perkotaan. Penelitian ini bertujuan untuk mengungkap pengaruh pembiayaan UMKM di bank syariah terhadap pengangguran di Indonesia. Hal ini bertujuan untuk mengetahui lebih jauh pengaruh tersebut terhadap pengangguran di daerah perkotaan dan pedesaan secara terpisah di Indonesia. Analisis dua langkah GMM panel dinamis digunakan untuk mengestimasi data lintas provinsi di Indonesia antara tahun 2010 dan 2019. Hasilnya mengungkapkan bahwa pembiayaan UMKM di Bank Syariah berkontribusi signifikan terhadap pengurangan pengangguran di Indonesia secara keseluruhan. Ditemukan juga bahwa pengangguran di perkotaan berkurang dengan pembiayaan UMKM di Bank Syariah. Di sisi lain, tidak ada hubungan yang signifikan antara pembiayaan UMKM di bank syariah dengan pengangguran di pedesaan. Hasil penelitian ini dapat menjadi dasar bagi bank-bank syariah dalam meningkatkan porsi pembiayaan UMKM dan dasar bagi pemerintah untuk memperluas peran perbankan syariah di seluruh bagian Indonesia untuk mengurangi pengangguran, khususnya di area pedesaan. Kata Kunci: Pembiayaan UMKM, Bank Syariah, Pengangguran, Perkotaan, Pedesaan. 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The determinants of youth unemployment: A panel data analysis of OECD countries. The European Journal of Comparative Economics, 15(2), 231–248. doi:10.25428/1824-2979/201802-231-248 Benbekhti, S. E., Boulila, H., & Bouteldja, A. (2021). Islamic finance, small and medium enterprises and job creation in Turkey: An empirical evidence (2009-2017). International Journal of Islamic Economics and Finance (IJIEF), 4, 41-62. doi:10.18196/ijief.v4i0.10490 Blanchflower, D. G., & Meyer, B. D. (1994). A longitudinal analysis of the young self-employed in Australia and the United States. Small Business Economics, 6(1), 1–19. doi:10.1007/BF01066108 Badan Pusat Statistik/BPS. (2021). Keadaan angkatan kerja di Indonesia. Retrieved from https://www.bps.go.id/publication/2021/12/07/ee355feea591c3b6841d361b/keadaan-angkatan-kerja-di-indonesia-agustus-2021.html Chapra, M. U. (2011). The global financial crisis: Can Islamic finance help? In: Langton, J., Trullols, C., Turkistani, A.Q. (eds) Islamic Economics and Finance (pp. 135-132). London: IE Business Publishing. doi:10.1057/9780230361133_5 Dusuki, A. W. (2008). Banking for the poor: The role of Islamic banking in microfinance initiatives. Humanomics, 24(1), 49–66. doi:10.1108/08288660810851469 Edmiston, K. D. (2007). The role of small and large businesses in economic development. SSRN Electronic Journal, 73-97. doi:10.2139/ssrn.993821 Elasrag, H. (2016). Islamic Finance for SMES. SSRN Electronic Journal. doi:10.2139/ssrn.2842160 Faggio, G., & Silva, O. (2014). Self-employment and entrepreneurship in urban and rural labour markets. Journal of Urban Economics, 84, 67–85. doi:10.1016/j.jue.2014.09.001 Fajri, M. Z. N., Muhammad, A. A., Umam, K., Putri, L. P., & Ramadhan, M. A. (2022). The effect covid-19 and sectoral financing on Islamic bank profitability in Indonesia. Journal of Islamic Economic Laws, 5(1), 38–60. doi:10.23917/jisel.v5i1.17181 Feldmann, H. (2012). Banking deregulation around the world, 1970s to 2000s: The impact on unemployment. International Review of Economics and Finance, 24, 26–42. doi:10.1016/j.iref.2012.01.003 Folawewo, A. O., & Adeboje, O. M. (2017). Macroeconomic determinants of unemployment: Empirical evidence from economic community of West African States. African Development Review, 29(2), 197–210. doi:10.1111/1467-8268.12250 Göçer, İ. (2013). Relation between bank loans and unemployment in the European Countries. Europan Academic Research, 1(6), 981-995. Hassanein, A., & Mostafa, M. M. (2023). Bibliometric network analysis of thirty years of Islamic banking and finance scholarly research. Quality and Quantity, 57(3), 1961–1989. Doi:10.1007/s11135-022-01453-2 Kayed, R. N., & Hassan, M. K. (2011). The global financial crisis and Islamic finance. Thunderbird International Business Review, 53(5), 551–564. doi:10.1002/tie.20434 Khairina, N. N., Syarief, M. E., & Setiawan. (2020). Peran perbankan Syariah dalam penyerapan tenaga kerja pada sektor riil. Human Falah: Jurnal Ekonomi dan Bisnis Islam, 7(1), 117–137. doi:10.30829/hf.v7il.6812 Kongolo, M. (2019). Job creation versus job shedding and the role of SMEs in economic development. Global Journal of Business Management, 13(7), 1–8. Lyu, H., Dong, Z., Roobavannan, M., Kandasamy, J., & Pande, S. (2019). Rural unemployment pushes migrants to urban areas in Jiangsu Province, China. Palgrave Communications, 5(1). doi:10.1057/s41599-019-0302-1 Manser, M. E., & Picot, G. (1999). The role of self-employment in U.S. and Canadian job growth. Monthly Labor Review, 122(4), 10–23. Mucuk, M., & Demirsel, M. T. (2013). The effect of foreign direct investments on unemployment: Evidence from panel data for seven developing countries. Journal of Business, Economics & Finance, 2(3), 53–66. Mumani, H. F. (2014). Islamic finance for SMEs in Jordan. Thesis of Master of Science in Banking and Finance, Eastern Mediterranean University. Nasr, S., & Rostom, A. M. (2013). SME contributions to employment, job creation, and growth in the Arab World. Policy Research Working Paper. doi:10.2139/ssrn.2361164 Neumark, D., Wall, B., & Zhang, J. (2011). Do small businesses create more jobs? New evidence for the United States from the National Establishment Time Series. The Review of Economics and Statistics, 93(1), 16–29. doi:10.1162/REST_a_00060 Oyelana, A. A., & Adu, E. O. (2015). Small and medium enterprises (SMEs) as a means of creating employment and poverty reduction in fort beaufort, Eastern Cape Province of South Africa. Journal of Social Sciences, 45(1), 8–15. doi:10.1080/09718923.2015.11893481 Ritsilä, J., & Tervo, H. (2002). Effects of unemployment on new firm formation: Micro-level panel data evidence from Finland. Small Business Economics, 19(1), 31–40. doi:10.1023/A:1015734424259 Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal, 9(1), 86–136. doi:10.1177/1536867x0900900106 Saifurrahman, A., & Kassim, S. (2021). Islamic financial literacy for Indonesian MSMEs during COVID-19 Pandemic: Issues and importance. Journal of Islamic Finance, 10(1), 45–60. Shabbir, G., Anwar, S.,

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,234
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,325
Écart entre enseignants0,303 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle