The hidden liquidity cost of pawn expansion: Evidence from Pegadaian
DOI:
https://doi.org/10.61511/jembar.v4i2.2027.3546Keywords:
asset-liability management, liquidity risk, non-bank financial intermediation, pawn, PegadaianAbstract
Background: Pawn finance provides households with access to collateralized liquidity, but less is known about how growth in core pawn receivables is associated with the lender’s own short-horizon balance-sheet liquidity. This study examines that relationship for Pegadaian and evaluates whether the observed pattern is consistent with short-run asset–liability adjustment. Methods: The analysis uses 101 monthly observations from January 2017 to May 2025. Liquidity is proxied by the current ratio, while pawn expansion is measured by the monthly log growth of outstanding core pawn receivables. The baseline dynamic regression uses 98 observations after transformations and lags and applies Newey–West heteroskedasticity- and autocorrelation-consistent inference. Findings: Pawn-receivable growth is associated with a statistically significant same-month decline in the current ratio. A positive one-month coefficient in the baseline specification is consistent with partial subsequent adjustment, although this lagged association is less stable across robustness specifications and the cumulative two-month association is not statistically distinguishable from zero. The contemporaneous result remains robust to alternative heteroskedasticity and autocorrelation consistent (HAC) bandwidths, calendar-month controls, and a log transformation of the liquidity outcome, while formal stability tests indicate no detectable structural break. Current assets and current liabilities both increase contemporaneously with pawn-receivable growth, with the liability coefficient numerically larger. Conclusion: The findings are consistent with short-horizon balance-sheet liquidity pressure accompanying rapid pawn-receivable growth, but they do not establish a causal effect. Novelty/Originality of this article: The study shifts the pawn-finance discussion from customer-side liquidity toward institution-side short-horizon balance-sheet adjustment using monthly evidence from a major collateral-based nonbank lender.
References
Acharya, V. V., Cetorelli, N., & Tuckman, B. (2026). Where do banks end and NBFIs begin? The Review of Corporate Finance Studies, 15(3), 627–659. https://doi.org/10.1093/rcfs/cfag012
Aldasoro, I., Doerr, S., & Zhou, H. (2025). Non-bank lending during crises. Review of Finance, 29(6), 1809–1832. https://doi.org/10.1093/rof/rfaf043
Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856. https://doi.org/10.2307/2951764
Aramonte, S., Schrimpf, A., & Shin, H. S. (2021). Non-bank financial intermediaries and financial stability. BIS Working Papers, No. 972. Bank for International Settlements.
Banerjee, R., & Serena, J.-M. (2026). Dampening the financial accelerator? Direct lenders and monetary policy. Journal of Money, Credit and Banking, 58(4), 1017–1049. https://doi.org/10.1111/jmcb.13237
Bechtel, A., Ranaldo, A., & Wrampelmeyer, J. (2023). Liquidity risk and funding cost. Review of Finance, 27(2), 399–422. https://doi.org/10.1093/rof/rfac020
Beirne, J., Renzhi, N., & Volz, U. (2023). Non-bank finance and monetary policy transmission in Asia. Emerging Markets Finance and Trade, 59(6), 1976–1991. https://doi.org/10.1080/1540496X.2022.2156279
Brooks, C. (2019). Introductory econometrics for finance (4th ed.). Cambridge University Press. https://doi.org/10.1017/9781108524872
Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society: Series B (Methodological), 37(2), 149–163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
Chernenko, S., Erel, I., & Prilmeier, R. (2022). Why do firms borrow directly from nonbanks? The Review of Financial Studies, 35(11), 4902–4947. https://doi.org/10.1093/rfs/hhac016
Claessens, S. (2024). Nonbank financial intermediation: Stock take of research, policy, and data. Annual Review of Financial Economics, 16, 273–294. https://doi.org/10.1146/annurev-financial-082123-105416
Cornelli, G., Frost, J., Gambacorta, L., & Jagtiani, J. (2024). The impact of fintech lending on credit access for U.S. small businesses. Journal of Financial Stability, 73, 101290. https://doi.org/10.1016/j.jfs.2024.101290
Cucic, D., & Gorea, D. (2026). Nonbank lending and the transmission of monetary policy. The Review of Financial Studies, 39(4), 966–1014. https://doi.org/10.1093/rfs/hhaf096
Davydiuk, T., Marchuk, T., & Rosen, S. (2024). Market discipline in the direct lending space. The Review of Financial Studies, 37(4), 1190–1264. https://doi.org/10.1093/rfs/hhad081
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431. https://doi.org/10.1080/01621459.1979.10482531
Donaldson, J. R., Piacentino, G., & Thakor, A. V. (2021). Intermediation variety. The Journal of Finance, 76(6), 3103–3152. https://doi.org/10.1111/jofi.13084
Durdu, C. B., & Zhong, M. (2023). Understanding bank and nonbank credit cycles: A structural exploration. Journal of Money, Credit and Banking, 55(1), 103–142. https://doi.org/10.1111/jmcb.12918
Elliott, D., Meisenzahl, R. R., & Peydró, J.-L. (2024). Nonbank lenders as global shock absorbers: Evidence from US monetary policy spillovers. Journal of International Economics, 149, 103908. https://doi.org/10.1016/j.jinteco.2024.103908
Erel, I., & Inozemtsev, E. (2025). Evolution of debt financing toward less-regulated financial intermediaries in the United States. Journal of Financial and Quantitative Analysis, 60(3), 1234–1271. https://doi.org/10.1017/S0022109024000206
Financial Stability Board. (2025). Global monitoring report on nonbank financial intermediation 2025. Financial Stability Board
Fleckenstein, Q., Gopal, M., Gutiérrez, G., & Hillenbrand, S. (2026). Nonbank lending and credit cyclicality. The Review of Financial Studies, 39(4), 925–966. https://doi.org/10.1093/rfs/hhaf024
Forbes, K. J., Friedrich, C., & Reinhardt, D. (2023). Stress relief? Funding structures and resilience to the COVID shock. Journal of Monetary Economics, 137, 47–81. https://doi.org/10.1016/j.jmoneco.2023.05.005
Gopal, M., & Schnabl, P. (2022). The rise of finance companies and FinTech lenders in small business lending. The Review of Financial Studies, 35(11), 4859–4901. https://doi.org/10.1093/rfs/hhac034
Hung, T.-C., & Lin, C.-Y. (2022). Key sustainable factors of the pawnbroking industry: An empirical study in Taiwan. Sustainability, 14(19), 12669. https://doi.org/10.3390/su141912669
Inoue, T. (2021). The role of pawnshops in risk coping in early twentieth-century Japan. Financial History Review, 28(3), 319–343. https://doi.org/10.1017/S0968565021000111
Irani, R. M., Iyer, R., Meisenzahl, R. R., & Peydró, J.-L. (2021). The rise of shadow banking: Evidence from capital regulation. The Review of Financial Studies, 34(5), 2181–2235. https://doi.org/10.1093/rfs/hhaa106
Li, L., Li, Y., Macchiavelli, M., & Zhou, X. (2021). Liquidity restrictions, runs, and central bank interventions: Evidence from money market funds. The Review of Financial Studies, 34(11), 5402–5437. https://doi.org/10.1093/rfs/hhab065
Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303. https://doi.org/10.1093/biomet/65.2.297
Ma, Y., Xiao, K., & Zeng, Y. (2022). Mutual fund liquidity transformation and reverse flight to liquidity. The Review of Financial Studies, 35(10), 4674–4711. https://doi.org/10.1093/rfs/hhac007
MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal of Applied Econometrics, 11(6), 601–618. https://doi.org/10.1002/(SICI)1099-1255(199611)11:6<601::AID-JAE417>3.0.CO;2-T
Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. https://doi.org/10.2307/1913610
Newey, W. K., & West, K. D. (1994). Automatic lag selection in covariance matrix estimation. The Review of Economic Studies, 61(4), 631–653. https://doi.org/10.2307/2297912
Otoritas Jasa Keuangan. (2016). Peraturan Otoritas Jasa Keuangan Republik Indonesia Nomor 31/POJK.05/2016 tentang Usaha Pegadaian. Otoritas Jasa Keuangan
Otoritas Jasa Keuangan. (2024). Peraturan Otoritas Jasa Keuangan Republik Indonesia Nomor 39 Tahun 2024 tentang Pergadaian. Otoritas Jasa Keuangan.
Sarmiento, M. (2025). The transmission of non-banking liquidity shocks to the banking sector. Latin American Journal of Central Banking, 6(2), 100139. https://doi.org/10.1016/j.latcb.2024.100139
Soedarmono, W., Gunadi, I., Pambudi, S., & Nurhayati, T. (2023). Monetary policy, funding liquidity, and undisbursed loans in Indonesia: The bank lending channel revisited. Journal of Economics and Business, 127, 106134. https://doi.org/10.1016/j.jeconbus.2023.106134
Susamto, A. A., Octavio, D. Q., Risfandy, T., & Wardani, D. T. K. (2023). Public ownership and local bank lending at the time of the COVID-19 pandemic: Evidence from Indonesia. Pacific-Basin Finance Journal, 80, 102072. https://doi.org/10.1016/j.pacfin.2023.102072
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