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The Cost of Borrowing as a Limiting Factor of Non-Life Insurance Development: The Italian Case

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  • Giovanni Millo

    (Dipartimento di Scienze Economiche, Aziendali, Matematiche e Statistiche (DEAMS), University of Trieste, 34127 Trieste, Italy)

Abstract

We address the effect of local financial conditions on the demand for non-life insurance. We consider the spread between the interest rates faced by the insured on the local credit market and the return rates earned by the insurer on national or international financial markets, sketching how it influences the present value of an insurance policy; we then use the local invariance of the insurer’s returns to identify the effect on demand. Drawing on a panel of Italian provinces with ample variability in insurance density as well as borrowing conditions, we show that the demand for non-life insurance decreases with the borrowing rate. We separate between different non-life insurance lines, finding a stronger effect for the lines prevailing in advanced economic systems. Credit conditions turn out to be an important factor of non-life insurance development, and they help to explain the underdevelopment of insurance markets in Southern Italy.

Suggested Citation

  • Giovanni Millo, 2024. "The Cost of Borrowing as a Limiting Factor of Non-Life Insurance Development: The Italian Case," Risks, MDPI, vol. 12(12), pages 1-15, November.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:12:p:189-:d:1530883
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    References listed on IDEAS

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    1. Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006. "Unobserved heterogeneity in panel time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2361-2380, May.
    2. Millo, Giovanni, 2014. "Maximum likelihood estimation of spatially and serially correlated panels with random effects," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 914-933.
    3. MOSSIN, Jan, 1968. "Aspects of rational insurance purchasing," LIDAM Reprints CORE 23, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Millo, Giovanni, 2017. "A simple randomization test for spatial correlation in the presence of common factors and serial correlation," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 28-38.
    5. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
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