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Do real estate loans reflect regional banking and economic conditions?

Author

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  • Amit Ghosh

Abstract

Purpose - Using state-level data, the purpose of this paper is to examine state banking-industry specific as well as region economic determinants of real estate lending of commercial banks across all 51 states spanning the period 1966-2014. Design/methodology/approach - Using both fixed-effects and dynamic-generalized method of moments (GMM) estimation techniques the study compares the sensitivity of different categories of real estate loans to regional banking and economic conditions. Finally, it provides a comparative perspective by comparing the results for real estate loans with other categories of loans given out by banks. Findings - Greater capitalization, liquidity and overhead costs reduce real estate lending, while banks diversification and the size of the banking industry in each state increase such lending. Moreover, real estate loans are found to be procyclical to state economic cycles with a rise in state real gross domestic product (GDP) growth, increase in state housing price index (HPI) and decline in both inflation and unemployment rates, increasing real estate loans. Within disaggregated loan types, construction and land development and single-family residential loans are most responsive to state banking and economic conditions. Originality/value - The recent financial turmoil is to a large extent attributable to excessive risk-taking by banks, particularly in terms of real estate lending. Hence, it is of paramount importance to empirically address the various determinants of real estate lending. With most banks restricting their operations in either one or a few states only, real estate lending in any given state may be more sensitive to regional banking and economic conditions than national aggregates. The present study is the first of its type to perform such an analysis.

Suggested Citation

  • Amit Ghosh, 2016. "Do real estate loans reflect regional banking and economic conditions?," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 8(1), pages 37-63, April.
  • Handle: RePEc:eme:jfeppp:v:8:y:2016:i:1:p:37-63
    DOI: 10.1108/JFEP-09-2015-0050
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    Cited by:

    1. Oksana Omelchenko & Oleksandr Dorokhov & Oleg Kolodiziev & Liudmyla Dorokhova, 2018. "Fuzzy Modeling of the Creditworthiness Assessments of Bank’s Potential Borrowers in Ukraine," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 100-125.

    More about this item

    Keywords

    Mortgages; Banks; Financial institutions and services; Models with panel data; Real estate services; R10; R11; E32; G21; G28; C23;
    All these keywords.

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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