Bank loan terms and conditions: is there a macro effect?

We examine whether macroeconomic factors contain significant information for bank loan contracting terms and conditions (T&Cs), over and above that of standard firm-specific or country-level institutional factors. Our estimation is based on a seemingly unrelated mixed-processes methodology that accommodates two salient data properties: (i) the fact that loan contract terms are determined jointly as a single lending contract, and (ii) the fact that the elements of loan T&Cs are generated by different distributional formats. Our findings indicate that cross-country variation accounts for a significant portion of observed variation in loan T&Cs. In addition, macroeconomic fundamentals significantly explain the “package” of loan T&Cs offered to corporate borrowers, with this effect being distinct from any influence that T&Cs receive from firm-specific factors, and also from country-specific institutional factors.

Are mortgage lenders guilty of the housing bubble? A UK perspective

Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.