Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Mandelbrot (1960) proposed using the so-called Pareto-Lévy class of distributions as a framework for representing income distributions. We argue in this paper that the Pareto-Lévy distribution is an interesting candidate for representing income distribution because its parameters are easy to interpret and it satisfies a specific invariance-under-aggregation property. We also demonstrate that the Gini coefficient can be expressed as a simple formula of the parameters of the Pareto-Lévy distribution. We subsequently use Terms of use: Documents in EconStor may

Husholdningenes kjøpekraft i boligmarkedet har betydning for etterspørselen etter bolig. Vi analyserer kjøpekraft i boligmarkedet ved å sammenstille fordelingen av prisen på omsatte boliger med fordelingen av hvor dyre boliger husholdningene kan lånefinansiere. Det siste beregnes med utgangspunkt i husholdningenes gjeldsdisponible inntekt, bankenes boliglånsrente, avdrag samt krav til betjeningsevne. Ved beregning av gjeldsdisponibel inntekt kontrollerer vi for utgifter til alminnelig forbruk. Formue og egenkapital inngår ikke i beregningen av kjøpekraft. For store grupper er kjøpekraften opprettholdt over tid til tross for betydelig høyere boligpriser. I Oslo har kjøpekraften utviklet seg relativt svakt de senere år sammenlignet med andre større byer og landet totalt sett.

Abstract:We use a dynamic factor model and a detailed panel data set with quarterly accounts data on all Norwegian banks to study the effects of banks' funding costs on their retail rates. Banks' funds are categorized into two groups: customer deposits and long-term wholesale funding (market funding from private and institutional investors including other banks). The cost of market funding is represented in the model by the three-month Norwegian Inter Bank Offered Rate (NIBOR) and the spread of unsecured senior bonds issued by Norwegian banks. Our estimates show clear evidence of incomplete pass-through: a unit increase in NIBOR leads to an approximately 0.8 increase in bank rates. On the other hand, the difference between banks' loan and deposit rates is independent of NIBOR. Our findings are consistent with the view that banks face a downward-sloping demand curve for loans and an upward-sloping supply curve for customer deposits. Keywords

We analyze the effect of house price changes on debt secured on dwellings in Norway. To this end, we use both macro time series and micro panel data. With the intention of being both a cross-check and motivation for the micro analysis, we estimate a structural vector auto regression using macro variables. A key result of the macro analysis is that positive house price innovations have positive and persistent effects on households debt secured on dwellings.Results from the micro data analysis suggest that the effect of house price changes on the borrowing decision differs from the effect on the instalment decision among existing home owners. These results are further investigated trough a two stage model where we control for income, collateral value and age. The model predicts that the size of both loans and instalments increase with income. Loan sizes increase and the instalments fall with increasing collateral value. The results support the existence of a wealth channel but do not provide support for a collateral channel.

We use a dynamic factor model and a detailed panel data set for six Norwegian bank groups to analyze i) how funding costs affect retail loan rates and ii) how retail rate differences between banks affect market shares. The data set consist of quarterly data for 2002Q1-2011Q3 and include information on loan volumes and retail (interest) rates for loans to firms and households. The cost of market funding is represented in our analysis by the three-month money market rate and a proxy for market risk -the credit spread on unsecured senior bonds issued by Norwegian banks. Our estimates clearly suggest incomplete pass-through: a 10 basis points increase in the market rate leads to an approximately 8 basis points increase in retail loan rates. We also find that credit demand from households is more elastic with regard to the loan rate than demand from businesses.