This paper investigates the determinants of Norwegian import prices of manufactures over the period 1970(1) - 1991(4). Multivariate cointegration analysis establishes a long-run relationship between import prices, foreign prices, the exchange rate and domestic unit labour costs. Normalized on...

The parameters in the cointegration vector and the loading parameters are not the only interesting parameters in a vector cointegration model. With a reformulation of the model the intercept parameters can be decomposed into growth parameters and cointegration mean parameters. These parameters...

The paper describes a procedure for decomposing the deterministic terms in cointegrated VAR models into growth rate parameters and cointegration mean parameters. These parameters express long-run properties of the model. For example, the growth rate parameters tell us how much to expect...

In a system with n input factors there are n − 1 independent cost shares. An often-used approach in estimating factor demand systems is to (implicitly or explicitly) assume that there is a (independent) cointegrating relationship for each of the n − 1 independent cost shares. However, due to...

The financial crisis has brought the interaction between housing prices and household borrowing into the limelight of economic policy debate. This paper examines the nexus of housing prices and credit in Norway within a structural vector equilibrium correcting model (SVECM) over the period...

We study whether the response of the economy to structural shocks changes at the zero lower bound. Monte Carlo evidence suggests that VARs have a limited ability to detect changes in impulse response functions at the ZLB compared to the standard environment with positive interest rates. This...

This paper aims to forecast the Market Risk premium (MRP) in the US stock market by applying machine learning techniques, namely the Multilayer Perceptron Network (MLP), the Elman Network (EN) and the Higher Order Neural Network (HONN). Furthermore, Univariate ARMA and Exponential Smoothing...

This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply different regression models, based on household covariates and previous-year equivalence income, to classify a...

This paper uses imperfect competition as a basis for modelling the export price for an aggregated commodity produced by the Norwegian private mainland economy. The long run solution is analysed using a cointegration technique. The dynamics are modelled according to two different approaches; a...