The stock market and investment in the small and open Norwegian economy

The relationship between the stock market and investment is analyzed by utilizing a multivariate vector autoregressive model, which also includes fundamentals represented by production and the bank interest rate. Two important results appear on the basis of data from the small, open economy of Norway. The financial market has no lead effect on real activity, as neither the stock market nor the credit market can predict future investment or production. On the contrary, current stock returns correlate negatively with lagged growth in investment, and positively with current growth in production. In addition, changes in the bank interest rate have a positive effect on future stock returns, production leads investment positively, and both production and the bank interest rate become exogenous variables in our model. First version received: November 1997/Final version received: October 2000     

Optimum Currency Areas Under Inflation Targeting

Several countries face the choice between targeting inflation independently and entering a monetary union that targets inflation. The present paper extends the theory of optimum currency areas to deal with this choice. In contrast to the conventional theory, countries might form more of an optimum currency area the more asymmetric supply shocks are.     

Granger-causality in multiple time series

The concept of Granger-causality is formulated for a finite-dimensional multiple time series. Special attention is given to causality patterns in autoregressive series, and it is shown how these patterns can be tested under quite general assumptions using a χ² statistic. The power of the test is discussed, and it is shown that the χ² statistic results from a Lagrange multiplier test in the Gaussian case. The causality test is tried both on artificial data and some economic time series. Finally we consider the problem of constrained estimation in models with a known causality structure.     

Portfolio optimization under model uncertainty and BSDE games

We consider robust optimal portfolio problems for markets modeled by (possibly non-Markovian) Itô–Lévy processes. Mathematically, the situation can be described as a stochastic differential game, where one of the players (the agent) is trying to find the portfolio that maximizes the utility of her terminal wealth, while the other player (“the market”) is controlling some of the unknown parameters of the market (e.g., the underlying probability measure, representing a model uncertainty problem) and is trying to minimize this maximal utility of the agent. This leads to a worst case scenario control problem for the agent. In the Markovian case, such problems can be studied using the Hamilton–Jacobi–Bellman–Isaacs (HJBI) equation, but these methods do not work in the non-Markovian case. We approach the problem by transforming it into a stochastic differential game for backward stochastic differential equations (a BSDE game). Using comparison theorems for BSDEs with jumps we arrive at criteria for the solution of such games in the form of a kind of non-Markovian analogue of the HJBI equation. The results are illustrated by examples.     

Cost structure and capacity in the Norwegian pelagic fisheries

The parameters of the short-run cost function are estimated for three vessel types taking part in the Norwegian pelagic fisheries: purse seine vessels, trawlers, and coastal vessels. The generalized translog functional form is used. Estimates of returns to scale are calculated and the results indicate that there are substantial economies of scale in all vessel classes. It is further investigated whether excess capacity varies with vessel size and age. The analysis suggests increased quotas per vessel to avoid rent dissipation. With the total allowable catch given, the number of participating vessels must be reduced.     

Interest rate model comparisons for participating products under Solvency II

Under the Solvency II regulatory framework it is essential for life insurers to have an adequate interest rate model. In this paper, we investigate whether the choice of the interest rate model has an impact on the valuation of the best estimate of the liabilities. We use three well-known interest rate models; the CIR++-model, the G2++-model and the Libor Market model. Our numerical results show that for low to medium durations of the liabilities and a relatively low proportion of credit bonds in the asset portfolio, the three interest rate models produce quite similar values for the best estimate liabilities. However, for large durations of the liabilities, or a large bond proportion, or both, the differences can be quite large. There is no easy answer to the question of which model should be used in cases where the choice of interest rate model has a significant impact. Based on the study described in this paper, our advice is to use the G2++-model, which seems to represent an appropriate trade-off between accuracy and complexity.     

House prices,credit and the effect of monetary policy in Norway: evidence from structural VAR models

This paper investigates the responses of house prices and household credit to monetary policy shocks in Norway, using Bayesian structural VAR models. The analysis indicates that the effect of a monetary policy shock on house prices is large, while the effect on household credit is muted. This is consistent with a relatively small refinancing rate (refinancing rate refers to the share of outstanding mortgages that are refinanced each period due to changes in, for example, house prices or interest rate) of the mortgage stock each quarter. Using monetary policy to guard against financial instability by mitigating property-price movements may prove effective, but trying to mitigate household credit may prove costly in terms of GDP and inflation variation.