Hilde C. Bjørnland

Oil Price Shocks and Stock Market Booms in an Oil Exporting Country

This paper analyses the effects of oil price shocks on stock returns in Norway, an oil-exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non-linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.

The Dynamic Effects of Aggregate Demand, Supply and Oil Price Shocks—A Comparative Study

This paper analyses the dynamic effects of aggregate demand, supply and oil price shocks on GDP and unemployment in Germany, Norway, the UK and the USA, and establishes the role of the different shocks in explaining output fluctuations over time. Symmetries of economic fluctuations across countries are also examined. The different shocks are identified by imposing dynamic restrictions on a structural vector autoregression model. For all countries except Norway, oil price shocks have significant negative effects on output. However, whereas the oil price shock in 1973-74 triggered off a global recession, the recession in the early 1980s was largely caused by other disturbances. Copyright 2000 by Blackwell Publishers Ltd and The Victoria University of Manchester

What Drives Oil Prices? Emerging Versus Developed Economies

We analyze the importance of demand from emerging and developed economies as drivers of the real price of oil over the last two decades. Using a factor-augmented vector autoregressive (FAVAR) model that allows us to distinguish between different groups of countries, we find that demand from emerging economies (most notably from Asian countries) is more than twice as important as demand from developed countries in accounting for the fluctuations in the real price of oil and in oil production. Furthermore, we find that different geographical regions respond differently to oil supply shocks and oilspecific demand shocks that drive up oil prices, with Europe and North America being more negatively affected than emerging economies in Asia and South America. We demonstrate that this heterogeneity in responses is not only attributable to differences in energy intensity in production across regions but also to degree of openness and the investment share in GDP.

Monetary Policy and Exchange Rate Interactions in a Small Open Economy

The transmission mechanisms of monetary policy in a small open economy like Norway are analysed through structural VARs, with special emphasis on the interdependence between monetary policy and exchange rate movements. By imposing a long-run neutrality restriction on the real exchange rate, thereby allowing the interest rate and the exchange rate to react simultaneously to news, I find considerable interdependence between monetary policy and the exchange rate. In particular, following a contractionary monetary policy shock, the real exchange rate immediately appreciates, after which it gradually depreciates back to the baseline. The results are found to be consistent with findings from an “event study”.

Does forecast combination improve Norges Bank inflation forecasts

We develop a system that provides model-based forecasts for inflation in Norway. We recursively evaluate quasi out-of-sample forecasts from a large suite of models from 1999 to 2009. The performance of the models are then used to derive quasi real time weights that are used to combine the forecasts. Our results indicate that a combination forecast improves upon the point forecasts from individual models. Furthermore, a combination forecast out-performs Norges Bank?s own point forecast for inflation. The beneficial results are obtained using a trimmed weighted average. Some degree of trimming is required for the combination forecasts to out-perform the judgmental forecasts from the policymaker.

Boom or gloom? Examining the Dutch disease in two-speed economies

Traditional studies of the Dutch disease do not account for productivity spillovers between the booming resource sector and other domestic sectors. We put forward a simple theory model that allows for such spillovers. We then identify and quantify these spillovers using a Bayesian dynamic factor model. The model allows for resource movements and spending effects through a large panel of variables, while also identifying disturbances to other shocks. Using Australia and Norway as representative cases studies, we find that a booming resource sector has substantial productivity spillovers on non-resource sectors, effects that have not been captured in previous analysis.

Weights and Pools for a Norwegian Density Combination

We apply a suite of models to produce quasi-real-time density forecasts of Norwegian GDP and inflation, and evaluate different combination and selection methods using the Kullback-Leibler information criterion (KLIC). We use linear and logarithmic opinion pools in conjunction with various weighting schemes, and we compare these combinations to two different selection methods. In our application, logarithmic opinion pools were better than linear opinion pools, and score-based weights were generally superior to other weighting schemes. Model selection generally yielded poor density forecasts, as evaluated by KLIC.

House Prices and Stock Prices: Different Roles in the US Monetary Transmission Mechanism

We analyze the role of house and stock prices in the monetary policy transmission mechanism in the U.S. using a structural VAR model. The VAR is identifed using a combination of short-run and long-run (neutrality) restrictions, allowing for contemporaneous interaction between monetary policy and asset prices. By allowing the interest rate and asset prices to react simultaneously to news, we find different roles for house and stock prices in the monetary transmission mechanism. In particular, following a contractionary monetary policy shock, stock prices fall immediately, while the response in house prices is much more gradual. However, the fall in both house prices and stock prices enhances the negative response in output and inflation that has traditionally been found in the literature. Regarding the systematic response in monetary policy, stock prices play a more important role in the interest rate setting in the short run than house prices. As a consequence, shocks to house prices contribute more to GDP and inflation fluctuations than stock price shocks.(This abstract was borrowed from another version of this item.)

Identifying Domestic and Imported Core Inflation

This paper estimates core inflation in Norway, identified as that component of inflation that has no long-run effect on GDP. The model distinguishes explicitly between domestic and imported core inflation. The results show that (domestic) core inflation is the main component of CPI inflation. However, CPI inflation misrepresents core inflation during some periods. The differences are well explained by the other shocks identified in the model, in particular the oil price shocks of the 1970s when Norway imported inflation, and the negative non-core (supply) shocks of the late 1980s, which pushed inflation up temporarily relative to core inflation.

The world is not enough! Small open economies and regional dependence

This paper bridges the new open economy factor augmented VAR (FAVAR) studies with the recent findings in the business cycle synchronization literature emphasizing the importance of regional factors. That is, we estimate and identify a three block FAVAR model with separate world, regional and domestic blocks and study the transmission of both global and regional shocks to four small open economies (Canada, New Zealand, Norway and UK). The results show that foreign shocks explain a major share of the variance in all countries, most so shocks that are common to the world. However, regional shocks also play an important role, explaining more than 20 percent of the variance in the variables. Hence in small open economies, the world is not enough. The regional factors impact the four countries differently, though, some through trade and some through consumer sentiment. Our findings of a strong transmission of both global and regional shocks to open economies are in sharp contrast to the evidence from recently developed open economy DSGE models.