In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

In the 1960s, Norway lagged behind its Scandinavian neighbors in the aggregate value of economic production per capita, as it had for decades. By the 1990s, Norway had caught up with and forged ahead of Denmark and Sweden. When and why did Norway catch up? The discovery and extraction of oil in the early 70s is usually suggested as the explanation. But oil alone cannot explain Norway's growth since Sachs and Warner (2001) show that resource-gifts often reverse growth, making oil a curse not a blessing. Moreover, there is the possibility of contracting the Dutch Disease, which involves a rapid and substantial contraction of the traded goods sector. This article explains how deliberate macroeconomic policy, the arrangement of political and economic institutions, a strong judicial system, and social norms contributed to let Norway escape the Resource Curse and the Dutch Disease for more than two decades. Intriguingly, it appears that Norway in the late 90s may show some symptoms. Norway experiences reversed relative growth compared to Denmark and Sweden and a contraction of industrial activity. This article explores the political economy behind this recent slow-down.

Escaping the Resource Curse and the Dutch Disease? When and Why Norway Caught up with and Forged ahead of Its Neighbors

It has been claimed that good environmental performance can improve firms’ economic performance. However, because of e.g. data limitations, the methods applied in most previous quantitative empirical studies on effects of environmental performance on economic performance of firms suffer from several shortcomings. We discuss these shortcomings and conclude that previously applied methods are unsatisfactory as support for a conclusion that it pays for firms to be green. Then we illustrate the consequences of these shortcomings by performing several regression analyses of the effect of environmental performance on economic performance using a panel data set of Norwegian plants. A pooled regression where observable firm characteristics like e.g. size or industry are controlled for, confirms a positive effect of environmental performance on economic performance. However, the estimated positive effect could be due to omitted unobserved variables like management or technology. When the regression model controls for unobserved plant heterogeneity, the effect is generally no longer statistically significant. Hence, although greener plants tend to perform economically better, the analysis provides little support for the claim that it is because they are greener. These empirical findings further indicate that a conclusion that it pays to be green is premature.

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“It Pays to be Green” – A Premature Conclusion?

We investigate the impact of plant downsizing on disability pension utilization in Norway. Plant downsizing substantially increases the disability entry rate of workers in affected plants. Workers originally employed in plants that downsized by more than 60% between 1995 and 2000 were 24% more likely to utilize disability pensions in 2001 than comparable workers in non-downsized plants. We also estimate significant effects of downsizing on future earnings and mortality, which suggest that the increase in disability participation could be driven by an adverse effect of downsizing on the economic opportunities or the health of affected workers. (JEL: H55, I12, I38, J63, J65)

/pdf/the-effect-of-plant-downsizing-on-disability-pension-1jp334ynk7.pdf

The Effect of plant downsizing on disability pension utilization

This paper estimates price and GDP/income elasticities of several energy goods in OECD countries over 1978 to 1999 by applying the one-step GMM estimation method suggested by Arellano and Bond (1991) to a panel data set. The energy demand is specified by a simple partial adjustment model. We find that compared to conventional OLS and Within estimator, the one-step GMM estimator gives more intuitive results in terms of sign and magnitude. The results show that for electricity, natural gas and gas oil demand, price elasticities are in general larger (in absolute value) while GDP/income elasticities are lower in the residential sector than in the industrial sector. This paper yields lower values for price elasticities compared to the results from earlier studies. The longrun GDP/income elasticities found in this paper, however, are quite similar to those found in earlier studies, and are around unity in general.

https://www.econstor.eu/bitstream/10419/192355/1/dp373.pdf

Estimating energy demand elasticities for OECD countries. A dynamic panel data approach

In this paper we analyse how oilrig activity in different Non-OPEC regions is affected by the crude oil price. Oilrig activity outside OPEC is an important indicator for production in the near future, and is more sensitive to the oil price than production from existing fields. We estimate relationships between oilrig activity and crude oil prices using Equilibrium Correction Models (ECM) augmented with a stochastic time trend. The results generally show a positive relationship between oilrig activity and the crude oil price, but the strength of the relationship differs across regions. Rig activity in the US seems to react much faster and stronger to oil price changes compared to other regions. In the long-run the price elasticity in the US is above 1.5. Half the effect is observed after six months. In other regions the long-run elasticity is mainly between 0.5 and 1. Overall, it seems to be a clear relationship between the oil industry structure in the region and the reaction to price changes.

Guro Børnes Ringlund

Papers

Does oilrig activity react to oil price changes? An empirical investigation

Does oilrig activity react to oil price changes? An empirical investigation