Alison Stegman

Can the IPCC SRES Be Improved

* This is a substantially reduced version of a paper entitled “Long Run Projections for Climate Change Scenarios” that was presented at the Stanford Energy Modeling Forum workshop on Purchasing Power Parity versus Market Exchange Rates and is available as a Lowy Institute working paper at http://www.lowyinstitute.org/Publication.asp?pid=129. The original paper covers a wide range of issues whereas this extract focuses on the SRES. The paper has benefited from discussions with Peter Wilcoxen, Barry Bosworth, Ian Castles, Alan Heston, Neil Ferry and many colleagues at the Stanford meeting. The views expressed in the paper are those of the authors and should not be interpreted as reflecting the views of the Institutions with which the authors are affiliated including the trustees, officers or other staff of the Brookings Institution.

Testing For Regime Switching In Singaporean Business Cycles

We examine a Markov-Switching model of Singaporean GDP using a combination of formal moment-based tests and informal graphical tests. The tests confirm that the Markov-Switching model fits the data better than a linear, autoregressive alternative. The methods are extended to allow us to identify precisely which features of the data are better captured by the nonlinear model. The methods described here allow model selection to be related to the intended use of the model.

Simulating emissions intensity targets with energy economic models: algorithm and application

Pressure on developing economies to make quantifiable emissions reduction commitments has led to the introduction of intensity based emissions targets, where reductions in emissions are specified with reference to some measure of economic output. The Copenhagen commitments of China and India are two prominent examples. Intensity targets substantially increase the complexity of policy simulation and analysis, because a given emissions intensity target could be satisfied with a range of emissions and output combinations. Here, a simple algorithm, the Iterative Method, is proposed for an energy economic model to find a unique policy solution that achieves an emissions intensity target at minimum economic loss. We prove the mathematical properties of the algorithm, and compare its numerical performance with other methods’ in the existing literature.

Modelling Complex Emissions Intensity Targets with a Simple Simulation Algorithm

Designing, modelling and analysing global emissions policies are becoming increasingly complex undertakings. Pressure on developing economies to make quantifiable emissions reduction commitments has led to the introduction of intensity based emissions targets, where reductions in emissions are specified with reference to some measure of output, generally gross domestic product. The Copenhagen commitments of China and India are two prominent examples. From a modelling perspective, intensity targets substantially increase the complexity of analysis, with respect to both theoretical design and computational implementation. Here, a clear and practically relevant theoretical design is used to present a new algorithm that can be applied to frameworks that model the complex interaction that occurs between emissions policy instruments, emissions levels and output effects under an emissions intensity target. The coding of the algorithm has been simplified to allow for easy integration into a range of modelling frameworks. Further development of the algorithm that allows for more complex theoretical design structures is possible.

Sectoral Productivity, Structural Change and Convergence

The concept of convergence, defined either narrowly, through productivity or income per capita, or broadly, across a range of economic variables, has become fundamental to the way we assess, analyse and project economic growth in developing economies. To the extent that economic growth projections are designed to reflect empirical behaviour, there is a need to identify relationships between and within key projection variables. To date the empirical analysis of convergence has been controversial. There is a strong argument that economic growth should be projection at a detailed sectoral level (see McKibbin et al (2009)). In practice, data limitations mean that industry level relationships are difficult to uncover and macroeconomic aggregate behaviours are often imposed on disaggregated data. The analysis in this paper attempts to uncover the key cross country trends in sectoral level productivity data. Whilst productivity convergence is evident in some sectors, generally service sectors, it is not evident in others. In part, aggregate convergence trends across developed economies appear to be driven by structural change. We generalise this result and argue that a combination of convergence and structural development assumptions could improve the empirical relevance of economic growth projection models.

A Review of Carbon Trading Theory and Practice

We present a summary of current initiatives to climate change management including a review of existing carbon trading schemes and the economic arguments supporting those schemes. We also outline conditions under which the existing carbon market structures are optimal as well as those under which improvements upon the current schemes can be made.

Long Term Projections of the World Economy - A Review

Economic growth projections are fundamental to long term investment planning by businesses and government. There is an extensive and well developed literature concerned with methodologies for projecting economic growth over short time horizons, but over long horizons, where the goal is to quantify the implications of a particular scenario, the literature is limited. This paper provides a review of publicly available projections of GDP per capita over long time horizons and compares them with projections from a multi-sector model of the world economy called the G-Cubed model. Although there appears to be some general agreement over methodology across the reviewed sources, the projections vary considerably, particularly for developing regions over long time horizons, highlighting the importance and influence of alternative model methodology and assumptions. The comparison with the G-Cubed model builds on previous research that has highlighted the importance of a detailed disaggregated approach to projecting output and productivity that accounts for the dynamic interactions between sectors and across economies. Long term economic issues are becoming increasingly important and economic growth projections are fundamental to both the design and the assessment of long term economic policy alternatives. In addition, our ability to analyse the impact of long term policy alternatives is linked to our ability to model and understand the impact of global economic shocks. Models need to be clear in their methodological design and assumptions, but they also need to be sufficiently complex to account for the important sectoral relationships and international linkages that drive economic growth.