Category Archives: Climate

Damages from Climate Change and the Gains from Complying with the Paris Accord

Computable general equilibrium (CGE) models are a standard tool for policy analysis and forecasts of economic growth. Unfortunately, due to computational constraints, many CGE models are dimensionally small, aggregating countries into an often limited set of regions or using assumptions such as static price-level expectations, where next period’s price is conditional only on current or past prices. This is a concern for climate change modeling, since the effects of global warming by country, in a fully disaggregated and global trade model, are needed, and the known future effects of global warming should be included in forward-looking forecasts for prices and profitability. This work extends a large dimensional intertemporal CGE trade model to account for the various effects of global warming (e.g., loss in agricultural productivity, sea level rise, and health effects) on Gross Domestic Product (GDP) growth and levels for 139 countries, by decade and over the long term, where producers look forward and adjust price expectations and capital stocks to account for future climate effects. The potential economic gains from complying with the Paris Accord are also estimated, showing that even with a limited set of possible damages from global warming, these gains are substantial. For example, with the comparative case of 4C, the global gains from complying with the 2C target  are approximately US$17,489 billion per year in the long run (year 2100). The relative damages from not complying to Sub-Sahara Africa, India, and Southeast Asia, across all temperature ranges, are especially severe.

Earth’s Future open access publication: Click Here

Building a Better Trade Model

Building a Better Trade Model to Determine Local Effects: A Regional and Intertemporal GTAP Model, Economic Modelling, 2017, 102-113.

Intertemporal CGE models allow agents to respond fully to current and future policy shocks. This property is particularly important for trade policies, where tariff reductions span over decades. Nevertheless, intertemporal CGE models are dimensionally large and computationally difficult to solve, thus hindering their development, save for those that are scaled-down to only a few regions and commodities. Using a recently developed solution method, we address this problem by building an intertemporal version of a GTAP model that is large in dimension and can be easily scaled to focus to any subset of GTAP countries or regions, without the need for ‘second best’ recursive approaches. Specifically, we solve using a new parallel-processing technique and matrix reordering procedure, and employ a non-steady state baseline scenario. This provides an effective tool for the dynamic analysis of trade policies. As an application of the model, we simulate a free trade scenario for Vietnam with a focus on the recent Trans-Pacific Partnership (TPP). Our simulation shows that Vietnam gains considerably from the TPP, with 60 per cent of the gains realized within the first 10 years despite our assumption of a gradual and linear removal of trade barriers. We also solve for intertemporal and sector-specific effects on each industry in Vietnam from the trade agreements, showing an added advantage of our approach compared to standard static and recursive GTAP models.

PDF of the full original article: Click Here