An Overview of the GTAP 9 Data Base

Historically fossil-fuel consumption subsidies have been one of the most widely used energy and public policy interventions. According to the International Energy Agency (IEA), in 2014 they amounted to $493 billion worldwide, which is equivalent to 0.6% of global GDP. Their contribution is even more significant for most energy exporting countries, in many cases exceeding 5-15% of national GDP. However, despite their large magnitude, fossil-fuel consumption subsidies are not explicitly represented in most global economic databases and models, including the Global Trade Analysis Project (GTAP) Data Base, as they are generally not captured by the input-output framework. In this paper, we present methods to integrate pre-tax fossil-fuel consumption subsidies to the GTAP Data Base and produce a version of the GTAP 9.2 Data Base that includes these subsidies. The proposed approach includes updates of energy commodity market prices and corresponding tax rates, within the GTAP Data Base build process. Including fossil-fuel consumption subsidies in the GTAP Data Base provides several benefits for energy and environmental policy simulations, including availability of an additional policy instrument and more consistent representation of energy prices.

Computable general equilibrium (CGE) models are ubiquitous in energy and environmental economic research. Recent technological advancements in electricity fuels, generation technologies, and environmental policies which target specific generation technologies (e.g. emission regulations) have motivated detailed CGE modeling of the electricity sector. Modeling these issues requires distinct electricity generating technologies in a CGE database. Researchers using the Global Trade Analysis Project (GTAP) Data Base have disaggregated the electricity sector into generating technologies independently using largely disparate, incomparable methodologies. This paper presents the methodology used to create the GTAP-Power Data Base, an electricity-detailed extension of the GTAP 9 Data Base with the following disaggregated electricity sectors: transmission and distribution, nuclear, coal, gas, hydroelectric, wind, oil, solar, and other. Gas, oil, and hydroelectric are further differentiated as base and peak load. The "bottom-up" data are electricity generation and levelized input costs for each technology and region. The levelized input costs for each technology are estimated to be as close as possible to the original data, but consistent with the original GTAP 9 Data Base. Major limitations in the initial version of the GTAP-Power Data Base are the lack of regional coverage in input cost data and disparity between available data and the total values for the electricity aggregate. All of the GTAP 9 Data Base is included in the GTAP-Power Data Base.

In this paper, we develop an approach towards incorporation of nutritional accounts for the Global Trade Analysis Project (GTAP) Data Base. We rely on the Food and Agricultural Organization (FAO) food balance sheets data and nutritive indicators to estimate nutritional content of primary commodities and derived commodities represented in primary equivalent within the food balance sheets. Calories, fats, proteins and carbohydrates are estimated and reported. We further identify use categories that account for food, feed, seed, losses and other uses. In terms of food supply, we identify GTAP Data Base primary commodity sectors, food processing sectors and service sectors that supply food. To redistribute nutritional data according to GTAP Data Base sectors, we calculate Leontief inverses, operating only over those sectors (and uses) that supply food. Trade in both primary and processed commodities is taken into account. The approach is applied to all four GTAP 10 Data Base reference years and can be replicated in a dynamic modelling framework for each simulated year (time step).

Introduction The Global Trade Analysis Project (GTAP) model is a global computable general equilibrium (CGE) model which has its origins in the SALTER model (Jomini et al. 1991). Since its inception in 1993, GTAP has become widely used and respected by researchers and policy-makers around the world. In this Appendix we introduce some of the key features of the GTAP database and model, applications of which are used in a number of chapters in this book. We then explain how results from the GTAP model can be analysed and we conclude with a summary of some of the main advantages and limitations of global CGE analysis. The GTAP database The GTAP model and database are publicly available and fully documented; these features enhance the credibility of modelling work and facilitate comparability of analysis. The global database is updated approximately every eighteen months, with contributions coming from throughout the GTAP network of international organisations and country experts. Version 3 of the database comprises 37 commodities and 30 countries (McDougall 1997), while Version 4 of the database comprises 50 commodities and 45 regions (McDougall et al. 1998). In both versions, Indonesia is one of the countries specified and there is a relatively heavy disaggregation for agricultural sectors. Table A1 details the countries and regions in recent versions of the GTAP database, while Table A2 shows the commodity breakdown. To aid computation and to highlight the implications for the regions and sectors of particular interest, the GTAP database is generally aggregated to a smaller number of regions and sectors when running simulations and interpreting results.

We estimate international transportation margin shares by mode of transport for the Global Trade Analysis Project (GTAP) Data Base. For each available origin-destination-GTAP sector triplet, we estimate the fractional share of the transport margin attributable to air, water, and other shipping modes. We use published relationships between ad valorem proportional changes in prices due to transportation costs and distances, weight-value ratios and fuel prices. Our final database contains 344,554 observations (origin-destination-sector-mode combinations) with transportation margin modal shares organized by 228 exporter countries, 209 importer countries, 45 traded GTAP sectors and 3 transportation modes. The main contribution of this article is to bring a more comprehensive set of information on trade by transport mode covering around 65% of global trade in 2004 and 55% in 2011. Our estimated shares contrast with those traditionally used in the GTAP Data Base which are extrapolations based solely on the modes of transport used by US exporters. A comparison of our shares with those used in version 9.0 of the GTAP Data Base reveals that the role of water transportation services in international trade is underestimated, while that of air transportation is overestimated. Overall, we find that estimations using the modal shares in version 9.0 of the GTAP Data Base overestimate the greenhouse gas emissions associated with international transport. Our new data were used to estimate transport margins by mode in Version 9.1 of the GTAP Data Base, and it is expected that our methods will be used to update future versions of the database.

The Global Trade Analysis Project (GTAP) is a global network of researchers and policy makers conducting quantitative analysis of international policy issues. The motivation and ultimate success of the Project stems from the fact that collaboration is essential for detailed analysis of the global economy. The importance of collaboration to improve the quality of policy analysis world-wide is most clearly seen in the development of the GTAP Data Base. The GTAP Data Base is the centerpiece of the Global Trade Analysis Project. It records the annual flows of goods and services for the entire world economy in the benchmark year(s). It consists of bilateral trade, transport, and protection matrices that link individual country/regional economic data bases. The production of the GTAP Data Base relies on the valuable contributions of many individuals and organizations throughout the world. Individuals contribute the best available input-output table for their country, while other experts contribute the macro, trade, protection and other data required. The Center for Global Trade Analysis, the home of GTAP, then brings these contributions together into one useable, globally consistent, database. The result is a fully documented , publicly available and regularly updated global database. This year (2012), the eighth version of the GTAP Data Base was released, covering 129 countries, 57 sectors, 5 factors and two base years (2004 and 2007). The GTAP Data Base is utilized in a suite of comparative static and dynamic computable general equilibrium models and underlies most contemporary economic analysis of global policy issues related to trade, energy and the environment.

Constructing a balanced and sufficiently detailed Social Accounting Matrix (SAM) is a necessary step for any work with Computable General Equilibrium (CGE) models. Even when starting with a given SAM, researchers might wish to develop their own, more detailed variants for a specific study by dis-aggregating sectors and products, a process termed splitting the SAM. We review three approaches for balancing and splitting a SAM: Cross-Entropy (CE), a Highest Posterior Density (HPD) estimator resulting in a quadratic loss penalty function, and a linear loss penalty function. The exercise considers upper and lower bounds on the (new) SAM entries, different weights for penalizing deviations from a priori information, and unknown row or column totals, to give the user flexibility in controlling outcomes. The approaches are assessed first by a systematic Monte-Carlo experiment. It re-balances smaller SAMs, after errors with known distributions are added. Here we find quite limited numerical differences between the CE and quadratic loss approaches. The CE approach was however considerably slower than the other candidates. Second, we tested the three approaches for dis-aggregating the Global Trade Analysis Project (GTAP) data base to provide, as an example, further agri-food detail. In such empirical applications, the distribution of the errors of the new SAM entries is typically not known. As in the SAM balancing exercise, we use CONOPT4 as a multi-purpose (non)linear solver which can be also be employed to solve the CGE model itself. For comparison, we add the specialized Linear and Quadratic Programming (QP) solvers CPLEDX and GUROBI. As in the Monte-Carlo experiment, the differences in results between the three approaches were moderate. The specialized solvers require very little time to solve the linear and quadratic loss problems. However, they did not achieve the same, very high accuracy as CONOPT4 for the quadratic loss problem. The CE problem could take longer by a factor of 100 or more, compared to a linear or quadratic loss approach solved with the specialized solvers. We conclude that using linear or quadratic loss approaches, especially combined with a specialized solver, are the most suitable candidates for larger SAM splitting / balancing problems. Additionally, we present a fast and accurate data processing chain to yield a benchmark data set for a CGE model from the GTAP Data Base which involves filtering out small cost, expenditure and revenue shares, and allows users to introduce further product and sectoral detail based on user provided information.

In the interest of including additional countries from the Caribbean into the Global Trade Analysis Project (GTAP) database to support economic analysis on these countries, the Inter-American Development Bank commissioned the inclusion of Jamaica, Trinidad & Tobago, Puerto Rico and the Dominican Republic into version 8.2 (and 9) of the GTAP database. The document describes the process of transforming the original input-out and supply use tables of these four Caribbean countries into the GTAP format. Further details on the GTAP database may be found at www.gtap.org.

In the interest of updating the input-output data of Paraguay in the Global Trade Analysis Project (GTAP) database to support economic analysis in this country, the Inter-American Development Bank commissioned the update of these data using the data from a 2009 social accounting matrix (SAM) developed by Cicowiez and Santander (2015). The document describes the process of transforming the 2009 SAM of Paraguay into the GTAP format. Further details on the GTAP database may be found at www.gtap.org.

This book, drawn from the Global Trade Analysis Project (GTAP), aims to help readers conduct quantitative analysis of international trade issues in an economy-wide framework. In addition to providing a succinct introduction to the GTAP modelling framework and data base, this book contains seven of the most refined GTAP applications undertaken to date, covering topics ranging from trade policy to the global implications of environmental policies, factor accumulation and technological change. The authors of the applications are representative of the broader group of GTAP users. Some are academics, while others are professional economists in national and international agencies. All of their studies can be independently replicated by the reader through accessing software and files via the Internet. Readers can also explore the sensitivity of results to varying assumptions and use the applications to launch independent research projects.

The making of projections often requires an economy-wide perspective, and the estimation of consumer demands at the international level. In this paper, an implicit, directly additive demand system (AIDADS) is estimated using cross-country data on consumer expenditures from the International Comparison Program (ICP), and then from Global Trade Analysis Project (GTAP) data. The two data sets are found to produce results that are quite consistent despite their differing origins, and the fact that the former is based on consumer goods that embody wholesale/retail margins, while margin demands are treated separately in GTAP. Given the similarity of the results, the estimation based on GTAP data is favored because it is readily matched to input-output based production and trade data, and provides valuable new information concerning how aggregate margin expenditures are related to per capita income.

The making of projections often requires an economy-wide perspective, and the estimation of consumer demands at the international level. In this paper, an implicit, directly additive demand system (AIDADS) is estimated using cross-country data on consumer expenditures from the International Comparison Program (ICP), and then from Global Trade Analysis Project (GTAP) data. The two data sets are found to produce results that are quite consistent despite their differing origins, and the fact that the former is based on consumer goods that embody wholesale/retail margins, while margin demands are treated separately in GTAP. Given the similarity of the results, the estimation based on GTAP data is favored because it is readily matched to input-output based production and trade data, and provides valuable new information concerning how aggregate margin expenditures are related to per capita income.

With a wide range of implications for welfare, food security, land use, trade and the environment, nutrition-related policies pose complex questions that should be assessed using an approach that properly accounts for all the involved interactions. Widely used partial equilibrium models fail to properly account for the post-farmgate food value chains. At the same time, most of the available integrated assessment and computable general equilibrium models have some major limitations in terms of the consistent representation of nutritional data flows. In this paper, we address some of the limitations identified in the literature and develop an approach for incorporating nutritional accounts into the Global Trade Analysis Project (GTAP) Data Base, tracing quantities of food, calories, fats, proteins and carbohydrates along the value chains. We further showcase how the developed nutritional database can be linked to the standard GTAP model. A sample application is developed in the paper to provide an assessment of the impact of import tariff elimination on nutritional flows.

Water is an essential input in the production processes of all goods and services. However, most economic models ignore water as an essential factor of production. In contrast with other inputs, economic data do not reflect the role of water in the production processes of goods and services and its final value in the demand side. This makes it difficult to incorporate water in economic models, properly examine its role in economic activities, and study its interaction with other inputs in the production processes. Introducing water into an economy-wide database such as Global Trade Analysis Project (GTAP) Data Base which has been widely used by many economic modelers across the world could help them to extend their research agendas on the role and importance of water in economic activities. As the first step towards this direction we divided the crop sectors of the GTAP-Power Data Base (which extends the GTAP Data Base Version 9 by disaggregating the electricity sector) into irrigated and rainfed categories and explicitly included water for irrigation into the cost structure of irrigated crops by river basin at the Agro Ecological Zone (AEZ) level.

According to the Global Burden of Disease study (Cohen et al., 2017), in 2015 ambient air pollutant emissions caused 4.2 million deaths and a loss of 103.1 million disability-adjusted life-years, making it the fifth-ranked global risk factor. In terms of the welfare costs of mortality and illnesses associated with outdoor air pollutant emissions, global estimates for 2015 range between $2.7-3.2 trillion (Coady et al., 2015; OECD, 2016). Still, while greenhouse gas emissions are usually well represented in many global economic databases and models, air pollutant emission accounts in most cases are not included. In particular, this is the case for the widely used Global Trade Analysis Project (GTAP) Data Base and model. In this paper we describe the methodology used to produce a global air pollutant emissions dataset consistent with the GTAP Data Base version 10A. In addition to the non-land use sources, emissions from land use activities are estimated by land cover type, based on the volume of burned biomass and emission factors. The emissions database can be readily incorporated in GTAP-based computable general equilibrium models, enabling assessments of a wide range of policy questions, including the health co-benefits from climate mitigation policies. We illustrate an application of the air pollutant emissions database by tracking changes in primary PM2.5 emissions embodied in trade between 2004 and 2014.