Introduction

The GDyn Data Base, used with the GDyn model, is based on the GTAP Data Base, which describes the global economy in a given year (2001 for the GTAP 6 Data Base; Dimaranan 2006). The GTAP Data Base is augmented with additional data required for GDyn, the dynamic version of the GTAP model. This chapter covers the preparation of these additional elements of the GDyn Data Base1 and the manipulation and aggregation of the GDyn Data Base with various utility programs. The focus is on the additional data requirements, with minimal discussion of the dynamic parameters (see Chapter 3). Readers interested in the underlying GTAP Data Base are referred to Dimaranan (2006).

The GTAP Data Base (Dimaranan, 2006) is changed in the following three ways to obtain a database for GDyn:

1. Five new arrays, listed in Table 4.1, are added to the standard GTAP data file. The values of the regional savings array also change from those in the standard GTAP Data Base, although the dimensions of the array do not change. These changes are discussed in Section 2.

2. A new parameters file contains the seven new parameters used in the dynamic theory (Table 4.2). The methodology for estimating econometrically, and in some cases calibrating these parameters, was examined in detail in Chapter 3. In this chapter the procedure for assigning values to these parameters in the standard GDyn Data Base is outlined. These changes are discussed in Section 3.

3. […]

Introduction

The use of welfare measures is now commonplace in many AGE applications. The calculation and decomposition of welfare have become important parts of the analytical tools used to evaluate and/or compare the impact of policies on regions. In dynamic models, in which the importance of capital ownership features significantly, welfare measures are clearly superior to the use of real GDP as a measure of assessing the benefits of a policy. This is because GDP is defined as goods and services produced in the country, rather than as ownership of produced goods and services. However, calculating and decomposing welfare in a dynamic model are much more difficult tasks than in the traditional comparative static models.

The aim of this chapter is to develop a method for decomposing welfare in the GDyn model presented in Chapter 2. In fulfilling this aim, a number of practical problems associated with decomposing welfare in the GDyn model arise. These problems are discussed and a solution is proposed. It involves a comparative static simulation that allows us to decompose the welfare change resulting from a policy shock at any year during the simulation horizon. The method is illustrated using an example.

The Welfare Decomposition

The welfare decomposition used in the GDyn model is based on the welfare decomposition outlined in Hertel and Huff (2001) for the comparative static GTAP model. Hanslow (2000) generalized it, showing that the decomposition can be applied to other models; for example, with multiple households and/or foreign income flows resulting from foreign capital ownership, remittances, or foreign aid.

Introduction

In the 1990s, there was a flood of regional trade agreements. By 2001, more than 130 such agreements were in place (WTO2000). The European Union, the North America Free Trade Agreement (NAFTA), and MERCOSUR have been particularly effective at promoting intraregional trade. This success has led other countries to explore options for such regional agreements, and in December 1999, Japan and Singapore established a Joint Study Group to examine the feasibility and desirability of establishing an FTA. After a favorable report from the Study Group, negotiations commenced in early 2001 (Joint Study Group 2000a), and the Japan-Singapore FTA came into effect in November 2002.

The main elements of the Japan-Singapore FTA involve bilateral liberalization and facilitation of trade through reduction of tariff and nontariff barriers, as well as the mutual recognition of national standards, streamlining of customs procedures, facilitation of increased services trade, and the establishment of an exemplary framework for foreign investment. This “new-age” FTA also envisioned increased collaboration on intellectual property, education and training, media and broadcasting, and tourism. This trade agreement is particularly significant, because it is viewed by many as providing a possible template for future FTAs in the region, for example the FTA between Japan and Korea (KIEP 2000).

With the launch of the GTAP project two decades ago it became possible for economists who are not specialists in AGE modeling to start using the general equilibrium approach for economic policy analysis, while at the same time avoiding the excessive costs of collecting data and programming. Not only the large number of citations of the first GTAP book documenting the standard GTAP model (Hertel 1997) but also the large number of individuals around the world using different versions of the framework and the database for policy research and analysis are testimony to the success of this project.

The GTAP network of researchers and analysts has been a key asset to the project: Members of the team not only benefited from the availability of data and advances in the modeling framework but also contributed models and data to the project. Knowledge generated by network members has been disseminated at annual conferences, and new ideas have been implemented quickly as the initial data and model lowered the costs of each new extension. In this respect GDyn is no different from other extensions of the GTAP model, although it did benefit substantially from the fact that there was a global database and standard model to start from.

It has been found that in some cases the investment mechanisms in the GDyn model can result in gross investment falling below zero. This will occur when the investment mechanisms cause the actual rate of return to rise considerably, lowering investment to unacceptable levels; for example, if there is a large error in expectations (the expected rate of return far exceeds the actual rate) or the expected and actual rates of return are far below the target rate of return.

In this appendix a complementarity is introduced to ensure that in these cases investment does not fall below a minimum level. We use the method developed by Harrison, Horridge, Pearson and Wittwer (2002) for introducing complementarities. The method is designed specifically for models implemented using the GEMPACK software.

First the equations from the GDyn model are used to demonstrate the negative investment problem in the GDyn model. Following this we introduce the complementarity and show, using the example, how the complementarity works.

Negative Investment

Here we outline an example of the case where investment falls to an unacceptable level. The example is based on a small 7 commodities by 7 region aggregation of the GDyn Data Base.

Introduction

During the 1980s and 1990s, China carried out significant reforms to restructure and open up its economy to foreign trade. These reforms helped spur a period of rapid growth, with annual growth in real per capita GDP averaging 6.04% over the period 1978–95 (Maddison 1998). However, reforms to the legislative framework governing foreign investment in China have proceeded more slowly. Entry into certain sectors, as well as the share of foreign ownership, is significantly limited, and joint ventures typically remain the best option for foreign investors. In an effort to boost foreign investment, the Chinese government began offering a number of special incentives in the early 1990s, including duty drawbacks on imported intermediate inputs and capital goods used for the production of exports, exemptions and reductions in the rate of income taxes paid on profits,1 and preferential tax rates for foreign enterprises that reinvest their profits (China Council 2000). These incentives paid off, with foreign investment increasing sharply in 1992–3 (Fig. 8.1). Indeed, by 1994 China accounted for approximately 20% of all foreign direct investment (FDI) in developing countries (Garbaccio 1995).

However, by 1996 the rate of growth in FDI had begun to slow (Fig. 8.1). A survey of the Chinese economy by The Economist (2000) explored some of the reasons behind the FDI slowdown in China. In many cases investors' high hopes for this market were slow to materialize, with the absence of a rules-based economy making it difficult for outsiders to operate effectively in China.

Introduction

The development of a baseline scenario is an important component of assessing the impact of a policy issue with a dynamic model. A baseline depicts how the world economy might be expected to change, over a given period of time, if the policy were not implemented. The baseline scenario should therefore reflect as closely as possible the changes expected to occur in the world economy, excluding the particular policy of interest.

The components of the baseline will depend on the regional/sectoral aggregation chosen for the study and the policy being examined. A good baseline will include projections for macroeconomic variables – such as real GDP, population, technological change, and primary factor growth rates – for each of the regions being examined, as well as key policies that have already been agreed on or are expected to affect the regions/sectors or the policy scenario being examined. New baselines are often developed each time a new policy issue is addressed. For example, a baseline built to examine China's accession to the WTO will not be suitable for examining the impact of free trade agreements within Southern Africa, most notably because the regional aggregation will differ between the two simulations but also because the policies we would want to include in the baseline would differ considerably.

Introduction

The purpose of this chapter is to introduce the reader to the publicly available software – RunDynam – that is used to carry out the applications presented in Part III of this book. The RunDynam program is based on the GEMPACK suite of software (Harrison and Pearson 1998),which is specifically designed to solve nonlinear general equilibrium models. Other general equilibrium models solved using the GEMPACK software suite include the standard GTAP model and the Monash model of Australia. The RunDynam program has been specially tailored to the needs of the GDyn model and other dynamic models. It offers the user a great deal of flexibility in constructing simulations. It is available from the Centre of Policy Studies at Monash University, Australia.

Using the RunDynam software, you can examine the data, construct and modify simulations, solve simulations, and examine results. Users who wish to alter the underlying theory of the model will need to acquire additional software from the Centre of Policy Studies at Monash University, Australia. In addition, those who wish to make their own aggregations will have to purchase the GTAP Data Base from the Center for Global Trade Analysis, Purdue University. Altering the standard model and the data aggregation process are not discussed in this chapter.