Discussions to establish common rules for digital trade and to enhance cooperation in the digital economy are taking place on various platforms. At the multilateral level, WTO e-commerce negotiations are in progress, and at the bilateral level, e-commerce chapters of regional trade agreements are being revised. South Korea is also expanding its digital trade network by promoting a number of digital trade agreements. Digital trade rules introduced by digital trade agreements are expected to have an economic impact via multiple channels. Digital trade rules have the potential to facilitate digital trade by reducing trade barriers, leading to overall trade expansion. Expanding trade not only boosts production through increased imports and exports, but can also increase productivity through the spillover of new technologies and increased competition. As the digital trade network expands, the need to analyze the economic impact of digital trade agreements also grows. In recognition of these developments, this study quantitatively analyzes the economic effects of digital trade agreements through a general equilibrium model. We first identify the key digital trade rules in digital trade agreements and estimate how much they reduce trade barriers. Then we build a general equilibrium model that includes the characteristics of the digital economy to analyze the macroeconomic impacts of introducing digital trade rules.

This study largely consists of five parts. In Chapter 2, we explore digital trade barriers, such as policy restrictions and technology barriers that can limit digital trade between countries and review the key provisions in digital trade agreements in order to mitigate the barriers. While there are still no explicit rules at the multilateral level such as the WTO, except for a moratorium on customs duties on electronic transmissions, digital trade rules in RTAs have become more comprehensive over time and the level of liberalization is increasing. In addition, Digital Economy Agreements have emerged that contain provisions for cooperation in areas such as SMEs, AI, and fintech.

In Chapter 3, we analyze the impact of digital trade rules on trade costs and trade barriers. In particular, we examine the impact on trade barriers, an exogenous variable, instead of the impact on trade, an endogenous variable. This choice was valid because this study analyzes the impact of digital trade rules through a general equilibrium model in the next chapter. We analyze the impact of digital trade rules on importer trade cost as well as bilateral trade cost because digital trade rules may have non-discriminatory effects on all trading partners through changes in domestic law and institutions. Our analysis shows that provisions such as consumer protection, data flow, and data localization measures have a significant negative impact on trade costs. In particular, provisions about data flow reduce trade costs in most service industries. However, it is possible that effects that would have been observed if the data were more disaggregated by country or industry are estimated to be statistically insignificant. For the sake of consistency with the general equilibrium analysis, this analysis uses ADB MRIO data, which contains only 35 industries in 60 countries/regions. In particular, ADB MRIO mainly contains data in major countries which have multiple agreements, making it difficult to estimate the impact of specific provisions of the digital trade agreement with statistical significance.

In Chapter 4, we build a theoretical model as a framework for analyzing the macroeconomic impact of digital trade rules. Based on Caliendo and Parro (2015) and Antras and Chor (2018), we model multi-country, multi-industry production and trade in the same way as previous literature, but with household decision-making reflecting the characteristics of the data economy. In the model, data is generated from the household's consumption, and as more data is generated, households experience disutility due to concerns about data leakage and abuse. Household decisions are made considering data generation and externalities. Then we simulate the impact of WTO e-commerce negotiation with this model and the estimation results in Chapter 3. The analysis scenarios are as follows: i) a low level agreement that includes only e-commerce facilitation and consumer protection-related provisions; ii) a high level agreement that includes privacy, source code, and data-related provisions as well; and iii) a separate high level agreement between only a few countries, including South Korea, given that the withdrawal of the U.S. proposal has made high-level agreements under the WTO more difficult. If the WTO e-commerce negotiations are concluded at a low level, our results show positive trade effects and welfare effects for the participating countries. On the other hand, non-participating countries lose both exports and imports, reducing their share of world trade. Trade and welfare effects in scenario 2 are greater than those in scenario 1. It is worth noting that non-participating countries also experience minor increases in exports, imports, and welfare. This is likely due to the fact that digital trade rules lower trade costs for all trading partners through improvements in domestic laws and institutions. In the case of a separate agreement between countries that support the adoption of high-level digital trade rules, the difference in economic impact between the participating and non-participating countries is clear, as in scenario 1.

In Chapter 5, we build a growth model of the dynamic data economy and analyze the economic effects on growth from a general equilibrium perspective when domestic data regulations are improved by the introduction of digital trade rules. We consider the impact on companies utilizing data in final goods, intermediate goods, and R&D sectors as well as on consumers due to privacy violations and abuse of data in the long run. The changes in domestic data regulation due to the digital trade rule are assumed to affect stock and accessibility of raw data. Domestic regulatory changes that increase data volumes or improve data accessibility due to the adoption of digital trade rules - coupled with changes in the share of labor in the final goods, intermediate goods, and R&D sectors, as well as changes in the growth rates of industrial and R&D data - will lead to higher economic (and technological) growth through increased data utilization. The model shows that even in the absence of regulatory changes that increase data volumes sufficiently, if the digital trade rule leads to regulatory changes that improve data accessibility, consumer welfare will increase.

In Chapter 6, we explore the application of the methodology proposed above in policy formulation and implementation. The analytical methodology presented in this report is expected to contribute to improving the ex ante and ex post evaluation of digital trade agreements. A wider range of scenarios can be considered when ex ante assessing digital trade agreements using the estimation results in Chapter 3. More rigorous analyses and comprehensive assessments of domestic economy-wide impacts could also be conducted, after negotiations have been concluded. Once it is determined which provisions are included in the agreement, a quantitative analysis can be conducted by considering how much trade cost will be reduced due to each provision. Finally, we also analyze the economic impact of different types of digital trade agreements with different countries, or groups of countries, to identify potential negotiating partners for a digital trade agreement.