Abstract
The structure of the IT industry has always evolved in line with technological progresses and changes in consumer preferences, as well as with regulatory trends. This is why, when assessing the effect that a new technology or industry policy may have on the national economy, companies and policy-makers need to consider dynamic structural changes affecting the IT industry. One of the most popular existing methods for economic impact analysis is based on a traditional input-output table, and is conducted over a period between the current time and a given time in the future. In this study, we compare the accuracy of RAS and Cross Entropy (CE), the two most widely employed methods for updating input-output (IO) tables, by applying them to Korean IT industries. The main results of this study are the following. In terms of the accuracy of input coefficient estimates, we have found that both the RAS and CE methods have a tendency to overestimate or underestimate them. When the Korean industry was first divided into fourteen sectors, and the RAS and CE methods were applied to each of the fourteen industries, it was difficult to discern a consistent trend for the two methods concerning their accuracy in estimation of input coefficients. Secondly, when used to update an IO table in which the IT industry is subdivided into IT equipment and services, neither the CE nor RAS method proved distinctly superior to the other. Third, in light of the above two findings, we concluded that updating IO tables is best done through a hybrid method combining the CE and RAS methods. This paper proposes a procedure consisting of two steps: IO tables are first updated using the two methods, which are once again updated by employing the OLS average approach through the use of optimal weights.
Highlights
IO tables are an important means of detecting changes affecting the structure of a country’s industry (Acemoglu et al 2011; Atalay et al 2011; Elliott et al 2011; Jones 2011)
Due to the complexity and cost of the data collection process, the Bank of Korea currently issues five-year benchmark tables instead of annual tables, publishing, in some special circumstances where unusual changes occur to the economy, extended versions based on these tables
This study compared the two methods that are most widely employed for predicting future economic effects of an industry or a policy undertaking or trend, using Korea’s 2000 and 2005 IO tables
Summary
IO tables are an important means of detecting changes affecting the structure of a country’s industry (Acemoglu et al 2011; Atalay et al 2011; Elliott et al 2011; Jones 2011). The goal of this study is to contribute to the methodology for updating IO tables by comparing RAS, the most widely used method for this purpose, and Cross Entropy (CE), a comparatively recent method, in order to determine their relative accuracy. This study has both theoretical and practical significance. We first estimated input coefficients based on the 2000 and 2005 transaction tables of domestic goods and services by industry using the two methods These estimates were compared with actual input coefficients for the year 2005. In the final section of the paper, we review the results of the comparative analysis and suggest some implications for applying the mentioned updating method to the IT industry
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