Comparison of the Roles of the South Korean and Japanese Electric Power Sectors in Their National Economies

Abstract

The growing demand for electricity, driven by factors such as the shift to carbon neutrality and economic growth, is a challenge shared by South Korea and Japan. South Korea, a peninsula nation, and Japan, an island country, which are both heavily dependent on foreign energy sources and have manufacturing-based industrial structures, are actively working to secure stable power supplies for their economic development. This article carries out a quantitative analysis of the roles of the South Korean and Japanese electric power sectors (EPSs) in their respective economies, seeking to identify differences and generate actionable insights for decision making and policy formulation. Utilizing the input–output (IO) technique with the latest available data, the analysis includes a demand-side model, a supply-side model, and a price-side model to examine various effects of the EPSs. The key findings reveal differences in the production-inducing, value-added creation, and job-creation effects between the two countries, highlighting operational disparities in their electricity sectors. Additionally, South Korea exhibits higher wage-inducing, supply shortage, and price-side effects than Japan, because of its public enterprise-oriented high-wage structure and a substantial manufacturing sector. These quantitative results provide valuable reference material for future government decisions and policy development in the EPS and emphasize the significant role and impact of the power sector in both countries.

1. Introduction

Electricity is one of the energy sources used by humans. Although electricity is not easily stored, it is quite convenient to use. It is not only an essential input into industrial production but also an indispensable partner in human life [1,2]. According to the results from a number of studies, electricity consumption has increased in tandem with economic growth [3,4,5,6]. Electric power consumption has the potential to stimulate industrial production and economic activity. Simultaneously, economic growth fosters surges in electricity usage [6].

In the future, electricity usage is expected to increase further because of two aspects. First, as the COVID-19 pandemic transitions into the endemic phase, human activities are increasing, leading to a rise in electricity consumption worldwide, especially in developing countries [7]. Second, many countries around the world have declared their commitment to carbon neutrality, and electrification is a prominent means of achieving this commitment. Unlike other fossil-fuel energy sources, electricity does not emit greenhouse gases (GHG) during the consumption process [8]. Although GHGs are emitted during the production of electricity, these emissions can be suppressed by using renewable energy (RE), nuclear power, hydrogen, etc., or by using means such as carbon capture and storage.

Ultimately, because of the increased demand for electricity, the importance of the power sector that produces and supplies electricity will become even greater. Meanwhile, the method of generating electricity will change towards utilizing low-carbon energy instead of using high-carbon energy. In addition, ancillary service markets, such as battery storage and pumped hydro, as well as the development and application of sector-coupling technologies like power to gas, will be expanded. Therefore, the electric power sector (EPS) will not only supply electricity but will also become a vital industry for countries, experiencing significant growth beyond its current state [9].

Furthermore, the Russia–Ukraine war that erupted in February 2022 disrupted the global energy supply chain. As the regional conflict between the two countries expanded to a global conflict to secure limited energy, energy supply and demand stabilization or energy security emerged as an important task along with the implementation of carbon neutrality. Countries around the world are now faced with the challenge of overcoming the energy supply network crisis and achieving energy security while participating in the global trend toward carbon neutrality. Efforts are being made to ensure a stable supply of diverse power sources and to restructure the EPS so that there is no disruption to the electricity supply [10,11,12].

The EPS has a crucial role to play in achieving the two goals of reducing GHG emissions and enhancing energy security. In addition, the electric power industry will undergo extensive changes in the future. As national policy on the EPS becomes more important, various types of decisions will need to be made. The important information required at this time is quantitative knowledge about the role and economic effects of the EPS on each sector as well as the national economy. We need to quantitatively and objectively examine the various economic effects of the EPS on the overall economy. This article aims to derive this information [13,14].

There are three main types of roles and economic effects of the EPS in the national economy covered in this study. The first is the amount of production, value-added, and the wages and number of employees that an investment or production in the EPS causes in other sectors. The second is the production disruption in other sectors caused by a supply shortage in the EPS. The third is the price increase in other sectors caused by a price increase in the EPS. The initial aim of this research was to look into the role of the EPS in the South Korean economy. However, the implications of such an investigation would be limited. Therefore, countries with similar electricity supply and demand conditions to those of South Korea were considered as comparison targets. Japan was chosen as the comparison country in this study. Japan is geographically adjacent to South Korea. Various implications can be derived from comparing the economic effects of South Korea’s EPS and those of Japan’s EPS.

There are four reasons why Japan was selected to compare with South Korea in the analysis of the economic effects of the EPS. First, the two countries have similarities as representative electricity islands located in East Asia. Neither country has a power grid connected to neighboring countries. South Korea is on the Korean Peninsula, but there are military tensions between it and North Korea, and Japan is an island country. Second, since South Korea and Japan have few energy sources themselves, they have to import from abroad most of the energy they consume. Third, since the two countries have a manufacturing-oriented industrial structure that consumes electricity intensively, and an export-led economic system, the stable supply of industrial power for 24 h every day is a very important factor in their survival. Fourth, the two countries both use nuclear power as an important means of generating electricity. In addition, they have national plans to increase the utilization of nuclear power plants in the future [15,16,17].

The most important purpose of this research is to delve, using quantitative methods, into the role of the EPS in the South Korean and Japanese national economies. To this end, the input–output (IO) technique, which has been widely adopted in the analysis of energy-policy issues, will be utilized. The IO technique is a research methodology that is applied to obtain the economic effects of a specific industry. Specifically, it is an analysis method that quantitatively grasps the interrelationships between industries through production activities. As is well known, Wassily Leontief, the Nobel laureate in economics in 1993, devised the IO technique. Three models, the demand-side, the supply-side, and the price-side models, will be applied.

This paper contributes to the literature in four aspects. First, in analyzing the economic effects of the South Korean and Japanese EPSs, a framework for applying the three models is presented and used empirically. Moreover, since an approach that treats the EPS as exogenous rather than endogenous is applied, the discussions can be focused on the EPS.

Second, the implications obtained from the comparison between South Korea and Japan enable the authors to present to policy officials the way in which the role of the South Korean EPS can be enhanced. This is the first such attempt in the literature. One could consider the external validity of directly applying the comparison to other electricity island economies. However, this is not feasible because the structure of power sources, the climate, the weather, industrial structures, power consumption patterns, and so on, are very different for each country.

Third, to the best of the authors’ knowledge, as a result of reviewing recent works that applied the IO technique to the energy sectors of South Korea and Japan, nothing similar to this work exists in the literature. For example, for South Korea, Kim et al. [18], Lee and Kim [19], and Lee et al. [20] used the IO technique to analyze the economic effects of the mining, forest, and renewable energy sectors, respectively. Kim and Yoo [21] adopted the IO technique to compare the economic effects of nuclear power generation and renewable energy generation. For Japan, Matsumoto and Matsumura [22] and Yagi et al. [23] addressed the economic effects of the renewable energy sector and earthquakes, respectively, employing the IO technique.

Fourth, the collection and examination of previous studies applying the IO technique and carrying out a comparative analysis between countries shows that the national economic role of EPS, which will play the most important role in the energy sector not only now but also in the future, has rarely been compared between countries. It is quite difficult to find any earlier pieces of research similar to this study. This suggests that this study may have novelty.

Of course, research dealing with other sectors can be found in the literature. For example, Ali et al. [24], Bon and Pietroforte [25], and Ilhan and Yaman [26] applied the IO techniques to the construction sector and derived implications by comparing the results of the analysis for several countries. De Souza et al. [27], Hasanli Salihova [28], and Mun et al. [29] used the IO technique to compare, respectively, the roles of the service sector, the tourism sector, and the software and healthcare sectors across countries. Fotia and Teclean [30], Gorska [31], and Thangavelu et al. [32] adopted the IO technique to analyze the efficiency of innovation, forward and backward linkage effects, and the economic effect of servicification in global value chains and conducted cross-country comparisons. Proops et al. [33], Li et al. [34], and Long [35] attempted cross-country comparisons of carbon dioxide-related issues within the IO framework.

All the works discussed above have something in common with this study, in that the IO technique was applied. They are also connected to this study in that they compare the results of the analysis between different countries. However, they can be differentiated because the topics of interest being analyzed in each study are different. The remainder of this paper contains four sections: Section 2 introduces the IO technique; Section 3 explains the data and results; Section 4 discusses the results; and Section 5 offers conclusions.

2. Materials and Methods

2.1. IO Technique as A Method

As noted above, this study employs the IO technique. An IO table is essential for the application of the technique. The IO table contains all transactions occurring in the process of producing and disposing of goods and services within an economy over one year in accordance with certain principles and formats [36]. The IO technique has two main advantages [37]. First, it can quantitatively produce information on the correlation between industries by utilizing an IO table that expresses input and output between sectors in a matrix structure. Second, the IO technique enables us to delve into the economic effects of one specific sector on other sectors by adopting exogenous specification techniques.

In particular, for the supply of a specific type of energy, the output from various sectors needs to be inputted into the energy sector, and the energy supplied is an essential input factor in industrial production. Therefore, it is necessary to analyze the role of energy not only from the backward perspective but also from the forward perspective. In this case, the IO technique can be quite useful. In fact, there are numerous pieces of research in the literature in which the IO technique has been applied to energy-related issues.

Table 1. Summary of some selected research that studied energy-related issues adopting input–output (IO) technique.

Sources	Countries	Objects to Be Investigated	Models
Hienuki [38]	Japan	Naphtha reforming hydrogen energy	Demand-side model
Ju et al. [39]	South Korea	Electricity	Value-added maximization model
Lim and Yoo [40]	South Korea	Electricity	Price-side model
Lim et al. [41]	South Korea	Coal, petroleum, natural gas	Structural decomposition analysis model
Logar and Van Den Bergh [42]	Spain	Oil	Price-side model
Önder [43]	Turkey	Renewable energy	Demand-side model
O’Sullivan and Edler [44]	Germany	Renewable energy	Demand-side model
Robison and Duffy-Deno [45]	United States	Oil and gas	Multiregional IO model
Siala et al. [46]	Europe	Energy-related CO2 emissions	Multiregional IO model
Sun et al. [47]	China	Coal, oil, natural gas, electricity	Supply-side model
Wang and Ge [48]	China	Coal	Multiregional IO model
Karkacier and Goktolga [49]	Turkey	Energy use in agriculture	Demand-side model

provides a summary of some of these. From this table, it can be seen that various studies have been conducted on various energy sources in different countries.

From Table 1, three distinctions between the previous studies and this study can be identified. First, our approach involves a comprehensive application of three models, providing richer insights through their synthesis. Second, unlike studies focusing on a single country, we conduct a comparative analysis of two countries, South Korea and Japan, ensuring meaningful insights due to their similar electricity supply conditions. Third, unlike some previous studies, we employ the exogenous specification method, treating the EPS as an exogenous sector and effectively deriving various economic effects.

The IO technique has not changed basic theory, but various application models have been developed so that it can be applied to a variety of fields. There are good introductions to these models by Casler and Wilbur [50], Leontief [51,52], Fletcher [53], Rose and Miernyk [54], Lahr and Dietzenbacher [55], Ten Raa [56], and Miller and Blair [57].

This article aims to draw implications after analyzing the national economic roles and economic effects of the EPSs in South Korea and Japan by synthesizing the models developed in various previous studies. Therefore, this analysis is different from a meta-analysis, which estimates a single equation by synthesizing the main results of various previous studies. Specifically, the procedure for applying the IO techniques used in this study consists of data, sector classification, theory and model, and derivation of results. Figure 1 presents a flowchart summarizing the entire process followed in this study.

The models applied in this study include a demand-side model, a supply-side model, and a price-side model. The methods and models adopted in this article are not newly developed or significantly modified by the authors. Therefore, they are not very novel in the literature. However, the significance of this study is that it provides a framework that systematically integrates the various models proposed in previous studies to analyze the national economic role of the EPSs and their various economic effects within a single setting.

2.2. Demand-Side Model

Let $X_i$ be the total output of sector $i$, $X_j$ be the total input of sector $j$, $Y_i$ be the final demand for sector $i$, and $z_{ij}$ be the intermediate input from sector $i$ to sector $j$. Usually, the input coefficient, $a_{ij}$, is defined as $z_{ij}/X_j$. $a_{ij}$ refers to the intermediate input from sector $i$ to sector $j$ as a proportion of the total input of sector $j$. Thus, the input coefficient represents a kind of technical characteristic and is called the technical coefficient. It is assumed that there are a total of $n$ sectors in the economy. Let $X$ be an $n\times 1$ matrix whose elements are $X_i$, $Y$ be an $n\times 1$ matrix whose elements are $Y_i$, $I$ be an $n$^th order identity matrix, and A be $n\times n$ matrix composed of $a_{ij}$. A well-known equation in the IO technique can then be derived as:

$$X={(I-A)}^{-1}Y$$

(1)

${(I-A)}^{-1}$ in Equation (1) is usually called the input inverse matrix. Let the elements of ${(I-A)}^{-1}$ be ${\alpha }_{ij}$; then, ${\alpha }_{ij}=\partial X_i/{\partial Y}_j$ indicates the amount by which $X_i$ should increase/decrease with a one unit increase/decrease of $Y_j$ [52]. Equation (1) represents a demand-side model. Usually, instead of Equation (1), a variability model such as the following equation is applied [57,58].

$$∆X={(I-A)}^{-1}∆Y$$

(2)

To examine the economic effects of a change in the total output of the EPS on other sectors rather than a change in final demand for the EPS, an exogenous specification is additionally required so that the EPS included in the endogenous sector is in the exogenous sector. When the EPS is treated as an exogenous sector, various economic effects centered around the EPS become easy to obtain. Let the EPS be sector $K$. After manipulating Equation (2) for the exogenous specification of the EPS, and assuming the absence of change in final demand, we can obtain the following equation [47].

$$∆X_e={(I_e-A_e)}^{-1}(A_K^e∆X_K)$$

(3)

where $∆X_e$ is the matrix remaining except for the row corresponding to sector $K$ in $X$, $I_e$ is an $(n-1)$th order identity matrix, $A_e$ is the $(n-1)\times (n-1)$ matrix with the column and row associated with sector $K$ removed from $A$, $A_K^e$ is an $(n-1)\times 1$ matrix in which one row, corresponding to sector $K$, is taken from $A$ and then $K$^th element is eliminated, and $∆X_K$ means the amount of change in total output in sector $K$. Therefore, ${(I_e-A_e)}^{-1}{A}_K^e$, an $(n-1)\times 1$ matrix, in Equation (3) implies the amount by which one dollar of investment or production in the EPS triggers production in other sectors.

Let $a_j^V$, the value-added coefficient of sector $j$, be defined as $V_j/X_j$. This refers to the proportion of the value added of sector $j$ to the total input of sector $j$. Let $A^V$ be an $n\times 1$ value-added coefficient matrix comprising $a_j^V$. The effects of one dollar of investment or production in the EPS on the value added of other sectors are formulated from Equation (3). To this end, an $(n-1)\times 1$ value-added matrix, $V_e$, and a $1\times (n-1)$ value-added coefficient matrix, $A_e^V$, can be introduced. $∆V_e$ indicates the amount by which the value-added matrix, $V_e$, changes.

$$∆V_e={\widehat{A_e^V}(I_e-A_e)}^{-1}(A_K^e∆X_K)$$

(4)

where $\widehat{A_e^V}$ is a diagonal matrix of $A_e^V$, and its dimension is $(n-1)\times (n-1)$.

Thus, ${\widehat{A_e^V}(I_e-A_e)}^{-1}{A}_K^e$, an $(n-1)\times 1$ matrix, indicates the amount that one dollar of investment or production in the EPS creates in the value added of other sectors. The amount of value added is found by comparing the right-hand side (RHS) of Equation (3) with the RHS of Equation (4), where the latter is the former multiplied by $\widehat{A_e^V}$.

The effects of one dollar of investment or production in the EPS on inducing the wages of other sectors also come from Equation (3). For this purpose, an $(n-1)\times 1$ wage matrix, $W_e$, and an $1\times (n-1)$ wage coefficient matrix, $A_e^W$, can be introduced. The elements of $W_e$ are the wages of all sectors except for sector $K$. The $j$th element in $A_e^W$ is defined as $W_j/X_j$ representing the ratio of sector $j$’s wage to the total input of sector $j$. Let $∆W_e$ be the changes in the wage of other sectors [50].

$$∆W_e={\widehat{A_e^W}(I_e-A_e)}^{-1}(A_K^e∆X_K)$$

(5)

where $\widehat{A_e^W}$ is a diagonal matrix of $A_e^W$, and its magnitude is $(n-1)\times (n-1)$.

Consequently, ${\widehat{A_e^W}(I_e-A_e)}^{-1}{A}_K^e$, an $(n-1)\times 1$ matrix, indicates the amount by which one dollar of investment or production in the EPS affects the wages of other sectors. Comparing the RHS of Equation (3) with the RHS of Equation (5), the latter is the former multiplied by $\widehat{A_e^W}$. The effects of one dollar of investment or production in the EPS on the wages of other sectors are computed using Equation (5).

The effects of USD 1.0 million of investment or production in the EPS on creating jobs in other sectors can also inferred from Equation (3). For this purpose, a $1\times (n-1)$ employment matrix, $N_e$, and an $1\times (n-1)$ employment coefficient matrix, $A_e^N$, are introduced. The elements of $N_e$ are the number of employees in the sectors, except for sector $K$. The $j$th element in $A_e^N$ is defined as $N_j/X_j$, which is the ratio of the number of employees in sector $j$ to the total input of sector $j$. Let $∆N_e$ be the changes in the number of employees of other sectors.

$$∆N_e={\widehat{A_e^N}(I_e-A_e)}^{-1}(A_K^e∆X_K)$$

(6)

where $\widehat{A_e^N}$ is a diagonal matrix of $A_e^N$, and its dimension is $(n-1)\times (n-1)$.

As a result, ${\widehat{A_e^N}(I_e-A_e)}^{-1}{A}_K^e$, an $(n-1)\times 1$ matrix, indicates the number of employees of other sectors that are added by a USD 1.0 million investment or production in the EPS. Comparing the RHS of Equation (3) with the RHS of Equation (6), the latter is the former multiplied by $\widehat{A_e^N}$. The effects of USD 1.0 million investment or production in the EPS on the triggering of jobs in other sectors are calculated by adopting Equation (6).

2.3. Supply-Side Model

As described above, the demand-side model reflects the view that the EPS demands the output of other sectors. This model is appropriate for analyzing the backward economic effects of the EPS, as it notes that the output from other sectors is supplied to the EPS. However, the model does not consider that electricity is used as an essential input for various sectors. An alternative to the demand-side model is, therefore, required. In response, Ghosh [59] proposed a supply-side model. The usefulness of this model has been discussed in some of the literature [60,61,62,63].

The approach that one model is right and the other wrong is absolutely inappropriate. One of the two models can be appropriately selected and applied, taking into account the objective of the study. This subsection seeks to introduce the supply-side model, which can obtain the supply-shortage effect of the EPS. In particular, since power supply can be disrupted by various causes, such as drought, flood, and earthquake, the power authorities need information about the effects of an electricity supply shortage on other sectors’ production. In addition, the model is known to be quite useful in calculating the supply-shortage effect [64,65]. Let the output coefficient, $r_{ij}$, be defined as $z_{ij}/X_i$ and $R$ be an $n\times n$ matrix composed of $r_{ij}$. The supply-side model can be expressed as:

$$X\prime ={V\prime (I-R)}^{-1}$$

(7)

where $X\prime$ and $V\prime$ indicate the transpose matrix of $X$ and $V$.

${(I-R)}^{-1}$ in the RHS of Equation (7) becomes the output inverse matrix. If the element of this matrix are ${\beta }_{ij}$, ${\beta }_{ij}$ is defined as $\partial X_i/{\partial V}_j$. The element of ${(I-R)}^{-1}$ means the amount by which $X_i$ increases/decreases when there are one dollar increases/decreases in $V_j$. Therefore, ${(I-R)}^{-1}$ may be referred to as the supply-shortage coefficient matrix. As before, Equation (7) can be rewritten as a variability model.

$$∆X\prime ={∆V\prime (I-R)}^{-1}$$

(8)

To analyze the economic impacts on other sectors of a change in the output of the EPS, instead of a change in the value added of the EPS. Exogenous specification of making the EPS included in the endogenous sector into the exogenous sector is needed. When the EPS is handled as an exogenous sector, the supply-shortage effects of the EPS are easily obtained. After assuming that there is no change in value added, the model in which the EPS is exogenous is derived as follows.

$$∆X_e^{\prime }={∆X_K{R}_K^{\prime }(I_e-R_e)}^{-1}$$

(9)

where $∆X_e^{\prime }$ is the matrix remaining except for the column corresponding to sector $K$ in $X\prime$, $R_e$ is an $(n-1)\times (n-1)$ matrix with the column and row associated with sector $K$ is removed from $R$, $R_K^{\prime }$ is an $1\times (n-1)$ matrix in which only column corresponding to sector $K$ is taken from $R$ and then $K$th element is eliminated, and $∆X_K$ means the amount of change in the total output in sector $K$.

Therefore, ${R_K^{\prime }(I_e-R_e)}^{-1}$ implies a decrease in the production of the other sectors when the supply of one dollar of output of the EPS to the other sectors is hindered. Its dimension is $1\times \left(n-1\right).$ The supply-shortage effects of one dollar of output of the EPS on other sectors are computed using Equation (9).

2.4. Price-Side Model

The supply-side model, as well as the demand-side model described above, deal with the effects of a change in the monetary unit output of the EPS. As a result, an IO table in monetary units has been used so far. However, the original IO technique started with an IO table in physical units. The description of the price-side model basically begins with an IO table in physical units [39]. Let $Q_i$ and $Q_j$ be the total output of sector $i$ and total input of sector $j$ in the physical unit, respectively, and $s_{ij}$ be the intermediate input from sector $i$ to sector $j$ in the physical units. The input coefficient for the physical unit, $d_{ij}$, is defined as $s_{ij}/Q_j$. An $n\times n$ matrix composed of $d_{ij}$ may be referred to as D. In addition, let $U_i$ be the physical unit value added of sector $i$, $P_i$ be the price for $Q_i$, $P_i^U$ be the price for $U_i$, and $d_i^U$ be the physical unit value-added coefficient of sector $i$. $P$, $P^U$, and $D^U$ can be defined as the ($n\times 1)$ matrices consisting of $P_i$, $P_i^U$, and $d_i^U$, respectively. Then, the basic equation representing the price-side model is derived as:

$$P={(I-D\prime )}^{-1}\widehat{D^U}{P}^U$$

(10)

where $\widehat{D^U}$ is the diagonal matrix of $D^U$ and its dimension $n\times n$.

If the prices per unit of total output, value added, and intermediate input are all normalized to 1, Equation (10) can be rewritten as follows.

$$\overline{P}={(I-A\prime )}^{-1}\widehat{A^U}\overline{P^U}=l$$

(11)

where $\widehat{A^U}$ is the matrix diagonalizing the monetary unit value-added coefficient matrix, and $l$ is a column vector filled with 1. $\overline{P}$ and $\overline{P^U}$ mean the results from normalizing $P$ and $P^U$, respectively.

Interestingly, although we started from an IO table in monetary units, Equation (11) consists of matrices in physical units. In fact, a physical unit IO table does not exist in the real world. This is because the units of output in each sector are different. Moreover, the South Korean and Japanese governments do not provide physical unit IO tables. Therefore, even if the explanation of the price-side model starts with the IO table in monetary units, it inevitably results in the use of the IO table in physical units in the final stage. Equation (11) can be re-expressed in the following variability model.

$$∆\overline{P}={(I-A\prime )}^{-1}\widehat{A^U}∆\overline{P^U}$$

(12)

By using Equation (12), the price effect caused by a change in $P^U$ in each sector is obtained even if $P^U$ is not known. For example, the effect on each sector of wage increases in a specific sector can be calculated from Equation (12). However, since Equation (12) refers to the amount by which a 1% increase in the price for value added changes the output price of each sector, its utilization is limited. This is because our main concern is not the effect of price changes in value added, but the effect of a change in the output price of the EPS. Let $A_e^{\prime }$ be a matrix in which the column and row related to sector $K$ are removed from $A\prime$. Its dimension is $(n-1)\times (n-1)$. When no change in $P^U$ is assumed and the EPS is specified as exogenous in Equation (12), the following equation is derived.

$$∆\overline{P_e}={(I_e-A_e^{\prime })}^{-1}{A}_{Ke}^{\prime }∆\overline{P_K}$$

(13)

where $∆\overline{P_e}$ is an $(n-1)\times 1$ matrix in which a value corresponding to sector $K$ is removed, $A_{Ke}^{\prime }$ is an $(n-1)\times 1$ matrix where the element corresponding to sector $K$ is eliminated from the $K$-th column vector of $A\prime$, and $∆\overline{P_K}$ is the percentage change in output price of sector $K$.

Using Equation (13), we can find the amount by which a 1% increase in the output price of the EPS raises the price for the output from other sectors. One thing to note is that the economic effects of one monetary unit of investment or production in the EPS on other sectors can be derived from Equations (3) and (9), while the amounts by which a 1% increase in output price of the EPS affects the price levels of other sectors are obtained from Equation (13).

3. Data and Results

3.1. Reconstruction of the IO Table for the Comparative Analysis

IO tables should be used for applying the IO technique. IO tables for a particular country are usually prepared and published by the country’s government agencies. The South Korean and Japanese IO tables come from the Bank of Korea and the Ministry of Internal Affairs and Communications, respectively [66,67]. This study uses the latest IO table published by these two institutions and employs the domestic IO table that removes imports. The reason is that this research aims to delve into the economic effects of EPS on the domestic national economy. The target years of the South Korean and Japanese IO tables adopted for this research are 2019 and 2015, respectively.

Although the years for the two IO tables are different, these two IO tables are used in this study [66,67]. These two IO tables are the latest to be issued. When comparing the results for the two countries, the difference of about four years is not a problem in terms of the stability of the input coefficient. The coefficient of input itself tends to remain relatively unchanged, unlike values such as total output, intermediate demand, and final demand [57]. In addition, the IO technique uses an input inverse matrix and not an input coefficient matrix, and an input inverse matrix is the more stable of the two [37]. An inverse matrix of output is also known to be stable against time changes. While the South Korean IO table adopts a 165-sector classification method or a 33-sector classification method, the Japanese IO table adopts a 187-sector classification method or a 37-sector classification method. Thus, in order to deal with the IO tables of the two countries, one appropriate sector classification method must be selected first and then applied consistently. For convenience, this study adopted the 33-sector classification method.

Since IO results of the analysis may vary slightly depending on how the sector is classified, the sector classification method should not be selected arbitrarily. In this regard, and in order to avoid unnecessary controversy related to determining the sector classification method, this study uses the sector classification method of the Bank of Korea, which issues South Korea’s IO table. Determining the sector classification method through robustness checks was avoided because it would entail too much work and would not be effective. In addition, among the Bank of Korea’s three sector classification methods, the 33-sector classification method is appropriate for showing the results of the analysis. The number of sectors used in the other two sector classification methods is greater than 33. Thus, this study adopted the 33-sector classification method. Japan’s IO table was adjusted to match the 33-sector classification method. Since, of course, the South Korean sector classification method is different from the Japanese one, there may be differences between the results of the analysis based on the former and those based on the latter. However, judging from the authors’ experience, the difference is quite small. Therefore, to save space, this study does not necessarily compare the two results. The 33-sector classification that was finally chosen is reported in

Table 2. Sector classification for this research.

Number of Sectors	Name of Sectors
1.	Agricultural, forest, and fishery goods
2.	Mined and quarried goods
3.	Food, beverages and tobacco products
4.	Textile and leather products
5.	Wood, paper products, printing and reproduction of recorded media
6.	Petroleum and coal products
7.	Chemical products
8.	Non-metallic mineral products
9.	Basic metal products
10.	Fabricated metal products, except machinery and furniture
11.	Computing machinery, electronic equipment and optical instruments
12.	Electrical equipment
13.	Machinery and equipment
14.	Transport equipment, manufacturing services, and repair services of industrial equipment
15.	Other manufactured products
16.	Gas and steam supply
17.	Water supply, sewage, waste treatment, and disposal services
18.	Construction
19.	Wholesale, retail trade, and commodity brokerage services
20.	Transportation
21.	Food services and accommodation
22.	Communications and broadcasting
23.	Finance and insurance
24.	Real estate services
25.	Professional, scientific, and technical services
26.	Business support services
27.	Public administration, defense, and social security services
28.	Education services
29.	Health and social care services
30.	Art, sports, and leisure services
31.	Other services
32.	Others
33.	Electric power

.

Typically, each country releases a single IO table, and such data generally do not necessitate statistical analysis. Therefore, the size of the sample is not defined for the IO table. Additionally, analysis using IO tables is deterministic. Regardless of who performs the IO analysis, deterministic results are obtained. Of course, if an analysis is conducted by dynamically linking multiple IO tables over several decades, a statistical approach may be applied. However, this study analyzes the IO tables for specific years for two countries and compares the results between the two countries, making any form of statistical approach unfeasible.

3.2. Comparison of the Role of South Korean and Japanese EPSs in the National Economy

This subsection compares the role of the South Korean and Japanese EPSs in their national economies. Regarding the comparison, this paper adopts four economic indicators: total output, value added, wage, and employment.

Table 3. Role of South Korean and Japanese electric power sectors in the national economy.

	South Korea			Japan
	Electric Power Sector (A)	National Economy (B)	Share of Electric Power Sector (A/B)	Electric Power Sector (A)	National Economy (B)	Share of Electric Power Sector (A/B)
Total output	KRW 63.1 trillion (USD 73.5 billion)	KRW 4365.9 trillion (USD 5087.9 billion)	1.4%	JPY 20.3 trillion (USD 24.6 billion)	JPY 1017.8 trillion (USD 1234.2 billion)	2.0%
Value added	KRW 19.2 trillion (USD 22.4 billion)	KRW 1900.7 trillion (USD 2215.5 billion)	1.0%	JPY 7.4 trillion (USD 9.0 billion)	JPY 548.2 trillion (USD 664.7 billion)	1.4%
Wage	KRW 5.3 trillion (USD 6.2 billion)	KRW 913.4 trillion (USD 1064.8 billion)	0.6%	JPY 0.1 trillion (USD 0.1 billion)	JPY 4.7 trillion (USD 5.7 billion)	1.5%
Employment	42.2 thousand persons	24.6 million persons	0.2%	0.2 million persons	68.6 million persons	0.3%

Note: The values for South Korea and Japan are for 2019 and 2015, respectively. The unit is KRW 1000 (USD 0.857) as of 2019. The unit is JPY 100 (USD 0.825) as of 2015 [68].

shows the results of comparing the four indicators for the EPS and the national economy in South Korea and Japan. Interestingly, the values for South Korea are consistently smaller than those for Japan. In other words, since Japan has a larger economy and a larger population than South Korea, the absolute size of the EPS is larger in Japan than in South Korea. In addition, the relative proportion of the EPS is larger in Japan than in South Korea.

The total output of the South Korean EPS accounts for 1.4% of the economy, compared to 2.0% for the Japanese EPS. The former is smaller than the latter. In other words, the role of the EPS in South Korea is smaller than its role in Japan. This is because South Korea’s electricity prices have themselves been set low, and are tightly controlled by the government, making the scale of total output itself low. The proportions of value added of the EPS are 1.0% and 1.4% for South Korea and Japan, respectively. The proportion is lower than that of the total output of EPS. The EPS’ wage shares are 0.6% and 1.5% for South Korea and Japan, respectively. The latter is 2.5 times the former. In other words, the difference in the share of wages is larger than the difference in the share of total output or the share of value added.

The employment shares of EPS are 0.2% and 0.3% for South Korea and Japan, respectively. In both South Korea and Japan, the proportion of value added, wage, and employment are all smaller than the proportion of total output. In particular, the share of employment is only one-seventh of the share of total output. This suggests that the EPS creates less value added, wages, and employment than other sectors. This is because the EPS itself plays a greater role in supplying electricity to each sector than in creating value added, wages, and employment.

3.3. Production-Inducing Effects of the EPS

The results of analyzing the effects of one dollar of investment or production in the South Korean and Japanese EPSs on the production of other sectors are presented in the second column of

Table 4. Production-inducing effects, value-added creation effects, and wage-inducing effects of one dollar of investment or production in the South Korean and Japanese electric power sectors (EPSs).

Sectors a	Production-Inducing Effects				Value-Added Creation Effects				Wage-Inducing Effects
	South Korea		Japan		South Korea		Japan		South Korea		Japan
	Value	Rank	Value	Rank	Value	Rank	Value	Rank	Value	Rank	Value	Rank
1.	0.00246	25	0.00044	27	0.00126	23	0.00017	28	0.00026	29	0.00000	29
2.	0.00276	24	0.31966	1	0.00130	22	0.00667	10	0.00056	23	0.00151	6
3.	0.00564	19	0.00023	29	0.00144	21	0.00007	30	0.00050	25	0.00000	30
4.	0.00455	21	0.00129	21	0.00093	28	0.00020	26	0.00041	27	0.00001	24
5.	0.00560	20	0.01174	11	0.00180	20	0.00416	12	0.00083	18	0.00011	11
6.	0.05155	3	0.06455	3	0.01293	7	0.01621	5	0.00051	24	0.00039	7
7.	0.05441	2	0.00740	13	0.01486	5	0.00211	13	0.00493	6	0.00007	12
8.	0.00065	32	0.00123	22	0.00020	31	0.00053	22	0.00008	31	0.00003	18
9.	0.01331	14	0.00468	16	0.00250	17	0.00107	17	0.00092	17	0.00004	15
10.	0.02109	9	0.00283	17	0.00750	10	0.00115	15	0.00358	8	0.00002	21
11.	0.02043	10	0.00184	20	0.00823	9	0.00044	23	0.00205	14	0.00001	23
12.	0.03842	5	0.00100	24	0.01093	8	0.00028	24	0.00437	7	0.00001	26
13.	0.00798	18	0.00266	18	0.00246	18	0.00102	18	0.00124	15	0.00001	25
14.	0.01636	11	0.00512	14	0.00460	14	0.00115	16	0.00244	13	0.00002	20
15.	0.00098	30	0.00091	25	0.00028	30	0.00023	25	0.00016	30	0.00001	28
16.	0.18222	1	0.00209	19	0.03879	1	0.00067	21	0.00650	5	0.00003	19
17.	0.00424	22	0.02223	9	0.00236	19	0.01243	8	0.00111	16	0.00028	8
18.	0.00865	17	0.01386	10	0.00382	16	0.00650	11	0.00272	10	0.00004	14
19.	0.02439	7	0.02506	7	0.01299	6	0.01748	4	0.00690	4	0.00001	27
20.	0.01513	12	0.05398	4	0.00550	13	0.02610	2	0.00321	9	0.03539	1
21.	0.01338	13	0.00000	31	0.00458	15	0.00000	31	0.00270	11	0.00000	31
22.	0.01165	15	0.02653	6	0.00654	12	0.01309	7	0.00259	12	0.01495	2
23.	0.02872	6	0.02485	8	0.01691	3	0.01615	6	0.00692	3	0.00003	16
24.	0.00966	16	0.00940	12	0.00709	11	0.00790	9	0.00067	21	0.00001	22
25.	0.04572	4	0.00000	32	0.02297	2	0.00000	32	0.01575	1	0.00000	32
26.	0.02403	8	0.06779	2	0.01626	4	0.04196	1	0.00937	2	0.01194	4
27.	0.00129	29	0.00122	23	0.00098	26	0.00087	19	0.00062	22	0.00016	9
28.	0.00066	31	0.00083	26	0.00047	29	0.00067	20	0.00040	28	0.00016	10
29.	0.00179	28	0.00013	30	0.00095	27	0.00008	29	0.00069	20	0.00003	17
30.	0.00194	27	0.00026	28	0.00107	25	0.00018	27	0.00042	26	0.00007	13
31.	0.00277	23	0.03593	5	0.00125	24	0.01988	3	0.00082	19	0.01418	3
32.	0.00206	26	0.00502	15	0.00000	32	0.00204	14	0.00000	32	0.00516	5
Sum (A)	0.62449		0.71478		0.21376		0.20146		0.08422		0.08468
Effect on the electric power sector (B)	1.00000		1.00000		0.30422		0.36567		0.08380		0.00347
Total (A + B)	1.62449		1.71478		0.51798		0.56713		0.16802		0.08815

^a The sectors are explained in Table 2.

. This contains values for each sector and their rankings. The total production-inducing effect, which implies the amount by which one dollar of investment or production in the South Korean and Japanese EPSs causes production to rise in the national economy, was analyzed as 1.62449 or 1.71478, respectively. The total production-inducing effects of one dollar of investment or production in the South Korean and Japanese EPSs are shown in Figure 2.

The figure for Japan is slightly larger than the figure for South Korea. However, since IO analysis is a deterministic approach and not a statistical approach, it is unfortunately not possible to test statistically whether the figure for Japan is larger than that for South Korea. South Korea simply imports fuels such as oil, coal, and natural gas (NG) for power generation, rather than directly exploring and producing them from abroad, while Japan directly explores, produces, and then imports some of them from abroad. Since the production-inducing effect is basically an effect on the domestic economy, it would be natural for the direct development and introduction of fuels for power generation to have more economic effects than just importing them, in terms of the backward linkage. Looking at each sector, the results appear to be somewhat different across the two countries. In South Korea, the production-inducing effects of sector 16 (gas and steam supply), sector 7 (chemical products), and sector 6 (petroleum and coal products) are ranked first, second, and third, respectively. Since the percentages of coal- and NG-fired power generation reach about 40% and 30%, respectively, it seems that the production-inducing effects for sectors 16 and 6 are large. Furthermore, the production-inducing effect for sector 7 is also significant because a large amount of chemical products are required for denitrification, desulfurization, and dust collection in the operation of coal- and NG-fired power plants.

Concerning Japan, sector 2 (mined and quarried goods), sector 26 (business support services), and sector 6 (petroleum and coal products) are ranked first, second, and third, respectively. Rather than simply importing NG and coal for power generation, Japan imports them through overseas development by its companies. Thus, Japan shows the greatest production-inducing effect in sector 2. The production-inducing effect of sector 26 is also high because legal services and consulting services are used to a large extent in the process of operating power plants and selling electric power. Because oil and coal products are used widely in power generation, the production-inducing effect on sector 6 is ranked third.

3.4. Value-Added Creation Effects of the EPS

The results from comparing the effects of one dollar of investment or production in the South Korean and Japanese EPSs on creating the value-added are reported in column 3 of Table 4. $a_K^V$, the value-added coefficient of the South Korean and Japanese EPSs, are 0.30422 and 0.36567, respectively. The former is smaller than the latter. However, the value-added creation effects of the South Korean and Japanese EPSs on other sectors are 0.21376 and 0.20146, respectively. The former is greater than the latter. The total value-added creation effects, defined as the sum of the value-added coefficient and the value-added creation effect, of the South Korean and Japanese EPSs are 0.51798 and 0.56713, respectively. The latter is larger than the former. The total value-added creation effects of one dollar of investment or production in the South Korean and Japanese EPSs are presented in Figure 3. Although the value-added creation effect of the South Korean EPS is greater than that of the Japanese EPS, Japan’s total value-added creation effect is greater than South Korea’s because the value-added coefficient of the Japanese EPS is much greater than that of the South Korean EPS.

In South Korea, the sector with the greatest value-added creation effect is sector 16 (gas and steam supply), the same as the production-inducing effect, followed by sector 25 (professional, scientific, and technical services), and sector 23 (finance and insurance). However, the value-added creation effects for sector 32 (others) and sector 8 (nonmetallic minor products) are low. As to Japan, the value-added creation effect for sector 26 (Business support services) is the greatest, followed by sector 20 (Transportation) and sector 31 (other services). The value-added creation effects for sector 25 (professional, scientific, and technical services) and sector 21 (food services and accommodation) have relatively low values.

Since South Korea imports all of its NG from overseas in the form of liquefied NG, the price of NG is quite high compared to the price of nuclear energy and coal. Therefore, although the share of NG-fired generation in total power generation is 30%, the share of NG-fired generation costs in total power-generation costs is significantly more than half. When the output of the EPS increases, sector 16 (gas and steam supply) has the largest increase in output and value added among the sectors. In addition, because the proportion of nuclear, coal, and NG power generation in the country is close to 90%, the output and value added of sector 25 (professional, scientific, and technical services), which relates to power-plant maintenance, greatly increases. Basically, in the EPS, a sales company purchases the electricity produced by purchasing fuel in advance, supplying it to the consumer, and collecting the fee later. Accordingly, an increase in EPS output in relation to fuel purchase, power generation, and power purchase has a significant impact on the output and value added of sector 23 (finance and insurance). While South Korea has only one electricity sales company, Japan has introduced competition in the electricity sales market, and a large number of electricity sales companies exist in the electricity market. An increase in Japanese EPS output increases the value added of sector 26 (business support services) by the most among all the sectors. South Korea warrants a revitalization of sector 26 (business support services) by opening up its monopolistic electricity sales market and introducing competition as has been done in Japan.

3.5. Wage-Inducing Effects of the EPS

The results of calculating the wage-inducing effects caused by one dollar of investment or production in the South Korean and Japanese EPSs are shown in column 4 of Table 4. The sums of the wage-inducing effects on other sectors are 0.08422 and 0.08468 in the two countries, showing little difference. However, the wage coefficients, which means the ratio of wages to total input, are 0.08380 and 0.00347, respectively. These values differ considerably. For this reason, the total wage-inducing effects are 0.16802 and 0.08815. The total wage-inducing effects of one dollar of investment or production in the South Korean and Japanese EPSs are given in Figure 4.

The figure in South Korea is about twice as high as that in Japan. This seems to reflect that the South Korean EPS has a higher wage level than other sectors. Unlike the Japanese EPS, which is highly competitive, the South Korean EPS has a larger wage coefficient. This is because public power-generation corporations, which account for more than half of the share of power generation and have a monopoly in power sales, play a leading role in the electric power market.

The South Korean sectors with a high wage-inducing effect are sector 25 (professional, scientific, and technical services), sector 26 (business support services), and sector 23 (finance and insurance). However, the wage-inducing effects for sector 32 (others) and sector 8 (nonmetallic mineral products) are low. As for Japan, sector 20 (transportation) has the greatest wage-inducing effect, followed by sector 22 (communications and broadcasting) and sector 31 (other services). The wage-inducing effects for sector 25 (professional, scientific, and technical services), and sector 21 (food services and accommodation) are the lowest.

3.6. Job-Creation Effects of the EPS

The results of examining the job-creation effects of USD 1.0 million worth of investment or production in the EPSs of both countries are shown in

Table 5. Job-creation effects of USD one million of investment or production in the South Korean and Japanese electric power sectors.

Sectors a	South Korea b		Japan b
	Value	Rank	Value	Rank
1.	0.05822	15	0.01322	14
2.	0.01154	26	0.06957	9
3.	0.01589	24	0.00096	30
4.	0.01834	23	0.00789	19
5.	0.02256	20	0.06842	10
6.	0.00492	30	0.00909	18
7.	0.09887	8	0.01942	12
8.	0.00188	31	0.00708	21
9.	0.01376	25	0.00577	23
10.	0.08087	10	0.02385	11
11.	0.03188	16	0.00480	24
12.	0.09764	9	0.00320	26
13.	0.02656	19	0.01190	15
14.	0.05958	14	0.01120	16
15.	0.00693	29	0.00594	22
16.	0.11642	7	0.00329	25
17.	0.03053	17	0.16984	5
18.	0.06538	11	0.13794	7
19.	0.33397	2	0.34681	4
20.	0.16016	5	0.39795	3
21.	0.17717	4	0.00005	31
22.	0.06179	13	0.10716	8
23.	0.11999	6	0.14815	6
24.	0.02837	18	0.01355	13
25.	0.34893	1	0.00000	32
26.	0.32553	3	0.78696	1
27.	0.01073	27	0.00757	20
28.	0.00914	28	0.00979	17
29.	0.02234	21	0.00179	28
30.	0.02156	22	0.00263	27
31.	0.06345	12	0.56377	2
32.	0.00000	32	0.00139	29
Sum (A)	2.44490		2.96095
Effect on the electric power sector (B)	0.09775		1.03860
Total (A + B)	2.54265		3.99955

^a The sectors are explained in Table 2. ^b The unit is the number of employees per USD 1.0 million.

. Since the South Korean currency unit and the Japanese currency unit are different, the job-creation effect was, for convenience, calculated based on the USD using exchange-rate information [69]. The number of people employed in the power sector per USD 1.0 million of production in South Korea and Japan is about 0.10 and 1.04, respectively. The latter is more than 10 times that of the former. South Korea has a relatively small number of employees in the EPS. Compared to the South Korean EPS, the Japanese EPS seems to be more labor intensive. The job-creation effects of the South Korean and Japanese EPSs on other sectors are about 2.44 and 2.96, respectively. The latter is greater than the former. Therefore, the total job-creation effects are 2.54 and 4.00, respectively. The total job-creation effects of USD 1.0 million of investment or production in the South Korean and Japanese EPSs are illustrated in Figure 5. Those in Japan are much greater than those in South Korea. The higher job-creation effect does not necessarily mean that the electric power industry structure is more desirable. However, the fact that the total job-creation effect of the EPS in South Korea is smaller than that in Japan suggests that South Korea needs to enhance the job-creation effect.

The sectors with the greatest job-creation effects in South Korea are sector 25 (professional, scientific, and technical services), sector 19 (wholesale, retail trade, and community brokerage services), and sector 26 (business support services). Sector 32 (others) and sector 8 (nonmetallic mineral products) have small job-creation effects. As to Japan, sector 26 (business support services), sector 31 (other services), and sector 20 (transportation) have the greatest job-creation effects, while sector 25 (professional, scientific, and technical services), and sector 21 (food services and accommodation) show the smallest job-creation effects.

3.7. Supply-Shortage Effects of the EPS

Table 6. Effects of one dollar of supply shortage in the output of the South Korean and Japanese electric power sectors.

Sectors a	South Korea		Japan
	Value	Rank	Value	Rank
1.	0.02388	24	0.01312	26
2.	0.00228	31	0.00193	32
3.	0.05382	13	0.04391	11
4.	0.02307	25	0.00690	28
5.	0.03263	19	0.04678	10
6.	0.02547	22	0.00844	27
7.	0.13940	3	0.09430	3
8.	0.03218	20	0.01898	22
9.	0.14998	1	0.12967	1
10.	0.05798	10	0.02591	19
11.	0.07348	7	0.03533	12
12.	0.03924	16	0.02219	20
13.	0.05437	11	0.04695	9
14.	0.11171	4	0.09200	4
15.	0.01052	29	0.00424	30
16.	0.00785	30	0.00475	29
17.	0.02200	26	0.03198	13
18.	0.09203	6	0.05566	6
19.	0.09689	5	0.10670	2
20.	0.04805	14	0.05359	8
21.	0.06720	8	0.05542	7
22.	0.03749	17	0.03074	15
23.	0.03574	18	0.01523	24
24.	0.04667	15	0.02021	21
25.	0.14296	2	0.01456	25
26.	0.01699	28	0.02829	18
27.	0.02827	21	0.02972	17
28.	0.05427	12	0.03025	16
29.	0.06352	9	0.06292	5
30.	0.02403	23	0.01744	23
31.	0.02032	27	0.03080	14
32.	0.00191	32	0.00337	31
Sum	1.63620		1.18226

^a The sectors are explained in Table 2.

shows the results of looking into the supply-shortage effect, which is the production disruption effect that occurs in other sectors when one dollar worth of output in the South Korean or Japanese EPSs is not properly supplied to the economy. The sums for the two countries are 1.63620 and 1.18226, respectively. The former is about 1.4 times greater than the latter. This means that the national effect of an electric power supply shortage in South Korea is 1.4 times that in Japan. The total effects of one dollar of supply shortage in the output of the South Korean and Japanese EPSs are provided in Figure 6. Both South Korea and Japan are manufacturing powerhouses, but the proportion of the gross domestic product of the South Korean manufacturing industry is much larger than that of the Japanese manufacturing industry. In particular, South Korea’s major manufacturing industries consume large quantities of electricity. According to the South Korea Electric Power Corporation (KEPCO), in 2020, 59.2% of the total electricity consumption was attributed to the manufacturing sector. This sector includes steel, oil refining, petrochemicals, semiconductors, and automobiles. Therefore, it seems natural that the supply-shortage effect of the South Korean EPS is greater than that of the Japanese EPS.

Sector 9 (basic metal products), sector 25 (professional, scientific, and technical services), and sector 7 (chemical products) are the sectors suffering the greatest supply-shortage effect in South Korea. Since all three sectors consume high quantities of electricity, this result is natural. On the other hand, sector 32 (others) and sector 2 (mined and quarried goods), which use relatively little electricity, are sectors with low supply-shortage effects. As for Japan, sector 9 (basic metal products), sector 19 (wholesale, retail trade, and community brokerage services), and sector 7 (chemical products) have the largest supply-shortage effects. Sector 2 (mined and quarried goods) and sector 32 (others) reveal the smallest supply-shortage effects. In other words, it can be seen that the structure of the supply-shortage effects in South Korea and Japan is not quite different.

3.8. Price Effects of the EPS

By applying the price-side model, the results from calculating the impacts of a 10% increase/decrease in the output price for the EPS on other sectors’ prices are shown in

Table 7. Price effects of a 10% increase in the output price of the South Korean and Japanese electric power sectors.

Sectors a	South Korea b		Japan b
	Value	Rank	Value	Rank
1.	0.23947	16	0.17009	21
2.	0.33627	7	0.01855	32
3.	0.24616	14	0.19357	17
4.	0.20826	23	0.13760	26
5.	0.44168	4	0.48659	4
6.	0.11736	30	0.08507	28
7.	0.31524	8	0.37117	6
8.	0.47833	3	0.54761	3
9.	0.66537	1	0.64581	1
10.	0.35369	6	0.40610	5
11.	0.16180	25	0.24301	11
12.	0.22596	19	0.21722	16
13.	0.24185	15	0.24032	12
14.	0.23585	18	0.31212	9
15.	0.27202	10	0.14669	23
16.	0.14576	27	0.22528	14
17.	0.57592	2	0.62289	2
18.	0.21105	22	0.18612	19
19.	0.21412	21	0.22691	13
20.	0.19524	24	0.18599	20
21.	0.24750	13	0.33478	8
22.	0.15268	26	0.11959	27
23.	0.12225	29	0.08407	29
24.	0.12788	28	0.05094	31
25.	0.39013	5	0.14494	24
26.	0.10863	32	0.08407	30
27.	0.11192	31	0.15213	22
28.	0.26328	12	0.24334	10
29.	0.23947	17	0.18938	18
30.	0.30253	9	0.36020	7
31.	0.21629	20	0.21834	15
32.	0.26646	11	0.14435	25
Weighted average	0.23995		0.21873

^a The sectors are explained in Table 2. ^b The unit is percent.

. The last row presents the magnitude of the effect on the overall price level. This value is derived as the weighted average of the sector-specific price effects on the total output of each sector. The arithmetic mean may be considered, but this does not properly represent the price effect because it does not reflect the difference in the total output of each sector. The arithmetic averages of the price effect for the two countries are 0.26345% and 0.24359%, respectively. However, the weighted averages are 0.23995% and 0.21873%, respectively. The arithmetic mean values and the weighted mean values are significantly different. The total price effects of a 10% increase in the output price of the South Korean and Japanese EPSs are shown in Figure 7.

Looking at the price effect for South Korea by sector, sector 9 (basic metal products), sector 17 (water supply, sewage, waste treatment, and disposal services), and sector 8 (nonmetallic mineral products) have the largest values. In these sectors, since electricity bills account for a relatively large fraction of the total production cost of the output, the price effect seems to be large. On the other hand, sector 26 (business support services) and sector 27 (public administration, defense, and social security services) have low price effects. As for Japan, the price effects for sector 9 (basic metal products), sector 17 (water supply, sewage, waste treatment, and disposal services), and sector 8 (nonmetallic mineral products) are large, which is interestingly the same as in South Korea. The sectors with low price effects are sector 2 (mined and quarried goods) and sector 24 (real estate services).

4. Discussion of the Results

The results reported in Section 3 will be discussed from two perspectives: the implications and the potential uses of the results. First, for convenience, several implications can be derived from

Table 8. Summary of the economic effects in the South Korean and Japanese electric power sectors.

	South Korea	Japan
Production-inducing effects
Effects on other sectors	0.62449	0.71478
Effect on the electric power sector	1.00000	1.00000
Sum	1.62449	1.71478
Value-added creation effects
Effects on other sectors	0.21376	0.20146
Effect on the electric power sector	0.30422	0.36567
Sum	0.51798	0.56713
Wage-inducing effects
Effects on other sectors	0.08422	0.08468
Effect on the electric power sector	0.08380	0.00347
Sum	0.16802	0.08815
Job-creation effects a
Effects on other sectors	2.44490	2.96095
Effect on the electric power sector	0.09775	1.0360
Sum	2.54265	3.99955
Supply-shortage effects	1.63620	1.18226
Price effects b	0.23995	0.21873

^a The unit is the number of employees per USD 1.0 billion of investment or production in the electric power sector. ^b The unit is percent per 10% increase in the output price of the electric power sector.

, which summarizes the results of investigating the six economic effects. First, with respect to the four economic effects obtained from the demand-side model, Japan shows greater total effects of the EPS on inducing production and creating value added than South Korea. South Korea should make efforts to improve the value-added coefficient of the EPS. The difference is not very large, and it seems to be due to the industrial and market structure of the EPSs in the two countries.

The South Korean EPS is strongly regulated by the government. Government-established public corporations are in charge of more than 80% of the total power generation. The only electricity distributor is also a government-established public corporation. In other words, the amount of power generated by private power-generation companies is increasing, but the electric power industry structure is still centered on public enterprises. Thus, the scope for improving production-inducing and value-added creation effects is somewhat limited. On the other hand, in Japan, the electricity sales market is open and competitive, and various public and private companies are active in the electric power-generation market. South Korea should make efforts to enhance the effects of the EPS on inducing production and creating value added by making a more competitive market environment. The authors think that competition should be more active in the South Korean EPS. Stimulating competition does not necessarily mean privatization. Even if privatization does not gain ground, more active competition can be promoted through facilitating network neutrality and liberalizing entry and exit.

Second, the total job-creation effect of the Japanese EPS is about 1.57 times greater than that of the South Korean EPS. Not only does the Japanese EPS cause more job creation in other industries, but also the number of employees per USD 1.0 million output in the South Korean EPS is less than a tenth of that in the Japanese EPS. As mentioned earlier, the South Korean EPS is centered on public enterprises. Therefore, competition in the market is weak. It seems that this leads to a high wage structure and reduces employment. In particular, the Japanese electric power sales market employs large numbers of people to expand its share in the market because of the fierce competition. A relatively small number of employees in the South Korean EPS may mean high efficiency, but it is not in line with the government’s plan to create jobs through the growth of the EPS. The authors think that deregulating the electricity industry would make the labor market of the South Korean EPS less monopsonic and more competitive [16].

Third, the total wage-inducing effect of the Japanese EPS is about half that of the South Korean EPS. In fact, the wage-inducing effect on other industries is almost the same for the two countries. However, the wage coefficient in the South Korean EPS is 24 times that in the Japanese EPS. This is an interesting finding. It clearly shows the aforementioned high wage structure of the South Korean EPS. The structure of the South Korean EPS, which is centered on government-owned companies, seems to have raised the wage coefficient compared to Japan.

Fourth, the supply-shortage effect of the South Korean EPS is about 1.4 times that of the Japanese EPS. This means that electric power supply disruptions cause more damage to South Korea than to Japan. The South Korean economic system depends heavily on exports by the manufacturing sectors, and all the major exporting manufacturing industries of South Korea consume more electricity than the manufacturing industries of Japan. Therefore, for the purpose of increasing the price competitiveness of the South Korean manufacturing industry, efforts should be made to reduce the ratio of electricity bills to their total costs by innovating to change the industry’s electricity-consumption structure to a less electricity-consuming structure.

Of course, this is quite difficult, since further development of industry will make firms use more electricity, and the wealth effect from industry upgrades will dominate the substitution effect from phasing out less efficient production machines. Even if the total electricity consumption in the industrial sector increases, various measures to reduce electricity costs as a proportion of total costs are being implemented in South Korea. For example, large-scale generation for self-consumption could be installed. One semiconductor manufacturer has installed and is operating a natural gas-fired power plant with a capacity of 580 MW for its own consumption and is currently constructing an additional power plant of the same capacity. Since generation for self-consumption does not require transmission facilities, spending on electricity can be reduced compared to purchasing electricity. Increasingly, industrial companies with processes that require heating or cooling generated by electricity are reducing their electricity bills by utilizing heating or cooling from sewage or river water [70,71,72]. In addition, electricity bills are being reduced by performing basic processes that consume a lot of electricity in foreign countries where electricity rates are low and performing final processes that consume relatively less electricity domestically.

Fifth, the price effect of an increase in the South Korean electricity bills is 9.7% greater than the effect on Japanese electricity bills. In other words, a rise in electricity bills has a more substantial impact on the production costs of South Korea than it does in Japan. This is because South Korea accounts for a larger share of electricity bills in total production costs than Japan. In addition, curbing the increase in electricity bills in South Korea has a more significant price-stabilization effect compared to Japan. For this reason, the South Korean government is implementing a stronger electricity rate suppression policy than the Japanese government. For example, the cumulative deficit of KEPCO, South Korea’s only electricity distributor, reached about KRW 47.5 trillion (USD 37.0 billion) by the first half of 2023. To the extent of the authors’ knowledge, KEPCO is the only large power seller in the OECD countries that is carrying such a huge deficit. The accumulated deficit is more than three times the market capitalization of KEPCO, which is KRW 13 trillion (USD 10.1 billion). If KEPCO had been a private company, it would have gone bankrupt already. However, since KEPCO is a public company with the government holding a 51% stake, it is still carrying on. Similarly, Taiwan Electric Power Corporation, which is also state owned and suffering enormous deficits owing to government directives to smooth inflation and absorb price hikes, posted a deficit of TWD 400 billion (USD 12.7 billion) in 2023.

The results described above have various potential uses. Various new power-supply projects are being planned because power demand will rise in the future, and the findings from this research can be employed to proactively diagnose the backward economic effects of these projects. For instance, according to the Korea Ministry of Trade, Industry, and Energy [12], the new construction of a number of NG-fired power plants, the phase-out of existing coal-fired power plants, the new construction of nuclear power plants, the extension of the lives of existing nuclear power plants, and the expansion of RE are scheduled. We can predict in advance the effect on production, value added, wages, and jobs that will occur in the national economy when these projects are carried out as planned.

Second, the results of employing the supply-side model enable us to set the priority for supplying electricity to each group of consumers. In the event of electricity rationing, it is important to identify which sectors should be supplied first with electricity when only a limited amount of electricity can be supplied. If the principle of prioritizing supply to sectors that would suffer high levels of damage is socially accepted, the supply-shortage effect by sector presented in this study can be used as an important basis. When the electricity supply was disrupted in the model by the same amount, the hardest-hit sector was basic metal products for both South Korea and Japan. Thus, from an industrial perspective, the rationale for preferentially supplying electricity to the basic metal products sector can be justified in terms of minimizing damage to society.

Third, the results of utilizing the price-side model can be used to predict the price effect of electricity rate hikes or cuts in advance. Fuels such as NG, oil, coal, and uranium are used to generate electricity. The international price of these fuels must be the most important factor for determining electricity bills. Knowing in advance the impact on the overall price level of adjusting electricity rates as fuel prices rise or fall would help industries to take the necessary follow-up measures early. In addition, if price adjustments would result in a significant price effect in a particular sector, consideration could be given to curbing the rise in product prices in that sector by subsidizing some of the electricity bills for that sector. Although KEPCO is already suffering a huge loss, the government operates a large-scale power industry infrastructure fund. Therefore, the government has the capacity to implement a subsidy. In South Korea, the fund, which is equivalent to 3.7% of the electricity bill, is levied on all consumers in addition to the electricity bill. In any case, rather than discussing measures for raising or lowering electricity rates without any information, the measures will be more productive and effective if they are discussed with the benefit of information on price effect by sector.

5. Conclusions

Stabilizing the EPS is a crucial task for national survival in Japan and South Korea, which have similar electric power supply conditions. Moreover, in the ongoing process, the EPS must go beyond its conventional role of supplying electricity and instead function as a growth engine for generating new jobs. This article not only delved into the roles of the South Korean and Japanese EPSs in the national economies through the IO technique but also tried to draw implications by comparing the results. This article makes a significant contribution to the existing literature in two ways. The first is that by utilizing the most recently published IO tables of the two countries as input data, the results have been updated. Furthermore, because the EPS was treated exogenously, not endogenously, the economic impacts of the EPS on other sectors can be quantitatively analyzed, focusing on the EPS. The second is that, by horizontally comparing the results for South Korea and Japan, various implications can be derived.

The production-inducing, value-added creation, and job-creation effects of the South Korean EPS are smaller than those of the Japanese EPS. South Korea and Japan have similar export-led economic systems based on manufacturing, but Japan’s economic capabilities and status are clearly higher than those of South Korea. In addition, Japan pursued modernization and industrialization before South Korea. Consequently, South Korea is adopting an industrial development strategy that seeks to pursue and leapfrog Japan, while referring to Japan’s industrial structure. Assuming that South Korea should pursue Japan, which is a more advanced country than South Korea, the South Korean EPS should strive to enhance these three effects. However, the wage-inducing, supply-shortage, and price effects of the South Korean EPS are greater than those of the Japanese EPS. Since the South Korean EPS has a higher wage structure than the Japanese EPS, South Korea should further boost competition in the electricity sector so that it can increase jobs rather than high wages. Since the supply shortage of electricity in South Korea can cause more economic damage than a shortage in Japan, preemptive investment to stabilize the electric power supply is essential. KEPCO, South Korea’s only electricity transmission, substation, distribution, and sales company, is suffering from large-scale deficits and is unable to invest properly in electricity transmission, substations, and distribution facilities. It is difficult for KEPCO to maintain and repair the existing facilities, let alone invest in new facilities. Thus, concerns are growing about the stability of the power supply. According to the government, approximately KRW 100 trillion (USD 78 billion) needs to be invested in transmission, substation, and distribution facilities by 2036. Furthermore, since the price effect of an increase in the output price of the South Korean EPS is higher than that for the Japanese EPS, careful measures should be taken to reduce the negative impact on prices when the inevitable electricity rate hikes are made. For instance, the government could suppress the overall electricity rate increases by injecting finances into KEPCO. In the past, the South Korean government invested KRW 600 billion (USD 467 million) to suppress electricity rate increases. Alternatively, the government could provide subsidies on electricity bills for specific sectors through finance. Moreover, the government could force KEPCO to provide discounts on electricity rates for essential areas, despite its deficits.