서울시 유통산업의 지역경제적 파급효과 분석: 지역간 산업연관모델(IRIO)을 중심으로

초록

Ⅰ. Introduction and Theoretical BackgroundThis study aims to estimate the economic impact of the distribution industry for the year of2011 on the economies of the Seoul, metropolitan Seoul and other region. To this end anInter-Regional Input-Output (IRIO) model was employed to derive distribution multipliers interms of output, income, employment, and value-added, using the regional I-O transactionstables developed by Bank of Korea (2009). Ⅱ. Research MethodologyAn I-O model is classified into national and regional models. While the national I-O modeldeals with the transactions of a country as a whole, the regional I-O model addressestransactions of a specific region. The production structure in a particular region may beconsiderably different in the national I-O transactions table (Miller and Blair 1985; Miyagawa1976). Thus, this study employs a regional I-O model to measure the economic impact ofdistribution industry on the Seoul metropolitan economy. Bank of Korea (2009) published 16 interregional I-O (IRIO) transactions tables, whichinclude Seoul metropolitan city. The IRIO tables include a 16 x 16 region matrix in which thisstudy aggregated the tables into a 2 x 2 region matrix including Seoul and other region. To simplify the description to the IRIO model we supposed a two-region economy (Seoul, Otherregion). Meanwhile, The IRIO (Inter-Regional Input-Output) model was first proposed by Isard(1951). The I-O framework consists of three major sectors; intermediate, primary input, andfinal demand sectors (Leontief 1966). The IRIO model can be expressed in a simple accounting equation (Bank of Korea, 2009):                          (1)where Z = intermediate demand, Y = final demand, X = intraregional output, d = domesticinput, and 1 and 2 = region 1 and 2. An input coefficient (      ) represents the proportion of sector  required fromsector  to produce one unit of output for sector  Equation (1) can be expressed using theinput coefficient as:                                  (2)Equation (3) can be expressed in the form of the following matrix:                 (3)Denoting the entire matrix of input coefficients as 'A' the matrix can be described in a simpleI-O accounting equation:       (4)Solving equation (4) for X gives the following equation:             (5)The matrix      , known as the Leontief inverse matrix, representing the output multiplier, indicates the direct and indirect effects throughout the regional economy on Seoulresulting from one unit change in final demand. Ⅲ. ResultsAs mentioned above distribution industry sectoral multipliers are estimated with two regions(i.e., Seoul, other regions). In specific, table 3 presents distribution industry sectoralmultipliers for output, income, employment, and value added in those two regions. Table 4 presents the economic impact of output associated with Seoul distribution industry. The economic impact was estimated by multiplying the direct sales of distribution industryrelated sectors by corresponding multipliers in terms of output, income, Value-added, andEmploy. The results of IRIO reveal that in 2011, total sales of distribution industry in Seoul city wouldgenerate approximately 609 trillion won of output impact (Seoul city: 506 trillion won, otherregion: 102 trillion won), 327 trillion won of value-added impact (Seoul city: 284 trillion won,other region: 43 trillion won), 142 trillion won of income impact (Seoul city: 127 trillion won,other region: 15 trillion won), and 9,211,708 non-paid and full-time jobs (Seoul city: 7,790,597jobs, other region: 1,421,111 jobs) throughout direct and indirect effects.

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