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Key sector analysis for a subnational region with leakages

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Abstract

Key sector analyses have a long and rich history. However, almost all the previous analyses were conducted only within an input–output (IO) framework for a national economy. The present study (1) performs the analysis for a subnational (or regional) economy suffering severe leakages of industries’ revenues due to a large amount of imports and a large fraction of factor income earned by non-residents, and (2) extends the previous IO-based analyses to an analysis within a social accounting matrix (SAM) model and, further, to a multi-regional SAM (MRSAM) model. Comparing the results from the three alternative models shows that the key sectors identified with the alternative models are considerably different. This finding points to the necessity of using SAM-based models for an accurate key sector analysis and offers valuable implications for regional policymakers whose main interest is identifying the industries that they target for the economic development of their regions.

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Notes

  1. Shao and Miller (1990) examined spatial linkages within an MRIO model for US, but did not identified key sectors.

  2. TBL and TFL, respectively, are based on two different IO models—Leontief demand-driven model and Ghosh supply-driven models. The use of Ghosh-driven model as an impact analysis where the forward linkage effects of a policy change are calculated could be problematic. Dietzenbacher (1997) suggested that the Ghosh model be interpreted as a price model when it is used to describe causal interpretation of the model (for impact analysis). However, the Ghosh-driven model is acceptable if the model is used, as in the present study, to gauge, ex post, the role of an industry as supplier of inputs to its forward-linked industries (Miller and Temurshoev 2017).

  3. Admittedly, the data is somewhat old. Seafood industry data in IMPLAN is not reliable, which means that analysts should estimate the data based on information obtained from surveys or other available data. In addition, analysts should develop a SAM for seafood industry using the data thus obtained. Estimating seafood industry data and constructing a SAM requires a significant amount of time. Because the most recent year for which the seafood industry data was estimated is 2004, this study uses the IMPLAN data (only the non-seafood industry portion) for the same year (2004) for consistency, although the most recent IMPLAN data is available for year 2017.

  4. Sources used to estimate seafood industry data include the Commercial Fisheries Entry Commission (CFEC), Alaska Fisheries Information Network (AKFIN), Pacific Fisheries Information Network (PacFIN), and NMFS. The Research Group (2007) and Seung and Waters (2009) provide more detailed descriptions of the procedures followed to construct the Alaska seafood industry dataset.

  5. This study chose this method of balancing the MRSAM to preserve the original economic structures shown in elements in the endogenous sectors with the elements in the exogenous sectors adjusted to make the row and column sums equal.

  6. Other Food Manufacturing includes all the food manufacturing activities, but excludes Fish processing. Baseline data indicates that Other Food Manufacturing does not use any raw fish but use a very small amount of processed fish as intermediate input.

  7. In fact, Alaskans do eat raw and unprocessed fish, especially those caught in subsistence fisheries. However, because there is no data on Alaskans’ direct consumption of the raw and unprocessed fish, this study does not consider the role of their direct consumption of the fish. Since it is likely that their direct consumption is small compared to the total amount of commercially harvested fish from Alaska waters, omission of their direct fish consumption is not likely to change the main findings in a considerable way in this study.

  8. Exports include the exports from Alaska to rest of US and foreign countries.

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Acknowledgements

The author would like to thank Steve Kasperski and Alan Haynie for providing valuable comments on this paper. Their comments helped improve this paper significantly.

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Correspondence to Chang K. Seung.

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Appendices

Appendix 1

See Tables 4, 5 and 6.

Table 4 Industry aggregation scheme for Alaska SAM model
Table 5 Social accounting matrix for Alaska
Table 6 Simplified schematic representation of a three-region MRSAM

Appendix 2: Detailed descriptions of the structures of SAM and MRSAM models

  1. 1.

    SAM model

The SAM model in Eq. (4) can be expressed alternatively as:

$$ \left[ {\begin{array}{*{20}c} Q \\ C \\ V \\ {\text{IBT}} \\ H \\ {\text{SG}} \\ \end{array} } \right] = \left( {I - S} \right)^{ - 1} \left[ {\begin{array}{*{20}c} {\text{eq}} \\ {\text{ec}} \\ {\text{ev}} \\ {\text{et}} \\ {\text{eh}} \\ {\text{eg}} \\ \end{array} } \right], $$
(B.1)

where Q = vector of industry output (endogenous), C = vector of commodity output (endogenous), V = vector of total primary factor payments (endogenous), IBT = indirect business tax payments (endogenous), H = vector of total household income (endogenous), SG = total state and local government revenue (endogenous), eq = vector of exogenous demand for industry output, ec = vector of exogenous demand for commodity output, ev = vector of exogenous factor payments, et = exogenous indirect business tax payments, eh = vector of exogenous federal transfers to households, eg = federal transfers to state and local government.

In Equation (B.1), vectors Q, C, V, IBT, H, and SG contain elements that are endogenous variables. Vectors eq, ec, ev, et, eh, and eg have elements that are exogenous variables. Nonzero elements are included in the vectors ec, eh, and eg. Vector ec is the final demand vector whose elements are investment demand, federal government demand, and export demand. Elements of eh include federal government transfers to households and capital income inflow from outside of Alaska. The components of eg include (1) federal government transfers, (2) revenue from, for example, investments, leases, and trusts, and (3) non-Alaska residents’ tax payments. The elements in vectors ec, eh, and eg constitute injections of income or revenue into the state’s economy. Leakages of income transpire via payments to non-resident factor owners (non-resident factor income), tax payments to the federal government, savings, and imports of commodities.

  1. 2.

    MRSAM model

As mentioned, the MRSAM model can be also represented by Eq. (4):

$$ T = \left( {I - S} \right)^{ - 1} K. $$

where \( T = \left[ {\begin{array}{*{20}c} {t_{1} } \\ {t_{2} } \\ {t_{3} } \\ \end{array} } \right] \), \( S = \left[ {\begin{array}{*{20}c} {Z_{11} z_{12} z_{13} } \\ {z_{21} Z_{22} z_{23} } \\ {z_{31} z_{32} Z_{33} } \\ \end{array} } \right] \), and \( K = \left[ {\begin{array}{*{20}c} {k_{1} } \\ {k_{2} } \\ {k_{3} } \\ \end{array} } \right] \).

Here S is now the matrix of direct MRSAM coefficients and \( \left( {I - S} \right)^{ - 1} \) is now called the MRSAM multiplier matrix or the matrix of MRSAM inverse coefficients. tr and kr denote the column vectors of endogenous and exogenous accounts, respectively, for region r; Zrr is the submatrix containing coefficients representing the intra-regional transactions; and zrs is the submatrix containing coefficients representing inter-regional transactions. All the coefficients in Zrr and zrs are derived by dividing the elements in the columns in the MRSAM by the column totals.

tr is a column vector for region r comprising the following endogenous sub-vectors:

  • Qr = vector of regional industry output.

  • Cr= vector of regional commodity output.

  • Vr = vector of total primary factor payments.

  • IBTr = indirect business tax payments.

  • Hr = vector of total household income.

  • SGr = total state and local government revenue.

Zrr for region r is:

$$ Z_{rr} = \left[ {\begin{array}{*{20}c} 0 & {M_{r} } & 0 & 0 & 0 & 0 \\ {U_{r} } & 0 & 0 & 0 & {{\text{CS}}_{r} } & {{\text{GD}}_{r} } \\ {V_{r} } & 0 & 0 & 0 & 0 & 0 \\ {{\text{IBT}}_{r} } & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & {F_{r} } & 0 & 0 & {{\text{STR}}_{r} } \\ 0 & 0 & {{\text{SF}}_{r} } & {{\text{BTS}}_{r} } & {{\text{HTX}}_{r} } & {{\text{IGT}}_{r} } \\ \end{array} } \right], $$
(B.2)

where Ur= matrix of coefficients showing the use of commodities by industries in production, Vr= matrix of primary factor payments coefficients, IBTr = matrix of indirect business tax coefficients, Mr= market share matrix (i.e., elements in make matrix divided by total output), Fr = matrix of factor payment to household coefficients, SFr = matrix of state and local factor tax coefficients, BTSr = matrix of state and local indirect business tax coefficients, CSr = matrix of household consumption coefficients, HTXr = matrix of state and local government direct household tax coefficients, GDr = matrix of state and local government demand coefficients, STRr = matrix of state and local government transfer coefficients, IGTr = matrix of intergovernmental transfers.

zrs is:

$$ z_{rs} = \left[ {\begin{array}{*{20}c} 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & {{\text{IM}}_{rs} } & 0 & 0 & 0 & 0 \\ 0 & 0 & {{\text{LK}}_{rs} } & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 \\ \end{array} } \right], $$
(B.3)

where IMrs is the matrix of imports from region r to s and LKrs is the matrix of leakage of factor income from region s to region r. kr is the column vector consisting of the following exogenous sub-vectors:

  • eqr = vector of exogenous demand for regional industry output.

  • ecr = vector of exogenous demand for regional commodity output.

  • evr = vector of exogenous factor payments.

  • etr = exogenous indirect business tax payments.

  • ehr = vector of exogenous federal transfers to households.

  • egr = federal transfers to state and local government.

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Seung, C.K. Key sector analysis for a subnational region with leakages. Ann Reg Sci 65, 619–644 (2020). https://doi.org/10.1007/s00168-020-00997-1

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