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Analyses of University-Partnered Economic Development Initiatives and Minimum-Wage Policies Under Different Assumptions of Competition and Scale Economies

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The Indonesian Economy and the Surrounding Regions in the 21st Century

Part of the book series: New Frontiers in Regional Science: Asian Perspectives ((NFRSASIPER,volume 76))

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Abstract

In this chapter we present general equilibrium analyses of economic development initiatives and minimum-wage policies that may be undertaken by a spatially dispersed, multiple-campus university in conjunction with a state government. The computable general equilibrium (CGE) model we employ in its two variants includes Cornell University as a sector (institution) unto itself (apart from other institutions of higher education in the state) and characterizes interactions between four regions of New York State—Tompkins County, counties adjacent to Tompkins County, the New York metropolitan area, and the rest of New York State—and areas external to the state. We compare projected policy outcomes for different assumptions about competition and scale economies.

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Notes

  1. 1.

    Indeed, the Association of Public and Land-Grant Universities and the University Economic Development Association exist in large part to promote such initiatives. See Klein and Woodell (2015).

  2. 2.

    Cornell University is among the ten largest employers in New York State.

  3. 3.

    Clearly, an institution as complex as a world-class research university has a broad range of impacts upon the community, region, and state in which it is located and increasingly upon other countries. In this analysis, however, our focus will be limited to expenditures and employment. In that regard, our study complements Florax (1992), which examines the impact of universities on (aggregate) manufacturing investments using the method of spatial econometrics.

  4. 4.

    This is a heroic and questionable counterfactual assumption. Consider that if another institution with an annual operating budget the size of Cornell’s at approximately US$ 5.25 billion were to attempt to begin operation in New York State what supply constraints and skilled labor shortages in particular it would encounter. Therefore, we would submit that it is perhaps more appropriate to use impact analysis models to assess actual or potential impacts of specific initiatives or, when considering the overall impact of an institution’s activities, employ several complementary analytical approaches.

  5. 5.

    CGE models have also been developed to use economic theory to overcome data limitations.

  6. 6.

    See also Sue Wing and Anderson (2007). Isard and Azis (1998) provides a thorough methodological introduction to interregional/multiregional CGE modeling. While Azis has contributed much to this area of CGE modeling theory, methods, and applications, he has contributed more widely to the use of CGE models to study problems of developing economies (Azis 1995), exchange rates and capital flows (Azis 1999), sustainable development (Azis and Roland-Hurst 1999), financial crises (Azis 2000a, b), and financial flows (Azis 2018).

  7. 7.

    Table 14.2 defines the notation employed in Fig. 14.1 and variations on this notation employed in the algebraic specification of the model in the ensuing pages of this section.

  8. 8.

    The three conditions F(z) ≥ 0, z ≥ 0, and zTF(z) = 0 taken together constitute what is known as a “complementary slackness condition” of nonlinear programming. See, e.g., Sydsaeter et al. (1999).

  9. 9.

    See footnote 6 above.

  10. 10.

    As a referee of this chapter has correctly observed, we have neither conducted nor reported an extensive sensitivity analysis of the model’s calibration in its two specifications. However, given the nest of aggregator functions chosen for the model’s specification, the model has been found to be quite stable and robust to small changes in parameter values in experiments in parametric variation conducted with the model ported to the EMP facility of GAMS at the University of Wisconsin at Madison (Ferris 2023). As observed above, our primary interest in this chapter lies in comparing the solutions of the model for the policies considered in the next section under different assumptions about competition and technology.

  11. 11.

    We acknowledge that the selection of 10% as the variation in investment and indirect taxes may appear to be arbitrary, but actual variations would depend upon specific projects undertaken by actual businesses. So, we have chosen a variation that we believe to be feasible and conservative.

  12. 12.

    Although we have not considered here the fiscal impacts on New York State or the regions considered of raising the minimum wage to US$ 15, the recent report by Ziperrer et al. (2021) estimated that if the 2021 Raise the Wage Act (which expired in Congress) were to have been passed, and the federal hourly minimum wage increased to US$ 15 by 2025, the earned income tax credit (EITC) and child tax credit (CTC) expenditures at the federal level would decline somewhere between US$ 6.5 billion and US$ 20.7 billion annually. Expenditures on the Supplemental Nutrition Assistance Program (SNAP) and other major government transfers would fall between US$ 5.2 billion and US$ 10.3 billion annually, and annual expenditure on SNAP alone would be reduced by US$ 3.3 to US$ 5.4 billion. Zipperer et al. also estimate that a US$ 15 minimum wage in 2025 would increase annual Federal Insurance Contributions Act (FICA) revenue by between US$ 7.0 billion and US$ 13.9 billion (Ziperrer et al. 2021:1).

  13. 13.

    For a discussion of ideas regarding how this can be done, see Giesecke and Madden (2013) and Donaghy (2019).

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Correspondence to Kieran Donaghy .

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Appendices

Appendix 1. PC-CRTS and IC-IRTS Models

Table 14.6 Benchmark solution of the PC-CRTS and IC-IRTS models

Appendix 2. Detailed Model Solutions for Policy Scenarios

Table 14.7 Regional industrial output
Table 14.8 Impacts of policies on sectoral consumption by region
Table 14.9 Impacts of policies on foreign imports by region
Table 14.10 Impacts of policies on domestic imports by region
Table 14.11 Impacts of policies on foreign exports by region
Table 14.12 Impacts of policies on domestic exports by region
Table 14.13 Impacts of policies on household incomes by region

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Waluyo, J., Burgos, J.P., Mansury, Y., Min, H.H., Donaghy, K. (2024). Analyses of University-Partnered Economic Development Initiatives and Minimum-Wage Policies Under Different Assumptions of Competition and Scale Economies. In: Resosudarmo, B.P., Mansury, Y. (eds) The Indonesian Economy and the Surrounding Regions in the 21st Century. New Frontiers in Regional Science: Asian Perspectives, vol 76. Springer, Singapore. https://doi.org/10.1007/978-981-97-0122-3_14

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