The Economic and Environmental Effects of a Green Employer of Last Resort: A Sectoral Multiplier Analysis for the United States

Abstract

We assess the sectoral impact of the implementation of a “green” employer of last resort (ELR) program in the US, based on an environmental modification of an extended Kurz’s (1985) multiplier framework and data from OECD Input-Output tables. We use these multipliers to estimate the impact of an “optimal” ELR, designed to maximize the impact on both output and employment while minimizing both imports and carbon emissions. We then test several alternative policy scenarios based upon different compositions of US government expenditure. We provide evidence that (1) investing in the optimal sectors in terms of output, employment, CO₂, and import multipliers does not always deliver optimal results in the aggregate; (2) ecological sustainability for the US economy also fosters import sustainability; (3) a rebounding effect in CO₂ emissions may be tamed if the ELR satisfies the abovementioned optimality condition, though this undermines its success in terms of output and employment.

Keywords:

• Employer of last resort
• Ecological transition
• CO₂ emissions
• Trade deficit

JEL CLASSIFICATIONS:

• B52
• C67
• D57
• J68
• Q43

Acknowledgements

We are grateful to Malcom Sawyer, the participants at the 2022 FMM Conference and two anonymous referees for their useful comments on the first draft of this paper. Of course, any remaining mistakes should be attributed to ourselves.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 The concept of the multiplier was introduced in the 1930s by Kahn (1931), Keynes (1936, Chap. 10) and Kalecki ([1933] 1990). What follows is primarily based on the theoretical contributions of Kurz (1985) and Metcalfe and Steedman (1981) and the relevant empirical applications of Mariolis et al. (2009), Rodousakis and Soklis (2022a, 2022b) and Apostolopoulos et al. (2022). For further generalization to the case of joint production, see Mariolis (2008), whilst for relevant empirical applications to the joint production case, see Mariolis and Soklis (2018) and Mariolis et al. (2018, 2021). For early contributions in the concept of the multiplier as a matrix, see Leontief (1941), Goodwin (1949), and Chipman (1950).

2 Assumptions (ii) and (iv) are imposed by the available input-output data, which include no information on inter-industry fixed capital stocks and non-competitive imports. Assumption (v) is also partially imposed by the available data, which include no information about the timing of payments. We choose to assume that wages are paid at the end of the common production period instead of assuming complete advancement of payments because it can be shown that the former case constitutes a better approximation to reality than the latter case (see Steedman 1977, 103–105).

3 See for instance the work of Miyazawa (1960), Miller and Blair (2009, ch. 6) and Ten Raa (2005, ch. 3).

4 For empirical studies of the savings ratios, see Bowles and Boyer (1995), Naastepad and Storm (2007), Hein and Vogel (2008), and Onaran and Galanis (2013).

5 This is driven, in particular, by sector TTL 03: Fishing and aquaculture. This means that for this industry, second-round multiplier effects as measured in Kurz (1985) are negative due to the fact that US presents higher than average import multipliers as also shown in Figure 1. It should be noted that primary effects (which corresponds to Leontief simple multipliers) are still positive also for sector TTL03.

6 As is well known, Miyazawa (1960) introduced multipliers in a Leontief framework, incorporating imports.

7 These are: TTL 01T 02: Agriculture, hunting, forestry; TTL 10T 12: Food products, beverages and tobacco; TTL 16: Wood and products of wood and cork; TTL 17T 18: Paper products and printing; TTL 19: Coke and refined petroleum products; TTL 20: Chemical and chemical products; TTL 22: Rubber and plastics products; TTL 24: Basic metals; TTL 29: Motor vehicles, trailers and semi-trailers; TTL 50: Water transport.

8 Since we are not taking into account the direct effect of a ELR program, the results for employment are also in line with the figure provided by Nersisyan and Wray (2021), in particular those related to the indirect multiplier effects.

9 Pavitt (1984) identified the following four groups: Science-Based industries (SB), which include sectors where innovation is based on advances in science and R&D and where research laboratories are important, leading to intense product innovation and a high propensity to patent; Specialized Suppliers industries (SS), such as the sectors producing machinery and equipment, in which R&D is present but an important innovative input comes from tacit knowledge and design skills embodied in the labor force; Scale and Information Intensive industries (SI), in which scale economies are relevant (automotive and basic metals) and a certain rigidity of production processes exists, so that technological change is usually incremental; Supplier Dominated industries (SD), which encompass traditional sectors (such as food and textile) where small firms are prevalent and technological change is introduced through inputs provided by suppliers from other industries.

10 More precisely, these industries are: fishing and aquaculture; mining and quarrying energy-producing products; mining and quarrying non-energy-producing products; Wood and products of wood and cork; basic metals; fabricated metal products; computer, electronic and optical equipment; electrical equipment; machinery and equipment, nec; Construction. As a matter of fact, also the vector y in Scenarios 3, 4, and 6 contains negative entries, but in these cases the increase in the other sectoral components of autonomous demand delivers better results in the aggregate.

Additional information

Notes on contributors

Nikolaos Rodousakis

Nikolaos Roudosakis is a Senior Researcher in the Center of Planning and Economic Research (KEPE). He is also a Research Scholar of Levy Economics Institute of Bard College and member of the Steering Committee of the Greek National Productivity Board. He holds a PhD in Political Economy from the Department of Public Administration of the Panteion University of Social and Political Sciences, Greece.

Giuliano Toshiro Yajima

Giuliano Toshiro Yajima is a Research Scholar at the Levy Institute of Bard College. He holds a PhD in Economics and Finance from the University of Rome La Sapienza.

George Soklis

George Soklis is Assistant Professor at Panteion University of Social and Political Sciences. He holds a PhD in “Economics” from the Department of Public Administration of the same university.