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Abstract
This article applies Hyman P. Minsky’s insights on financial fragility to analyze the behavior of electricity distribution firms in Brazil from 2007 to 2015. More specifically, it builds an analytical framework to classify these firms into Minskyan risk categories and assess how financial fragility evolved over time, in each firm and in the sector as a whole. This work adapts Minsky’s financial fragility indicators and taxonomy to the conditions of the electricity distribution sector and applies them to regulatory accounting data for more than 60 firms. This empirical application of Minsky’s theory for analyzing firms engaged in the provision of public goods and services is a novelty. The results show an increase in the financial fragility of those firms as well as of the sector throughout the period, especially between 2008 and 2013.
Notes
1 As an example, Tymoigne (Citation2010) analyzed Ponzi finance in residential housing in the U.S. household sector.
2 ANEEL Research and Development Project PA3009, “Economic and Financial Sustainability Index of Electricity Distribution Firms.
3 This unprecedented dataset was built by the Study Group on the Electric Energy Sector (GESEL) from the Federal University of Rio de Janeiro (UFRJ), based on regulatory information provided to the public by ANEEL.
4 According to Minsky (Citation1992), the financial instability hypothesis leverages on the work of the economists John Maynard Keynes (Citation1936, Citation1937), Irving Fisher (Fisher Citation1933), and Joseph Schumpeter (Citation1934).
5 It is worth mentioning that this perspective is very different from the mainstream view of neoclassical economists, which postulates that markets inexorably tend to reach a position of equilibrium, except when unexpected price shocks or economic policy mistakes take place.
6 When the level of current revenues is substantially lower than expected, it is necessary to review the parameters that provided the basis for the calculus behind the operations with third-party resources, be it in the form of debt or in the form of equity.
7 Three kinds of margins or cushions of safety are used as mechanisms to safeguard debts. First is the addition of an excess margin over expected revenues in order to mitigate the risk of abrupt changes in this variable over time. This kind of margin tends to diminish expected cash flows in the face of current obligations to cushion any negative fluctuation of revenues from sales or interests and rents. The second kind is associated with a positive coefficient on the market value of assets in comparison to the market value of liabilities. Alternatively, it has to do with the cushion of net worth or equity relative to indebtedness. Finally, the third kind of margin of safety is the liquid assets held in portfolios, including cash (Kregel, Citation2008, pp. 7–10; Minsky, Citation1986).
8 However, as acknowledged by Reinhardt and Rogoff (Citation2008, p. 1): “Major default episodes are typically spaced some years (or decades) apart, creating an illusion that ‘this time is different’ among policymakers and investors.
9 Ponzi units are usually associated with fraudulent financial practices, though it is not always the case (Minsky, Citation1986, p. 231).
10 Some empirical studies use the terms financial fragility or financial instability but are based on a theoretical framework that is very distinct from the one used in this work. Neoclassical and New Keynesian authors use a static notion of financial fragility, usually referring to it as an exogenous phenomenon that occurs because of random shocks, market imperfections, or inappropriate government policies (Tymoigne, Citation2010, p. 2). For “mainstream economists,” fragility is not a process, but a state or event—this result being intimately related to a deterministic treatment of time in this tradition (Schroeder, Citation2009, p. 293).
11 The sectors are the following: (a) agriculture, forestry, fishing, and hunting; (b) mining, quarrying, and oil and gas extraction; (c) utilities; (d) manufacturing; (e) transportation and warehousing; (f) information; (g) real estate, rental, and leasing; and (h) professional, scientific, and technical services.
12 The behavior compatible with the financial instability hypothesis is described by Mulligan (Citation2013, p. 452) as follows: “the percent of speculative and Ponzi firms […] fall during the recovery phase, increase over the course of the business expansion between recessions, and rise again during or prior to the next recession.
13 Though Nishi (Citation2016, p. 7) criticizes previous empirical analyses by focusing only on taxonomy and argues for the benefit of an analysis of the determinants of financial fragility, our interest in this article is set only on the construction of financial fragility indicators. We believe that, before advancing in an empirical analysis of the determinants, we need to build consistent indicators of financial fragility.
14 Schroeder (Citation2009) used a simple cash-flow accounting framework to analyze financial fragility in New Zealand (as a unit) from 1990 to 2007. Her empirical exercise is based on the cash-flow equation proposed by Foley (Citation2003) in a model explaining the analytics of financial fragility: Profit + Borrowing = Investment + Debt Service.
15 The introduction of dividend payments is an innovation.
16 This behavior is due to mergers and acquisitions, and the lack of data, which nonetheless does not hamper the results in the sample as it refers to very small firms in specific years.
17 Eletrobrás controls the following firms: CEAL, CELG, CEPISA, CEA, CERON, ELETROACRE, and AMAZONAS.
