In this paper we analyze Minskian dynamics in the US economy via an empirical application of Minsky's financing regime classifications to a panel of nonfinancial corporations. First, we map Minsky's definitions of hedge, speculative and Ponzi finance onto firm-level data to describe the evolution of Minskian regimes. We highlight striking growth in the share of Ponzi firms in the post-1970 US, concentrated among small corporations. This secular growth in the incidence of Ponzi firms is consistent with the possibility of a long wave of increasingly fragile finance in the US economy. Second, we explore the possibility of short-run Minskian dynamics at a business-cycle frequency. Using linear probability models relating firms' probability of being Ponzi to the aggregate output gap, which captures short-term macroeconomic fluctuations exogenous to individual firms, we find that aggregate downturns are correlated with an almost zero increased probability that firms are Ponzi. This result is corroborated by quantile regressions using a continuous measure of financial fragility, the interest coverage ratio, which identify almost zero e↵ects of short-term fluctuations on financial fragility across the interest coverage distribution. Together, these results speak to an important question in the theoretical literature on financial fragility regarding the duration of Minskian cycles, and lend support, in particular, to the contention that Minskian dynamics may take the form of long waves, but do not operate at business cycle frequencies.

This paper uses panel cointegration and error correction models to unveil the direction of long-run causality between the real product wage and labor productivity at the industry level. I use two datasets of manufacturing industries: the EU-Klems dataset covering 11 industries in 19 developed economies, and the Unido Industrial Statistics Database covering 22 industries in 30 developed and developing economies. In both datasets, I find evidence of cointegration between the two variables, as well as evidence of two-way, long-run Granger causality. These findings are consistent with theories of directed technical change, which claim that a rise in labor costs sparks the adoption of labor-saving innovations. They are also consistent with distributive theories whereby real wages keep apace of labor productivity growth, giving rise to long-run stability in functional distribution.

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This paper presents a two-sector growth model in which industrial accumulation is sensitive to the factor-saving bias of technical change in agriculture. Agriculture features low factor substitutability and hidden unemployment and, in the baseline scenario, industrial growth is constrained by aggregate demand. Land-saving innovations are then shown to raise rural employment, enlarge the domestic market for manufactures, and bolster industrial accumulation, in contrast to labor-saving innovations. The baseline model and its extensions illuminate recent empirical studies which

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