Historical Patterns of Inequality and Productivity around Financial Crises

Abstract

To understand the determinants of financial crises, previous research focused on developments closely related to financial markets. In contrast, this paper considers changes originating in the real economy as drivers of financial instability. To this end, I assemble a novel data set of long-run measures of income inequality, productivity, and other macrofinancial indicators for advanced economies. I find that rising top income inequality and low productivity growth are robust predictors of crises, and their slowmoving trend components largely explain these relations. Moreover, recessions that are preceded by such developments are deeper than recessions without such ex-ante trends.

Income Inequality, Financial Crises, and Monetary Policy

“…Finally, column (3) reports that once we control for income inequality, the credit variable loses its predictive power. These are the stylized facts emphasized by Paul (2017) and our model can replicates them quite well. In particular, the marginal effects of credit and income inequality shown in squared brackets are quite comparable to those reported in his study.…”

“…27 Figure 5 shows how the exact shapes of the 25 The linear relationship also justifies the reduced form approach that assumes a (log) linear relationship between the excess credit and the probability of disaster without structural modeling, an approach recently taken by Gourio et al (2018). In Appendix D, using our simulated data, we replicate the results of Paul (2017) that income inequality dominates credit in the predictive power of financial crises.…”

“…The following table shows the estimation results using our simulation data. As in Paul (2017), the credit variable predicts financial crises in our simulated economy as reported in column (1). However, column (2) shows that the share of shareholders predicts financial crises as well.…”

“…(C.42) ∆ t = π γ t [(1 − ϕ)p −γ 0,t + ϕπ −vγ t−1 ], (C.43) n t = (1 − ρ)n t−1 + q(θ t )v t , (C.44) D Additional Results D.1 Replication of Paul (2017) In what sense can the moments shown in Table 3 can be considered representative of reality? To answer this question, we replicate the empirical exercise of Paul (2017): we test the predictive power of credit in forecasting the probability of financial crises, with and without controlling for income inequality using our simulated data. Specifically, we replicate Paul (2017)'s early warning signal model using the binary data of crisis indicator during our stochastic simulation.…”

A Macroeconomic Model with Occasional Financial Crises

“…The model therefore distinguishes between outstanding and newly issued loans. Jordà et al, 2017) and various productivity measures (Source: Bergeaud et al, 2016, andPaul, 2017, for additional calculations) around financial crises (year zero denotes start of a crisis based on the dates in Jordà et al, 2017). Median, 33 rd , and 66 th percentiles are shown.…”