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Wage Inequalities under Real Competition

Wage Inequalities under Real Competition published on No Comments on Wage Inequalities under Real Competition

Mokre Patrick (2021): The Quantile Impacts of Real Competition on Industrial Wage Inequality in the United States, 1998-2018. Accepted at the Eastern Economics Association 2023 Meeting, Eastern Economics Association.

Wages are set in bargaining between workers and capitalists, with wage increases rather than levels the bargaining subject. The ability and willingness of firms to increase wages co-determines the bargaining outcomes. Both are subject to the competition of firms between and within industries. The literature on real competition and wage inequality (Botwinick 1993; Shaikh 2020; Mokre and Rehm 2020) poses (1) that this links profit rates and wage growth, (2) both behave as turbulent processes, and (3) the dynamics contain both determinate and stochastic components. In this paper, we attempt to explain the wage distribution and wage inequality as an outcome of turbulent wage growth dynamics.

We present a multi-sector model of turbulent wage growth and persistent wage inequality. In real
competition, when a sector realizes above-average profit rates on new capital and this induces accelerating investment streams. Increased labor demand as well as higher profit rates shift the limits to wage growth. The subsequent fall below the average in later periods, which is characteristic for turbulent equalization, also translates into reversed wage dynamics. In the model, we distinguish between direct labor mobility (coaxing) and indirect mobility (recruitment from unemployment). Finally, we formalize a wage growth model in stochastic differential equation form of a Cox, Ingersoll, and Ross (1985) – style drift – diffusion process, and derive analytically the corresponding cross – sectional distribution parameters (Fischer 2018).

We also present a novel Bayesian approach to estimate the parametersof drift-diffusion equations as
well as the corresponding wage distribution. When we apply the model to US wage growth data (1998 –
2018), the estimation explains about 93 % of the wage distribution below the top percentile, and 86 %
of total sample inequality.

On Top of the Top – Adjusting wealth distributions using national rich lists

On Top of the Top – Adjusting wealth distributions using national rich lists published on

Disslbacher Franziska, Ertl Michael, List Emanuel, Mokre Patrick and Schnetzer Matthias (2021): On Top of the Top – Adjusting wealth distributions using national rich lists. INEQ Working Paper Series, 20. WU Vienna University of Economics and Business, Vienna.

Poor coverage of the top in wealth surveys conceals the extent of wealth inequality. The literature mitigates this shortcoming by enriching survey data with rich lists and estimating the top tail with a Pareto distribution. However, recent studies rely on ad-hoc assumptions for some of the required parameters. We suggest a unified regression approach to estimate all parameters of a Pareto distribution jointly and extend our analysis with a more flexible three-parameter Generalized Pareto estimation. We introduce a new database of national rich lists (ERLDB) as an alternative to commonly used global rich lists to combine with survey data from the Household Finance and Consumption Survey (HFCS 2017). Our findings for 14 European countries show that wealth is more concentrated than surveys suggest, with almost doubling Top 1% shares in the most extreme cases. In contrast, countries with successful oversampling strategies tend to experience only minor changes in inequality metrics.

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