Here you will find three job market papers. The first and second ones I developed in my Ph.D. Thesis.
SHIFTING PERSPECTIVES: LOOKING AT THE LABOR SIDE IN A HICKS-SRAFFA SUPERMULTIPLIER
(with Professor Joanilio Rodolpho Teixeira, Ph.D.)
The central objective of this paper is to introduce the wage elasticity of labor demand into the Hicks-Sraffa Supermultiplier (HSSM). It is a well-known fact that some technological advancement excludes part of the workforce of the market, especially the less qualified ones, restricting the demand for workers, which makes it impossible for all economies to ensure full employment (sometimes even in the long-run). However, it is not restricted to less skilled. The development of Artificial Intelligence created the possibility of a computer performing small surgeries without any assistance from a human doctor. Unfortunately, the post-Keynesian tradition usually does not give proper attention to this market, only assuming that, in a long-run perspective, employment automatically adjusts to the capital. Thus, here, we expand the HSSM incorporating the wage elasticity of labor demand and the average salary growth rate to determine how such a mechanism influences the dynamics of this type of model. Then, we attest their stable conditions and estimate a numerical simulation to measure the computational support of our theoretical results.
A THEORETICAL NOTE ON THE SUPERMULTIPLIER APPROACH IN A LABOR CONSTRAINED ECONOMY
(with Professor Jorge Thompson Araujo, Ph.D., the early version published as UnB Working Paper can be read here)
This note discusses a potential inconsistency in the treatment of the supply side under the supermultiplier approach. More specifically, it shows that, in the case where labor is the restricting factor of production, the accelerator mechanism does not provide a satisfactory framework with which to analyze investment behavior, as it drives the economy towards over-accumulation of capital – a form of dynamic inefficiency. Although countervailing effects are considered, including exogenous labor-augmenting technological progress, they are not sufficient to fully offset tendencies towards excessive capital accumulation. The note also stresses that long-period output will not be purely demand-driven in a supermultiplier-type model when labor is the binding constraint under a Leontief technology. Instead, it will be determined through the interplay of aggregate supply and demand. The above findings imply that the usual results of supermultipliertype models are highly dependent on the conventional assumption that capital is the restricting factor.
AN ANALYTICAL ECONOMIC DYNAMIC MODEL CONSIDERING UNEMPLOYMENT AND INCORPORATING SIR’S APPROACH
(link - with Geraldo Sandoval Góes, Ph.D. and Professor Joanilio Rodolpho Teixeira)
The present paper has the objective to develop three new approaches. In the first one, we design a new model where capacity utilization is defined by the difference between population (represented by the sum of activity and unemployed labor force), and capital stock growth rates. Second, we spread unemployment into the natural one and the other caused by external reasons. Third, we incorporate the SIR’s (Susceptible, Infectious, or Recovered) approach into the second framework to understand how Pandemics can affect economic behavior. Then, we proved the stable condition of all three cases and also consider a numerical simulation to ensure their economic efficiency. As a result, the first model acts exactly like a post-Keynesian (neo-Kaleckian) expects it to behave (in the short and medium runs it is possible to assume unemployment, but in a long-period full employment is arrived). Despite the convergence of capacity utilization to its normal level, it seems that, in the second case, we will have a time lag of involuntary unemployment. In the third case, when the epidemiological model is considered (if, and only if, the Pandemic is the only reason for unemployment caused by external motives), the model will converge to full employment of factors like in the first case.