Ingrid Cecilia VARGAS YAÑEZ

Job market paper

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“Does network heterogeneity enhance consumption inequality?, working paper, 2020

I study the implications of network connectedness for aggregated economic inequality when connectedness is the only source of heterogeneity. The analysis is carried out using a static general equilibrium model with a production sector that uses labor as its sole input. In this model, individuals perceive utility from leisure and have homogeneous relative concerns preferences for good consumption. Networks are considered exogenous and simulated using a preferential attachment algorithm.  Using Gini indices to measure inequality and eigenvector centrality for network connectedness, a significant link between network heterogeneity and inequality is found. Model extensions with heterogeneous responses in relative concerns and the inclusion of an additional source of inequality are also studied. I find that partially shutting down any of the relative concern responses does not reduce inequality. Moreover, reverberations due to neighborhood size effects and leisure preference levels originate non-monotonicities when externality size increases. Finally, for the same endowment, the inclusion of different sources of wealth heterogeneity leads to equivalent levels of economic outcomes, all with increased inequality.

 

Other Papers

 

“Estimating network formation parameters from sampled data, a simulation exercise”, working paper, 2020

I study numerically the extension of a random network formation model to a setting under incomplete information. The setting studied deals specifically with large (vertices number growing to infinity) and sparse (network density tending to zero for increasing vertices number) networks. I perform simulations that address three questions. First, what is the impact of using an estimator from sampled data for the parameters of the network formation model. Second, how the inclusion of isolates impacts estimation performance. Finally, I analyze how the network size affects the performance of the two estimation process mentioned.

 

“Time-use poverty, an econometric approach”, with Prof. Jaya Krishnakumar, working paper, 2020

We consider the lifestyle of an individual in terms of the activities that the individual engages in during the course of a day and the time allotted to each of them. Using this information we construct a measure of value attached to that lifestyle along the lines of the Capability Approach by Amartya Sen which defines well-being in terms of the freedom to do things that one has reason to value. We perform an empirical analysis using this framework and time-use information from the United Kingdom for 2000, 2005, and 2015. Results show that time-use poor do more employment and household care and have less personal care time compared to non-time-use poor.

 

“Increasing transparency when assessing the impact of technology on human well-being: a capability approach perspective”, International Journal of Technoethics, 2021 (available here)

We argue that the impact of technological artifacts on well-being is inconsistently assessed since evaluation criteria are conditioned by the definition of technology, the taken moral perspective, and the heterogeneity of interests at stake. We propose an analytical framework that structures this evaluation process with a modified capability approach using Nussbaum’s list of central capabilities and including the five moral principles put forward by Peterson for the ethical evaluation of technology. We provide an illustration of our framework applied to car use.