Pascuel Plotkin

phone 778-513-9776
launchTwitter
Education

The University of British Columbia, PhD in Economics, 2019-2025 (expected)
Universidad de San Andres, Masters in Economics, 2016-2017
Universidad de Buenos Aires, Bachelor in Economics, 2010-2015


About

Research areas: Labor Economics, Development Economics, Applied Econometrics, Public Economics

I am an applied economist with interests in Labour Economics, Development Economics, and Applied Econometrics. Much of my research examines how alternative work arrangements affect inequality, workers and firms.

In my job market paper, I use data from a large online-delivery platform which I link to administrative employer-employee data to study the direct and indirect effects of delivery platforms on restaurant workers, gig workers and firms.

My expected graduation date is 2025. I will be available for interviews in the 2024-2025 job market.


Research

Dinner at Your Door: How Delivery Platforms Affect Workers and Firms (Job Market Paper)

Abstract: Online-delivery platforms are part of a recent wave of technologies that reshape workforce composition and demand for goods. While these platforms can provide new opportunities for workers with limited outside options, they may also replace “good jobs”. This paper uses unique data linking employer-employee records with restaurants and workers from a major Brazilian delivery platform, along with a matched event-study design, to estimate the impact of platform adoption on labor market outcomes. Adopting restaurants, on average, replace waiters with outsourced platform workers one-to-one. Workers at adopting restaurants experience modest earnings losses, as most displaced employees find new formal sector jobs. In contrast, non-adopting restaurants tend to downsize or shut down, with their workers facing greater earnings losses due to increased displacement risks. However, the earnings gains for gig workers outweigh the losses faced by restaurant employees. These findings offer insights into the distributional effects and trade-offs of online-delivery platforms.

Working Papers:

The Consequences of Domestic Outsourcing on Workers: New Evidence from Italian Administrative Data, Co-Authors: Diego Daruich, Martino Kuntze and Raffaele Saggio

Abstract: We exploit a novel identifier of outsourcing events present in Italian administrative data. This information permits us to estimate the effects of outsourcing across a wide set of occupations without restricting the analysis to workers who remain employed after being outsourced. We find that outsourcing leads to substantial earnings losses, primarily driven by the extensive margin—a margin not fully analyzed by previous research—as several outsourced workers become non-employed shortly after joining the contracting firms. Outsourced workers in non-routine manual jobs have the largest earnings losses, while those in jobs involving abstract, cognitive tasks experience some earnings gains following the outsourcing event. Our evidence is consistent with some Italian firms using outsourcing to bypass the country’s strict employment protection legislation.

Work in progress:

Labor Supply of the Gig Economy: Evidence From the Online-Delivery Industry in Brazil, Co-Authors: Nina Roussille (MIT), Gabriel Ulyssea (UCL)

Abstract: This project investigates in detail the labor supply of gig workers and the role of information frictions in shaping labor supply of these workers in Brazil. For that, we combine administrative data from the largest food delivery platform in Latin America, with primary survey data from a sample of riders in the platform. Previous studies on labor supply have assumed that workers have a full knowledge of the wage distribution and form expectations rationally. Yet in the context of gig employment where earnings present a high volatility, it is possible that workers form inaccurate expectations. In this project we overcome this constraint by surveying a sample of platform workers to elicit their reservation wages and expected wages. We first document the error in workers beliefs, contrasting survey data and administrative records. We then move on to an experimental research design where we expose workers to unbiased information on expected wages and study how they update their beliefs and behavior on the platform. By linking the experimental research design with platforms administrative records and employer-employee data, we study how unbiased information can potentially modify labor supply decisions and adjust labor allocation in a more efficient way – as measured by the surplus generated between the actual earnings in the platform and workers reservation wages.

Does it Matter Where and What I Study? Evidence from the Oil Price Crash in Canada, Co-Authors: Constanza Abuin (Harvard)

Abstract: We estimate the impact of a labour demand shock on Canadian recently graduated bachelor students. We leverage a unique Canadian administrative data that features links between individuals post-secondary education and their tax-files. We estimate that a standard deviation increase in school-major specific labour demand, increased earnings immediately in a magnitude between 2.3 and 2.6 log points, with persistent and increasing effects throughout the oil shock. Additionally, the labour demand shock had effects on other labour market outcomes such as unemployment or self-employment. In terms of schooling, school-major specific labour demand had a positive effect on dropouts, which remarks the importance of considering the outside option of students when studying school enrollment.

Disempowered Unions, Collective Bargaining, and Wage Inequality, Co-Authors: Carla Srebot (UBC)

Abstract: We study the effects of deunionization–characterized by the weakening of labor unions–on firm compensation, labor inequality, and earning gaps. Specifically, we leverage a reform in Brazil that ended the automatic renewal of collective bargaining agreements (CBAs) upon their expiration, significantly curtailing the bargaining power of unions over wages and job amenities. Using a dataset on the universe of CBAs alongside an administrative linked employer-employee dataset, we estimate the causal effect of deunionization. Our approach compares firms with expired CBAs, where workers are no longer covered by a CBA, to those with active CBAs at the time of the reform’s implementation. We extend our analysis to explore the mechanisms through which deunionization affects wage and amenity distributions, applying textual analysis to the CBAs to explain changes in employee welfare. Additionally, the analysis examines the heterogeneity in the reform’s effects across different industries, occupations, and worker skill levels, aiming to uncover whether the reform widened inequality in earnings and employment amenities.

Algorithmic v.s. Human Bias in Hiring, Co-Authors: Sam Gyetvay (OSU), Choenden Kyirong

Abstract: We investigate the potential impact of the diffusion of large language models on hiring discrimination by comparing the biases in AI-driven and human-driven resume screening. To do so, we reanalyze data from previous field experiments by reconstructing resumes and comparing human call-back rates with LLM-generated results. We find that LLMs exhibit significantly less racial bias than human decision-makers. However, LLMs are not perfectly unbiased. In a more stringent test, we fail to reject the null hypothesis that LLMs do not use information contained in names.


Publications

Paying outsourced labor: Direct evidence from linked temp agency-worker-client data

Co-Authors: Andres Drenik (UT Austin), Simon Jäger (MIT) and Benjamin Schoefer (Berkeley)

Abstract: We estimate how much firms differentiate pay premia between regular and outsourced workers in temp agency work arrangements. We leverage unique Argentinian administrative data that feature links between user firms (the workplaces where temp workers perform their labor) and temp agencies (their formal employers). We estimate that a high-wage user firm that pays a regular worker a 10% premium pays a temp worker on average only a 4.9% premium, compared to what these workers would earn in a low-wage user firm in their respective work arrangements. This 49% pass-through constitutes the midpoint between the benchmarks for insiders (one) and the competitive spot-labor market (zero).

 


Awards

  • JPAL JOI Brazil Pilot Grant (with Gabriel Ulyssea and Nina Roussille)
  • CIDER Small Grants

Teaching

  • Cost Benefit Analysis & Project Evaluation (UBC)
  • Economics of technological Change (UBC)
  • Economics Analysis of Law (UBC)
  • Economics of the Environment (UBC)
  • Principles of Macroeconomics (UBC)
  • Microeconomics I (Universidad de Buenos Aires)
  • Statistics II (Universidad de Buenos Aires)

Pascuel Plotkin

phone 778-513-9776
launchTwitter
Education

The University of British Columbia, PhD in Economics, 2019-2025 (expected)
Universidad de San Andres, Masters in Economics, 2016-2017
Universidad de Buenos Aires, Bachelor in Economics, 2010-2015


About

Research areas: Labor Economics, Development Economics, Applied Econometrics, Public Economics

I am an applied economist with interests in Labour Economics, Development Economics, and Applied Econometrics. Much of my research examines how alternative work arrangements affect inequality, workers and firms.

In my job market paper, I use data from a large online-delivery platform which I link to administrative employer-employee data to study the direct and indirect effects of delivery platforms on restaurant workers, gig workers and firms.

My expected graduation date is 2025. I will be available for interviews in the 2024-2025 job market.


Research

Dinner at Your Door: How Delivery Platforms Affect Workers and Firms (Job Market Paper)

Abstract: Online-delivery platforms are part of a recent wave of technologies that reshape workforce composition and demand for goods. While these platforms can provide new opportunities for workers with limited outside options, they may also replace “good jobs”. This paper uses unique data linking employer-employee records with restaurants and workers from a major Brazilian delivery platform, along with a matched event-study design, to estimate the impact of platform adoption on labor market outcomes. Adopting restaurants, on average, replace waiters with outsourced platform workers one-to-one. Workers at adopting restaurants experience modest earnings losses, as most displaced employees find new formal sector jobs. In contrast, non-adopting restaurants tend to downsize or shut down, with their workers facing greater earnings losses due to increased displacement risks. However, the earnings gains for gig workers outweigh the losses faced by restaurant employees. These findings offer insights into the distributional effects and trade-offs of online-delivery platforms.

Working Papers:

The Consequences of Domestic Outsourcing on Workers: New Evidence from Italian Administrative Data, Co-Authors: Diego Daruich, Martino Kuntze and Raffaele Saggio

Abstract: We exploit a novel identifier of outsourcing events present in Italian administrative data. This information permits us to estimate the effects of outsourcing across a wide set of occupations without restricting the analysis to workers who remain employed after being outsourced. We find that outsourcing leads to substantial earnings losses, primarily driven by the extensive margin—a margin not fully analyzed by previous research—as several outsourced workers become non-employed shortly after joining the contracting firms. Outsourced workers in non-routine manual jobs have the largest earnings losses, while those in jobs involving abstract, cognitive tasks experience some earnings gains following the outsourcing event. Our evidence is consistent with some Italian firms using outsourcing to bypass the country’s strict employment protection legislation.

Work in progress:

Labor Supply of the Gig Economy: Evidence From the Online-Delivery Industry in Brazil, Co-Authors: Nina Roussille (MIT), Gabriel Ulyssea (UCL)

Abstract: This project investigates in detail the labor supply of gig workers and the role of information frictions in shaping labor supply of these workers in Brazil. For that, we combine administrative data from the largest food delivery platform in Latin America, with primary survey data from a sample of riders in the platform. Previous studies on labor supply have assumed that workers have a full knowledge of the wage distribution and form expectations rationally. Yet in the context of gig employment where earnings present a high volatility, it is possible that workers form inaccurate expectations. In this project we overcome this constraint by surveying a sample of platform workers to elicit their reservation wages and expected wages. We first document the error in workers beliefs, contrasting survey data and administrative records. We then move on to an experimental research design where we expose workers to unbiased information on expected wages and study how they update their beliefs and behavior on the platform. By linking the experimental research design with platforms administrative records and employer-employee data, we study how unbiased information can potentially modify labor supply decisions and adjust labor allocation in a more efficient way – as measured by the surplus generated between the actual earnings in the platform and workers reservation wages.

Does it Matter Where and What I Study? Evidence from the Oil Price Crash in Canada, Co-Authors: Constanza Abuin (Harvard)

Abstract: We estimate the impact of a labour demand shock on Canadian recently graduated bachelor students. We leverage a unique Canadian administrative data that features links between individuals post-secondary education and their tax-files. We estimate that a standard deviation increase in school-major specific labour demand, increased earnings immediately in a magnitude between 2.3 and 2.6 log points, with persistent and increasing effects throughout the oil shock. Additionally, the labour demand shock had effects on other labour market outcomes such as unemployment or self-employment. In terms of schooling, school-major specific labour demand had a positive effect on dropouts, which remarks the importance of considering the outside option of students when studying school enrollment.

Disempowered Unions, Collective Bargaining, and Wage Inequality, Co-Authors: Carla Srebot (UBC)

Abstract: We study the effects of deunionization–characterized by the weakening of labor unions–on firm compensation, labor inequality, and earning gaps. Specifically, we leverage a reform in Brazil that ended the automatic renewal of collective bargaining agreements (CBAs) upon their expiration, significantly curtailing the bargaining power of unions over wages and job amenities. Using a dataset on the universe of CBAs alongside an administrative linked employer-employee dataset, we estimate the causal effect of deunionization. Our approach compares firms with expired CBAs, where workers are no longer covered by a CBA, to those with active CBAs at the time of the reform’s implementation. We extend our analysis to explore the mechanisms through which deunionization affects wage and amenity distributions, applying textual analysis to the CBAs to explain changes in employee welfare. Additionally, the analysis examines the heterogeneity in the reform’s effects across different industries, occupations, and worker skill levels, aiming to uncover whether the reform widened inequality in earnings and employment amenities.

Algorithmic v.s. Human Bias in Hiring, Co-Authors: Sam Gyetvay (OSU), Choenden Kyirong

Abstract: We investigate the potential impact of the diffusion of large language models on hiring discrimination by comparing the biases in AI-driven and human-driven resume screening. To do so, we reanalyze data from previous field experiments by reconstructing resumes and comparing human call-back rates with LLM-generated results. We find that LLMs exhibit significantly less racial bias than human decision-makers. However, LLMs are not perfectly unbiased. In a more stringent test, we fail to reject the null hypothesis that LLMs do not use information contained in names.


Publications

Paying outsourced labor: Direct evidence from linked temp agency-worker-client data

Co-Authors: Andres Drenik (UT Austin), Simon Jäger (MIT) and Benjamin Schoefer (Berkeley)

Abstract: We estimate how much firms differentiate pay premia between regular and outsourced workers in temp agency work arrangements. We leverage unique Argentinian administrative data that feature links between user firms (the workplaces where temp workers perform their labor) and temp agencies (their formal employers). We estimate that a high-wage user firm that pays a regular worker a 10% premium pays a temp worker on average only a 4.9% premium, compared to what these workers would earn in a low-wage user firm in their respective work arrangements. This 49% pass-through constitutes the midpoint between the benchmarks for insiders (one) and the competitive spot-labor market (zero).

 


Awards

  • JPAL JOI Brazil Pilot Grant (with Gabriel Ulyssea and Nina Roussille)
  • CIDER Small Grants

Teaching

  • Cost Benefit Analysis & Project Evaluation (UBC)
  • Economics of technological Change (UBC)
  • Economics Analysis of Law (UBC)
  • Economics of the Environment (UBC)
  • Principles of Macroeconomics (UBC)
  • Microeconomics I (Universidad de Buenos Aires)
  • Statistics II (Universidad de Buenos Aires)

Pascuel Plotkin

phone 778-513-9776
launchTwitter
Education

The University of British Columbia, PhD in Economics, 2019-2025 (expected)
Universidad de San Andres, Masters in Economics, 2016-2017
Universidad de Buenos Aires, Bachelor in Economics, 2010-2015

About keyboard_arrow_down

Research areas: Labor Economics, Development Economics, Applied Econometrics, Public Economics

I am an applied economist with interests in Labour Economics, Development Economics, and Applied Econometrics. Much of my research examines how alternative work arrangements affect inequality, workers and firms.

In my job market paper, I use data from a large online-delivery platform which I link to administrative employer-employee data to study the direct and indirect effects of delivery platforms on restaurant workers, gig workers and firms.

My expected graduation date is 2025. I will be available for interviews in the 2024-2025 job market.

Research keyboard_arrow_down

Dinner at Your Door: How Delivery Platforms Affect Workers and Firms (Job Market Paper)

Abstract: Online-delivery platforms are part of a recent wave of technologies that reshape workforce composition and demand for goods. While these platforms can provide new opportunities for workers with limited outside options, they may also replace “good jobs”. This paper uses unique data linking employer-employee records with restaurants and workers from a major Brazilian delivery platform, along with a matched event-study design, to estimate the impact of platform adoption on labor market outcomes. Adopting restaurants, on average, replace waiters with outsourced platform workers one-to-one. Workers at adopting restaurants experience modest earnings losses, as most displaced employees find new formal sector jobs. In contrast, non-adopting restaurants tend to downsize or shut down, with their workers facing greater earnings losses due to increased displacement risks. However, the earnings gains for gig workers outweigh the losses faced by restaurant employees. These findings offer insights into the distributional effects and trade-offs of online-delivery platforms.

Working Papers:

The Consequences of Domestic Outsourcing on Workers: New Evidence from Italian Administrative Data, Co-Authors: Diego Daruich, Martino Kuntze and Raffaele Saggio

Abstract: We exploit a novel identifier of outsourcing events present in Italian administrative data. This information permits us to estimate the effects of outsourcing across a wide set of occupations without restricting the analysis to workers who remain employed after being outsourced. We find that outsourcing leads to substantial earnings losses, primarily driven by the extensive margin—a margin not fully analyzed by previous research—as several outsourced workers become non-employed shortly after joining the contracting firms. Outsourced workers in non-routine manual jobs have the largest earnings losses, while those in jobs involving abstract, cognitive tasks experience some earnings gains following the outsourcing event. Our evidence is consistent with some Italian firms using outsourcing to bypass the country’s strict employment protection legislation.

Work in progress:

Labor Supply of the Gig Economy: Evidence From the Online-Delivery Industry in Brazil, Co-Authors: Nina Roussille (MIT), Gabriel Ulyssea (UCL)

Abstract: This project investigates in detail the labor supply of gig workers and the role of information frictions in shaping labor supply of these workers in Brazil. For that, we combine administrative data from the largest food delivery platform in Latin America, with primary survey data from a sample of riders in the platform. Previous studies on labor supply have assumed that workers have a full knowledge of the wage distribution and form expectations rationally. Yet in the context of gig employment where earnings present a high volatility, it is possible that workers form inaccurate expectations. In this project we overcome this constraint by surveying a sample of platform workers to elicit their reservation wages and expected wages. We first document the error in workers beliefs, contrasting survey data and administrative records. We then move on to an experimental research design where we expose workers to unbiased information on expected wages and study how they update their beliefs and behavior on the platform. By linking the experimental research design with platforms administrative records and employer-employee data, we study how unbiased information can potentially modify labor supply decisions and adjust labor allocation in a more efficient way – as measured by the surplus generated between the actual earnings in the platform and workers reservation wages.

Does it Matter Where and What I Study? Evidence from the Oil Price Crash in Canada, Co-Authors: Constanza Abuin (Harvard)

Abstract: We estimate the impact of a labour demand shock on Canadian recently graduated bachelor students. We leverage a unique Canadian administrative data that features links between individuals post-secondary education and their tax-files. We estimate that a standard deviation increase in school-major specific labour demand, increased earnings immediately in a magnitude between 2.3 and 2.6 log points, with persistent and increasing effects throughout the oil shock. Additionally, the labour demand shock had effects on other labour market outcomes such as unemployment or self-employment. In terms of schooling, school-major specific labour demand had a positive effect on dropouts, which remarks the importance of considering the outside option of students when studying school enrollment.

Disempowered Unions, Collective Bargaining, and Wage Inequality, Co-Authors: Carla Srebot (UBC)

Abstract: We study the effects of deunionization–characterized by the weakening of labor unions–on firm compensation, labor inequality, and earning gaps. Specifically, we leverage a reform in Brazil that ended the automatic renewal of collective bargaining agreements (CBAs) upon their expiration, significantly curtailing the bargaining power of unions over wages and job amenities. Using a dataset on the universe of CBAs alongside an administrative linked employer-employee dataset, we estimate the causal effect of deunionization. Our approach compares firms with expired CBAs, where workers are no longer covered by a CBA, to those with active CBAs at the time of the reform’s implementation. We extend our analysis to explore the mechanisms through which deunionization affects wage and amenity distributions, applying textual analysis to the CBAs to explain changes in employee welfare. Additionally, the analysis examines the heterogeneity in the reform’s effects across different industries, occupations, and worker skill levels, aiming to uncover whether the reform widened inequality in earnings and employment amenities.

Algorithmic v.s. Human Bias in Hiring, Co-Authors: Sam Gyetvay (OSU), Choenden Kyirong

Abstract: We investigate the potential impact of the diffusion of large language models on hiring discrimination by comparing the biases in AI-driven and human-driven resume screening. To do so, we reanalyze data from previous field experiments by reconstructing resumes and comparing human call-back rates with LLM-generated results. We find that LLMs exhibit significantly less racial bias than human decision-makers. However, LLMs are not perfectly unbiased. In a more stringent test, we fail to reject the null hypothesis that LLMs do not use information contained in names.

Publications keyboard_arrow_down

Paying outsourced labor: Direct evidence from linked temp agency-worker-client data

Co-Authors: Andres Drenik (UT Austin), Simon Jäger (MIT) and Benjamin Schoefer (Berkeley)

Abstract: We estimate how much firms differentiate pay premia between regular and outsourced workers in temp agency work arrangements. We leverage unique Argentinian administrative data that feature links between user firms (the workplaces where temp workers perform their labor) and temp agencies (their formal employers). We estimate that a high-wage user firm that pays a regular worker a 10% premium pays a temp worker on average only a 4.9% premium, compared to what these workers would earn in a low-wage user firm in their respective work arrangements. This 49% pass-through constitutes the midpoint between the benchmarks for insiders (one) and the competitive spot-labor market (zero).

 

Awards keyboard_arrow_down
  • JPAL JOI Brazil Pilot Grant (with Gabriel Ulyssea and Nina Roussille)
  • CIDER Small Grants
Teaching keyboard_arrow_down
  • Cost Benefit Analysis & Project Evaluation (UBC)
  • Economics of technological Change (UBC)
  • Economics Analysis of Law (UBC)
  • Economics of the Environment (UBC)
  • Principles of Macroeconomics (UBC)
  • Microeconomics I (Universidad de Buenos Aires)
  • Statistics II (Universidad de Buenos Aires)