nep-ltv New Economics Papers
on Unemployment, Inequality and Poverty
Issue of 2019‒01‒14
four papers chosen by
Maximo Rossi
Universidad de la República

  1. The Impact of a Conditional Cash Transfer Program on Households' Well-Being By Daniela Del Boca; Chiara Pronzato; Giuseppe Sorrenti
  2. Racial Bias and In-group Bias in Judicial Decisions: Evidence from Virtual Reality Courtrooms By Samantha Bielen; Wim Marneffe; Naci H. Mocan
  3. Do Workers Value Flexible Jobs? A Field Experiment on Compensating Differentials By Haoran He; David Neumark; Qian Weng
  4. Understanding Trends in Alternative Work Arrangements in the United States By Lawrence F. Katz; Alan B. Krueger

  1. By: Daniela Del Boca (University of Turin and Collegio Carlo Alberto); Chiara Pronzato (University of Turin, CHILD and Collegio Carlo Alberto); Giuseppe Sorrenti (University of Zurich)
    Abstract: We evaluate the impact of a conditional cash transfer (CCT) program that we designed on family well-being among low-income families with young children. Although most CCTs have been implemented in low-income countries, our research is in the context of a high-income country, Italy, where the recent economic crises have worsened the conditions of families with children, especially among immigrants. Our objective is to evaluate the introduction of conditionality (attendance of courses) into a pre-existing unconditional cash transfer program. Using a randomized controlled trial, we find that CCT families search more actively for work, and they work more hours and more regularity than the cash transfer and control groups. CCT families also are able to save more money and eat healthier foods. The CCT intervention appears to be more effective than cash transfer alone in changing households' behavior in several dimensions of well-being. Our findings add to the accumulating evidence on the impact of conditional cash transfers versus unconditional ones and to the literature concerning multidimensional incentive programs.
    Keywords: conditional cash transfers, poverty, use of money, Labor Supply, parenting
    JEL: I10 I20 J24 I31
    Date: 2018–12
    URL: http://d.repec.org/n?u=RePEc:hka:wpaper:2018-093&r=all
  2. By: Samantha Bielen; Wim Marneffe; Naci H. Mocan
    Abstract: We shot videos of criminal trials using 3D Virtual Reality (VR) technology, prosecuted by actual prosecutors and defended by actual defense attorneys in an actual courtroom. This is the first paper that utilizes VR technology in a non-computer animated setting, which allows us to replace white defendants in the courtroom with individuals who have Middle Eastern or North African descent in a real-life environment. We alter only the race of the defendants in these trials, holding all activity in the courtroom constant (http://proficient.ninja/splitscreen/). Law students, economics students and practicing lawyers are randomly assigned to watch with VR headsets, from the view point of the judge, the trials that differed only in defendants’ skin color. Background information obtained from the evaluators allowed us to identify their cultural heritage. Evaluators made decisions on guilt/innocence in these burglary and assault cases, as well as prison sentence length and fine in accordance with the guidelines provided by the relevant law. There is suggestive evidence of negative in-group bias in conviction decisions where evaluators are harsher against defendants of their own race. There is, however, significant overall racial bias in conviction decisions against minorities. In the sentencing phase, we find in-group favoritism in prison times and fines, driven by white evaluators. This translates into overall racial bias against minority defendants in prison sentences and fines. We find only scant evidence that the concerns of the evaluators about terrorism, about immigration, or their trust in the judiciary or the police have an impact on their judicial decisions, suggesting that the source of the bias may be deep-rooted. Merging a small sample of judges and prosecutors with the sample of lawyers provides very similar results as those obtained from the analysis of lawyers.
    JEL: K4 Z1
    Date: 2018–12
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25355&r=all
  3. By: Haoran He; David Neumark; Qian Weng
    Abstract: We explore compensating differentials for job flexibility, using a field experiment conducted on a Chinese job board. Our job ads differ randomly regarding when one works (time flexibility) and where one works (place flexibility). We find strong evidence that workers value job flexibility – especially regarding place of work. Application rates are higher to flexible jobs, conditional on the salary offered. Additional survey evidence indicates that workers are willing to take lower pay for more flexible jobs. Non-experimental job board data do not indicate that workers value job flexibility, reinforcing the difficulty of estimating compensating differentials from observational data.
    JEL: J01
    Date: 2019–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25423&r=all
  4. By: Lawrence F. Katz; Alan B. Krueger
    Abstract: This paper describes and tries to reconcile trends in alternative work arrangements in the United States using data from the Contingent Worker Survey supplements to the Current Population Survey (CPS) for 1995 to 2017, the 2015 RAND-Princeton Contingent Work Survey (CWS), and administrative tax data from the Internal Revenue Service for 2000 to 2016. We conclude that there likely has been a modest upward trend in the share of the U.S. workforce in alternative work arrangements during the 2000s based on the cyclically-adjusted comparisons of the CPS CWS’s, measures using self-respondents in the CPS CWS, and measures of self-employment and 1099 workers from administrative tax data. We also present evidence from Amazon Mechanical Turk that suggests that the basic monthly CPS question on multiple job holding misses many instances of multiple job holding
    JEL: J21 J81
    Date: 2019–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25425&r=all

This nep-ltv issue is ©2019 by Maximo Rossi. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.