Research

The UN General Assembly recognises the right to equal treatment before the law as a universal human right. A minimum requirement to uphold this right is to guarantee access to a lawyer independently of one's income, and this is what legal aid does. While legal aid is necessary to reduce income-based inequality before the law, the extent to which this is achieved depends on the quality of its services. In a context where all defenders have access to a lawyer, I study the impact of refusing legal aid on court outcomes. This is a conservative estimate of the performance gap between privately- and publicly-funded legal services. I do this by taking a double machine learning approach to a new administrative dataset linking data from legal aid application forms to their court outcomes in New South Wales, Australia. Access to the legal aid application forms, which include all the factors used in the decision to provide aid, allows me to learn the unknown treatment assignment function and identify treatment effects via the random forests algorithm. I find that aid applicants who fail the means test and hire a private lawyer are 10 p.p. less likely to be incarcerated than if they passed it and relied on legal aid. With an average positive incarceration length is almost 4 years, this gap is consequential. Finally, I argue that this approach, combining high-quality administrative data with double machine learning, may allow policy-makers to track the performance of public programs that are hard to evaluate using standard econometric approaches.

Keywords: Indigent Defense, Crime, Criminal Justice.

JEL: I30, K14, H44.

Pregnancies conceived via assisted reproductive technology (ART) are considered high-risk. While ART-use correlates with predictors of poor obstetric outcomes, such as advanced maternal age, it remains unclear whether ART-use increases the risk of such outcomes. We address this identification issue by (i) comparing obstetric outcomes for ART-conceived births with spontaneously-conceived births after failed ART treatment, (ii) adjusting flexibly for key confounders using double machine learning. We do this using clinical registry ART data and administrative birth data from New South Wales (NSW) between 2009-2017, which include the outcome of the ART treatment and clinical information on mothers and babies. We find that ART slightly decreases the risk of obstetric interventions, lowering the risk of a caesarean section (-2.8 p.p.) and increasing the rate of spontaneous labour (+3.5 p.p.). This evidence is consistent with ART not exacerbating defensive medical behaviour, where physicians intervene more than necessary to reduce the risk of adverse medical outcomes and litigation. Moreover, we estimate that ART has a precise null effect on the risks of preterm spontaneous birth and preterm birth, on the gestational age at birth, birth weight and APGAR scores—evidence of ART not affecting the health of the baby in a clinically significant way.

Keywords: Fertility, Assisted reproduction, IVF, Obstetric outcomes, Infertility

JEL: I10, I12, I19.

I look at the effects of making the exit costs of cohabitation as high as divorce on new and existing partnerships. I exploit the Family Law Amendment Act, introduced in Australia in 2008, as an exogenous shock to the cost of exiting cohabitation. This law defines cohabiting partnerships as de facto relationships and makes the termination of a de facto relationship equivalent to a divorce. I hence exploit the time discontinuity produced by the reform to identify its effects on the stability of new and existing couples.

I find that when terminating a cohabitation becomes as costly as getting divorced, (i) new unions are more stable (ii) existing cohabitors affected by the reform in their third year are more likely to split, while (iii) the probability of starting a cohabitation and the duration of premarital cohabitation do not change. This paper is the first to look at changes in the exit cost of cohabitation and it does it while disentangling the effect on new and existing partnerships.