Patrick Rehill Email & Phone Number

I am spending a few months at the Australian Centre for Evaluation at Treasury to work on quasi-experimental evaluations of federal policy.

I co-teach Causal Inference an intensive in the summer session at ANU for masters students. The course aims to take masters-level data scientists and give them the tools for making causal inferences from data including the use of randomised controlled trials, quasi-experimental methods and causal machine learning.

I work on answering social science research questions with large and often complex datasets. Most of this work is consulting for governments. Some highlights have been modelling the effects of COVID-19 containment policies on vaccine adoption and psychological wellbeing, evaluating a housing program for those exiting custody for an Australian corrections department and working on a project to determine the effect that socio-economic stressors in childhood can have on biomarkers later in life.

Melbourne, Victoria, Australia

I am currently working towards my PhD at the Centre for Social Research and Methods. My research focuses on developing causal machine learning methods and structural causal models for use in impact evaluations by government and not-for-profits.

When I am not working on my PhD research, I consult with not-for-profits to do quantitative research or data science projects. The type of work varies from projects that focus purely on data wrangling and analysis to assist a larger team, to designing research projects, running analysis and writing reports or white papers. My consulting work has included:• Writing a major report on the wellbeing of young Australians for UNICEF and the Australian Research Alliance for Children and Youth• Writing white papers at the International Women's Development Agency that used the organisation's gender sensitive measure of multidimensional poverty - Equality Insights. My first paper was a methods paper around the importance of using random effects models for measuring gender difference in poverty. My second paper was about the effect that drought in Fiji had had on different dimensions of deprivation.• Designing and building a dashboard with R and Shiny to allow staff at the Australian Environmental Grantmakers Network to easily keep track of feedback from event attendees which feeds into organisational KPIs.

Melbourne, Australia

The AEGN helps environmental philanthropists to give more and more effectively to environmental organisations. My role as Research Officer is to conduct research for member-facing or public-facing publications and events. Some of my projects have included:- Running a program of research yearly which culminates in writing our Giving Trends report. The project involves pulling together administrative data from a number of sources and supplemental research to create the most comprehensive picture of the state of environmental giving in Australia.- Working in partnership with the Department of Energy and Environment to publish a public report on a decade of environmental NGO data that had previously not been publicly available.- Developing a new framework for our members to fund climate change causes.

Melbourne, Australia

I have been engaged for a number of consultancies in the IWDA's Equality Insights team. The work focuses on analysing survey data from developing countries with R and then writing outputs based on this analysis.Equality Insights is a project developing an individual deprivation measure to better understand poverty, particularly gender differences in poverty. It is really interesting as it differs from conventional measures of poverty in two ways:1) It measures a wider range of indicators of poverty than traditional income based or even multi-dimensional measures. For example it measures food insecurity and education, but also personal autonomy and access to contraception.2) Enumeration occurs at the individual level rather than the household level (which other measures use) meaning it better captures differences within households (particularly gender and age differences).

Melbourne, Australia

I taught Applied Research Methods, a third-year capstone subject on quantitative research methods to BA social science students at the University of Melbourne. The course focuses on the basic theory of quantitative research, basic causal inference, academic writing and SPSS skills. It culminates in students writing their own quantitative research paper using linear regression. I received excellent reviews from students in end-of-semester surveys.

Melbourne, Australia

I consulted on projects for public sector and not-for-profit clients. My work tended to focus on the areas of start-ups, health, education and innovation. Some of the projects I am most proud of included:- Writing a state government industry department's biotechnology strategy.- Designing a major career education initiative for an Australian education department.- Advising a large technology not-for-profit on how it should adapt in the face of serious challenges to its operating model.In this role I developed my ability to write clear and insightful outputs for clients and conduct quantitative and qualitative research under often tight deadlines.

Melbourne, Australia

I coordinated regional debating nights for the Ivanhoe Region and adjudicated secondary school debates across Victoria.

Melbourne, Australia

I undertook an internship which focused on changes in Emergency Relief provision by the organisation between 2011 and 2014. It found a large disparity between the types of goods that saw the most growth in demand as emergency relief and the changes in the prices of different types of goods in the Consumer Price Index. This could be explained by applying a model of short-run relative elasticities of demand which suggested that people absorbed price increases in inelastic goods (such as housing) by cutting back on consumption of elastic goods (such as food). This was supported by fieldwork accounts. Emergency relief was therefore responding to this shortfall in elastic consumption, even though overwhelmingly inelastic goods (primarily energy and housing) saw the most growth as economic stressors.

Doctor Of Philosophy - Phd, Machine Learning In Impact Evaluation

Master Of Public Policy And Management

Ba (Hons), Politics And International Studies, First Class Honours

Activities and Societies: Melbourne University Debating SocietyMajor in Politics and International Studies, Minor in Economics My honours.