Personal profile

Overview

Constanza Avalos is a PhD student in Social Statistics at the Cathie Marsh Institute, University of Manchester (UoM). She is a Sociologist and holds an MSc in Social Research Methods and Statistics from the UoM. She has developed her career mostly in Chile, leading research projects in public and private institutions, both in the design of surveys and in the analysis of quantitative information supported by statistical software. Constanza worked as head of the Department of Agricultural Studies at the Chilean National Institute of Statistics. She has done research into macroeconomic growth, food security, and food industry. These studies have been published in national and international institutions contributing to methodological improvements of studies in the food area. Her master and doctoral research has been funded by National Agency for Research and Development – Becas Chile. Her PhD research focus on modeling the effect of food labels and ecolabels on consumers' choices in the framework of causal inference. Constanza's doctoral resesearch is supervised by Nicholas Shryane.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 2 - Zero Hunger
  • SDG 3 - Good Health and Well-being
  • SDG 10 - Reduced Inequalities

Education/Academic qualification

Master of Statistics, MSc Social Research Methods and Statistics, The University of Manchester

1 Oct 202010 Sept 2021

Award Date: 10 Sept 2021

Bachelor of Science in Economics, Universidad de Santiago de Chile

1 Mar 201330 Jun 2016

Award Date: 30 Jun 2016

Bachelor of Social Science, Sociology

1 Mar 20031 Dec 2008

Award Date: 11 Dec 2009

Areas of expertise

  • HA Statistics

Research Beacons, Institutes and Platforms

  • Cathie Marsh Institute

Keywords

  • Causal inference
  • Experimental Design
  • Machine Learning
  • Food Security