1. Measuring quality of life in Latin America Orazio P Attanasio (UCL & IFS)

2. INTRODUCTION Measurement has a long tradition in economics  Bentham  Cowles foundation There is now a renewed interest in these issues. It is recognized that measuring economic variables alone might be unsatisfactory …and even for economic variables one needs to discuss the level of aggregation Many of these discussions are (or should be) driven by theory

3. Why go beyond economic variables? Much of economics is about human welfare, which is affected only in part by income, consumption etc.  There are other important variables and dimensions that affect ‘utility’. Economic decisions are not taken in a vacuum, but interact with other aspects.  Our models have a residual, can we measure part of it? ‘Technological’ relations that are important in determining economic outcomes are influenced by non economic factors:  Example: the production function of human capital,

4. What determines utility? There is lots of talk about the economics of happiness My take: a moderately conservative one  True that many dimensions are important (Sen)  However, I am skeptical as economists we can offer much in this field. An important temptation to be resisted:  Tolerate bad performance in the economic sphere because it could be compensated in other dimensions

5. What determines utility? Much important work:  How does the brain work when making economic decisions?  What determine preferences?  What determine abilities? Much (less important) work:  Comparing happiness in different countries

6. Economic decisions are not taken in a vacuum. When we model individual decisions we often recognize the presence of aspects not captured by our model  ‘Unobserved heterogeneity’ Much progress can be made in measuring parts of these factors. Here economists can learn much from other scientists:  Psychologists  Anthropologists  Epidemiologists  Sociologists  Education and health specialists A variable which I think is very important in developing countries is information

7. Measuring information Poor individuals in developing countries make important investment decisions What information do they use? What are the perceived returns on different activities? Even if one buys the rational expectations assumption, it is important to establish what is the conditioning set. This can be done

8. Measuring expected returns to education among Mexican youths (joint work with Katja Kaufmann) Within an evaluation of Jovenes con Oportunidades we asked 16 year olds, just graduated from junior high school, questions about expected future earnings We infer the probability distribution under different schooling scenarios.

9. Explaining probability

10. Data: subjective expectations Probability of working: Assume that you finish secundaria (preparatoria, universidad), but then you stop going to school. From zero to one hundred, how certain are you that you will be working at the age of 25? Earnings distribution: Assume that you finish secundaria (preparatoria, universidad), but then you stop going to school and you have a job. (a) What do you think is the maximum amount you can earn per month when you are 25 years old? (b) What do you think is the minimum amount you can earn per month when you are 25 years old? (c) From zero to one hundred, how certain are you that your earnings at age 25 will be at least... (midpoint between maximum and minimum amount of question above)?

12. These ideas can (and are) being used in a variety of contexts Effectiveness of bednets in India Productivity of wells in India Effectiveness of contraception in Africa Return to an ‘buffalo health insurance’ scheme in India … much more can be done!

13. Learning about ‘technology’ relationships Most phenomena we study are very complex: Example: Production of human capital Dynamic process Many factors  Early years nutrition and social stymulus  Schooling  Role of motivation  Role of non-academic skills All these interact with basic investment decisions:  Liquidity constraints  Decisions within the family

14. Measurements can help We need to integrate economic surveys with other measurements Biological markers Individual food intakes Cognitive development Ability

15. Some of these represent important challenges Example of Cognitive development: Are existing scales and instruments adequate to developing countries?

16. Levels of aggregation Household surveys are clearly crucial. But often we need to go deeper than that and collect information at the individual level This is crucial to understand within families allocations. … and this might be crucial for understanding policies.

17. Where to go? We need to be creative in data production. We need to experiment and develop new instrument  Expectations and risk perceptions  Expected returns to education  Expected return to investments  Social capital  Cognitive abilities and perceptions  Measuring the environment

18. Where to go? We need to be creative in exploiting different opportunities:  Integrating existing data initiatives  Using data sets developed for evaluation work Exploit at best new technologies in data collection Coordinate data initiatives across countries  What happened to MECOVI?