The goal of this session is to understand how the age structure of a population is related to different services requirements. And in the next 10 minutes, we will explain how to account for the Paid work overhead and we will presents some examples of this accounting using the case study of Catalonia in Spain. So, human activity can be considered as a fix endowment. So, each person has 24 hours per day and 365 days per year. So, we each have 8,760 hours per year. And, this time is fixed we cannot have more hours per day. So, all the activities that we do that the society is able to do, have to be done with this time frame. So how is this time used? So, as we said before out of the total, part of this goes into physiological overhead which is sleeping, eating, taking care of oneself. And that accounts for usually about half of the time that we have. And, the rest of the time we called disposable human activity. Which can be divided into different activities. For example, paid work and unpaid work, education and leisure and entertainment. We also have some time that we spend traveling to different places to work. For example, to school or to places of entertainment. So, this time in transport can be allocated to different activities. This classification of time used at the individual level is useful. For example, to compare how different people use their time across different age groups. And also, to compare as we are going in this case how men and women use their time. So, what we can see from these graphs is for example, how time devoted to education which is the red mark is concentrated mostly in children and people up to the age 24. Unpaid work which comprises house chores, cooking, cleaning, taking care of others. We see that it's unevenly distributed across genders. So for example, women devote a lot more time to unpaid work than men do. We can also see how this time allocation affects the time that people have available for other things. So if more time is devoted to unpaid work, then less time is available, for example for leisure. And also, the amount of time devoted to physiological overhead diminishes in the records. What is also important to note this is that there is different activities, there's different time usage, say how different requirements in terms of resources. So, when we aggregate this at the level of society, we see how this affects the requirement of flows in the society. And the way that we aggregate this is to look at the population structure and to see how many people we have in all the different age categories and into different genders, and from this so that we can calculate how much time the society in total devotes to these different types of activities. We can also do this analysis at the household level. And so what we see when looking at a household is for example, how much time the household is supplying to the paid work sector. How much time is used in physiological overhead within the household? How much time the household is using for itself for some productions. So for example, in household chores. And, there is also some time that is spent in the entertainment, education, in health. Some time that is spent in shopping, in buying some goods that household needs. What we see is also, that all this time, all these activities that the household does have to be matched by an equal amount of time. In terms of, services and production of goods and food and energy and all the things that the household consumes. So the society has to provide the same amount of time in for example, education and health care that the household consumes in order to have a balance between these activities. The requirement of activities in the household and the supply of activities from the side of society. In the next slide, we will try to study in general terms the requirement of time from the education and health sectors by different household in the real world. Here in this table, we can see the requirements of the human activity from the health system in Catalonia in 2006. In the first two columns, we have divided the population in different age category and in different genders. So in the first column, we have the number of visits to the health system performed by different people of different age categories and different sex. So in the bottom of the column, we have the total amount of visit per year. In the next column, we have the percentage of visits to the health system performed by people of different age categories and different sex. So we have the percentage of the utilization of the health system by these people. In the next column, we have the total human activity allocated to a health system. And this time is the time spent by workers that work in the health system. So, this total amount is distributed in different age categories according to the percentage of the previous column. Then, by using the population of different age categories, we can calculate the amount of hours consumed by each person in different age categories and by different sex. This graph in the bottom part of the slide shows that, people all that are 64 years old are the people that consume more hours in the health system. This is obvious because, these people goes more often to the hospitals and to visit the doctor. Also, we can see that very young people or younger than 40 years old, more or less in the same amount of time from the health system than people from 45 to 64. The same sort of analysis can be performed for the location system. This is also, for Catalonia 2006. The first two columns divided people in different age categories and different sex. So, from the time use survey in Catalonia 2006, we know how many hours is allocated to study. For instance, people younger than 15 years old, allocate more or less two and a half hours to study. Whereas, people older than 64 years old, almost don't allocate time to study. So, in the next column you have the population divided by different age categories and different sex. And in the next column we have the total amount of hours that the society has allocated to study. Next, we have the person that of this time by different age categories. And in the next column we have also as the previous case the total amount of hours allocated to the educational sector. This is, this column represents the workers working in the education sector administrative people and also teachers. So, with this information, we can distribute all the time allocated in the education sector that corresponds to different age categories. In this way, we can calculate the amount of hours consume by different people of different age categories and different sex that they consume from the education sector. As we can see, old people older than 64 almost don't consume hour from the education sector. Whereas, people from five to 15 years is the people that consume most hour from the education sector. This slide shows a very simple exercise trying to evaluate the changes in the quality of the education sector. For instance, on the upper left side we have the requirement of hours from the education sector by different age categories. As mentioned before, young people consume more time from the education sector. On the right side, we have the age pyramid of Catalonia 2006. As we can see in the table in the bottom part of the slide, the total requirement of hours, matches with the total supply of hours in these years. This is considered as a baseline. But then, as the population of Catalonia has changed. And, if we keep the allocation requirement in hours constant by different age categories, we can calculate the total requirement of hours from the population in Catalonia to the education sector. And, if we can calculate the total supply of hours. We can see that, even though the workers has increased, the hours per week that they work in the education sector has decreased. This entails a reduction in the total supply of hours. This, can be considered as a decrease in the quality of education that because most people is attended by less amount of workers. So to sum up, in these lesson, we have learned that the age structure of the population is an important variable to consider when studying the metabolism of societies. The provision of services such as education and health care, cannot be estimated on a per capita basis because, the surfaces are typically skewed towards specific demographics. MuSIASEM makes it possible to access the requirement of time in a Paid Work sector at different levels of analysis. So we have seen the individual level, the household level and the society level.