Population economics (or demographic economics) is the application of economic analysis to demography. It aims to theoretically model and to empirical predict variation in population, and is as such interested in outcomes such births, marriage, divorce, mortality, morbidity and migration. Many major political challenges result from demographic changes. For instance, the pensions systems in many high-income suffer under a declining ratio of economically active individuals per retiree. This trend is caused by declining birth rates and increasing longevity. Or, some middle-income countries (such as China) have to cope with an excess supply of men, which results from a cultural preference for sons and the wide availability prenatal sex-determination technology. In this seminar, we first explore together the ideas and methods economists use to understand population dynamics. This will aid our understanding of topics such as the formation and dissolution of families and migration. In a second step, students will carry out a small empirical project.
The focus of this seminar is on understanding the fundamental models of population economics keeping also close contact to empirical trends and research. In addition, we study the role of public policy in affecting demographic trends. We will cover the history of population, theories of the demographic transition; population aging and population decline; Malthus and population debate; economic theories of family formation and dissolution (i.e., marriage, fertility, divorce); Mortality; Morbidity; and Immigration.
There is no single textbook we follow. We will use a variety of journal articles. A detailed reading list is in the syllabus. For each topic additional material (such as presentation slides) may be posted bewlow.
The scheduled meetings (including topic) can be found in the syllabus: pdf-file
Introduction: slides
Demographic transition: notes
Fertility: slides
Marriage: slides
Divorce: slides
Mortality:
Migration:
In the beginning of the semester, there will be about three lecture sessions. Towards the end of the semester, there will be about four sessions for the student's classroom presentations. The final number of sessions will depend on the overall demand (see below).
Each student has to work on a small empirical project. This involves the steps of finding your own topic (i.e., formulating a simple research question), data collection, empirical analysis (using simple descriptive statistics), preparing a short classroom presentation, and writing a short report by the end of the semester. More details on finding at topic and data are provide below.
Presentation: In each session, two students will present their topic. Each presentation will be 20 minutes in total. Note, I will enforce a strict time limit. Following each presentation, we will have a short discussion, where the audience (=non-presenting students) will ask questions or provide comments. The scheduled presentations (for the summer term 2020) can be found here: pdf-file
Written report: At the end of the semester students have to hand-in a short report (between 1,500 and 1,700 words). This is a written-version of your presentation.
Students will be graded according to their classroom presentation (40%), and their short report (60%). The deadline for the short report is June, 26.
The first and most important step in your empirical project is finding you own topic and data. This is itself is probably the most important learning process in your empirical project. It allows you to understand important limitations of empirical works such as that
dis-aggregated data are much harder to find than aggregated data;
there are many interesting and important research question, which cannot be studied due to a lack of data;
it is not sufficient to find data; preparation is need before you can analyze;
etc.
You should find a topic (broadly) related to the topics listed above. A natural restriction is data availability. In this term, you can use regional (community or district-level) data from Austria from any period.
One way to get-started is to do something old-fashioned: you can actually go to a library! Visit the area with statistical publications and look at (older) data published in "big statistical books". While these printed "hardcopy data" are cumbersome, you have to digitalize (=type) it before analyzing, but they allow you to browse nicely across different topics. This helps you to understand which type of data/variables are available, and to find a topic. You can work with (older) "hardcopy data", but you do not have to. Of course, you will find even more data online. I will point you to two good starting points for demographic data from Austria.
To learn about recent data, you can have a look at the annual Demographic Yearbook (Demographisches Jahrbuch) of Statistik Austria. Here is the link to the most recent version: link.
For historical data, you can visit ANNO - AustriaN Newspapers Online, a digitisation initiative of the Austrian National Library (Österreichische Nationalbibliothek). This website hosts a digital version of many newspapers and journal. Among these are also statistical publications: 1880-1909, 1910-1918. In each book, you can click through all pages. Maybe this inspires you to use historical data.
In one previous term , we had a focus on historical data, in particular from the Austro-Hungarian Empire (1867-1918). Here is a list of past presentation titles:
Emigration in the Habsburg Empire. Determinants of the emigration of Austrian to America between 1860 and 1890.
An analysis of mortality patterns in Austria between 1900 and 2014
An analysis of age at first marriage patterns in Austria between 1899 and 2014
An exploration of the incarceration statistics of the Habsburg Empire and attempt of a comparison with contemporaneous data from Austria
A comparative analysis of the seasonality in infant mortality in urban and rural areas of the Habsburg Empire in the period from 1880 to 1910
Differences in fertility between rural and urban regions in the Habsburg Empire
Students have to be present at every meeting. Non-attendance in one meeting will have no consequences.