Research and teaching cooperation between academia and NSI: Finland

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1 Research and teaching cooperation between academia and NSI: Finland Risto Lehtonen, Seppo Laaksonen and Markku Lanne s: Abstract The paper briefly presents experiences in research and teaching cooperation between academic and official statistics institutions in Finland. In addition, some general and international aspects are discussed. Focus is in survey methodology but also empirical economics is considered. The paper introduces a suggestion that the EU (Eurostat) should promote more strongly European networking in this important field. Further progress necessarily requires additional funding. Key words: funded training, Master s programs, Statistics Finland, University of Helsinki, University of Jyväskylä 1. Introduction Framework of cooperation Mutual benefits of interaction of university research and teaching with official statistics are obvious. A step forward in this avenue is offered by the current idea of establishing a platform, a European Masters in Official Statistics, for coordinated teaching and studying arrangements at a European level. Developing such an activity presupposes information on the state-of-the-art on the different co-operational arrangements already existing between national statistical institutes (NSI) and the Academia. International experiences on research cooperation between NSI s and universities have been recently reported to some extent by Lehtonen, Pahkinen and Särndal (2002) and Lehtonen and Särndal (2009), based on an empirical follow-up survey (NSI Follow-Up Survey). In these papers, cooperation was explored from the side of the NSI. Two aspects were considered: the infrastructure available for R&D within an agency, and networking and similar co-operation arrangements of the NSI with universities. The following forms of research networking of NSI s with universities were considered important (Lehtonen and Särndal 2009): Use of expertise from university departments in methods R&D University professorships with various funding arrangements Fellowship schemes funded by the NSI Joint research projects with universities. It was found that many forms of research networking were executed by the NSI s of the EU countries. In 2006, the most frequently implemented component of networking was Use of

2 experts from university departments to contribute to the Methods R&D (over 90 % of NSI s reported this activity), and the second common was Joint research projects with universities (65 % of NSI s). Within the EU, almost 60 % of NSI s reported having launched funding schemes for professorships (with funding shared by a university and the agency, funded by a university but with some duties at the agency, and/or professorships completely funded by the agency). Forms of cooperation in arranging study programs or courses on disciplines relevant to official statistics were not addressed in detail in the NSI Follow-Up Survey. However, the authors report for example that in 2006, regular teaching and lecturing at universities by staff members of NSI was executed but as a quite rare activity within the NSI s of the EU countries. International experiences indicate that successful and productive networking of NSI with universities involves a well-developed research infrastructure within the NSI (Lehtonen and Särndal 2009). Preferably, an infrastructure should include such components as a well-documented research plan that fits with the agency s objectives, a scientific or professional board with representation from the academic community, and funds and procedures to support scientific research by staff members. In the NSI Follow-Up Survey, the levels of R&D infrastructure and of R&D networking were measured by means of certain summary indicators constructed from the questionnaire items. Both indicators of networking and infrastructure showed that a large variation exists between NSI s (and groups of such institutes). A high level of infrastructure often accompanied a high level of networking. When both levels were high, the chances of a successful implementation of research results into the production of statistics were improved. It is fair to assume that since 2006, co-operational arrangements in research and teaching exchange have progressed further between NSI s and universities of many EU countries. One important recent feature is the increased visibility of Eurostat in fostering such developments. The paper is organized as follows. We first present selected case studies on co-operational arrangements between Statistics Finland and Finnish universities (Section 2). Section 3 includes discussion with a number of working proposals. Statistics Finland and other NSI s Statistics Finland is the general authority within the National Statistical Service whose main tasks include the direction and development of the National Statistical Service. Statistics Finland and 16 other government institutions produce official Statistics of Finland, of which Statistics Finland compiles approximately three quarters. We do not here list all of these institutions but mention some that have recently had activities with the academia, in addition to Statistics Finland: Kela (The Social Insurance Institution of Finland), THL (The National Institute for Health and Welfare ), Heuni (The European Institute for Crime Prevention and Control), TIKE (Information Centre of the Ministry of Agriculture and Forestry) and METLA (Finnish Forest Research Institute). On the other hand, we have several academic institutions and almost all of them have sometimes co-operated with statistics institutions. Again, we do not here mention all of them but basically, all

3 (scientific) universities and also the so-called polytechnic universities (universities of applied sciences) have submitted trainees to the statistical institutions. This kind of training does not automatically belong to university studies but can help students in their future work. In this paper, we highlight cooperation that is on a more regular basis and actually has produced university degrees, Masters, in particular. It should be noted that many students have also prepared a thesis for their Bachelor degree so that various statistical topics are considered. Our key universities related to Masters studies are currently the University of Helsinki and the University of Jyväskylä. In the 1990 s and early 2000 s the role of Jyväskylä was much more crucial than that of Helsinki (more in Section 2). Currently, University of Helsinki is the main actor in this field. Statistics Finland has a long tradition in developing the research infrastructure and in regular cooperation with universities. For example, according to the main lines of the first published research policy programme (1994), a separate Statistical R&D Unit was set up, the post of Scientific Director 1 was established, closer relations of co-operation with universities and other research organizations was developed, a Scientific Advisory Board was launched with representation from universities and research institutes, the Research Reports publication series was launched, and opportunities for personnel to take paid leave of absence for purposes of completing further university studies were created (Statistics Finland, 2005). Furthermore, Statistics Finland has been actively involved in international research co-operation, especially through EU Framework Programmes. A Survey Laboratory has been set up to develop survey measurement methods and a Research Laboratory to promote the use of microdata for research purposes. More recently, an experimental remote access facility for microdata use has been launched. According to Statistics Finland (2005), Overall, in the past ten years, research has become an integral part of Statistics Finland s operation and organization. However, we may see that since then, resources put to research activities have been declined, much due to the economic recession. Also, many jobs have been closed when a job owner has left the institute. Statistics Finland has developed a reasonably strong R&D infrastructure within the agency and has implemented successfully many of the components of research networking. We next present three case studies on co-operational arrangements between Statistics Finland and Finnish universities (University of Jyväskylä and University of Helsinki). 2. Case studies Case study 1: Master s Program in Statistical Systems ( ) One example of cooperation between Statistics Finland and a university is provided by a Master s Program in Statistical Systems (MPSS) (Pahkinen and Lehtonen, 2001). The program was jointly funded by Statistics Finland and University of Jyväskylä, and it was run by the Department of 1 This position was abolished in 2006 but a new joint position, professorship in empirical macroeconomics, was established together with the University of Helsinki. More details in Section 2.

4 Mathematics and Statistics in For MPSS, a professorship in statistics was jointly funded by the agency and the university. MPSS concentrated on the production of experts of statistics specialized in survey sampling and survey methodology. Supplementing the main branch, the program also covered two other branches: biostatistics and industrial statistics. The two-year MPSS program comprised of studies of a total of 120 credit units (cu). To have an access to the program a student should have passed a relevant intermediate university degree (e.g. B.Sc.) or equal amount of studies involving courses in statistics, mathematics, and applied information technology. The applicants were also interviewed in order to evaluate their personal characteristics. The curriculum covered several different courses in areas relevant to official statistics. A key feature was the preparation of Master s Thesis as a joint research project, where the student was hired by a partner organization for a fixed time period. Teaching modules were built mainly on the regular curriculum of the Department of Mathematics and Statistics, but there also were more specialized courses designed for the MPSS. Courses covering important topics in survey sampling and survey methodology were included in the curriculum. The theory of statistical inference, principles of statistical modeling, and probability theory were included as key theoretical areas of statistical inference. Courses on survey sampling, study design, data collection methods and data analysis methods included basic and advanced sampling techniques and estimation procedures such as generalized regression estimation and calibration; edit, imputation and weighting techniques; cross-sectional and panel survey design; experimental design; electronic data collection techniques such as CASIC; small area estimation methods; and the analysis of complex surveys. In addition, the program included professionoriented studies in order to strengthen student s skills in team work and interpersonal communication. Co-operation of the department and partner organizations outside the university constituted an important feature of the program. A Master s thesis was prepared as a joint research project on a topic that was agreed jointly with the co-operating partner organization, the Department of Mathematics and Statistics and the student. Statistics Finland, research and development units of governmental agencies and large companies, and research institutes were typical partner organizations. Benefits for the partner organization arise from the fact that the partner was provided with a scientifically sound solution for a topical R&D need. The University gained from having access to real-world problems to be offered for a student as a topic of the Master s thesis. From the student s point of view, this kind of a networking arrangement was useful e.g. in order to get touch with working life and real-world problems and real data, and to train to work as a member of a multi-disciplinary team. Based on a signed agreement, the student spent, as a salaried trainee, a total of six months in the premises of the partner organization. The salary was paid by the partner organization. And last but not least, research work was co-financed and thus, expenses and risks were shared between the partners. The actors in a Master s thesis project consisted of experts of the partner organization, the MPSS student, and a scientific supervisor provided by the university. The responsibilities and share of labor are described below.

5 University Student Partner institute Supply of courses, scientific supervision, scheduling, followup, project guidance, administration, co-funding Advanced studies in statistics, studies in application area, research work, preparation of thesis Subject-matter supervision, research environment and equipment, project support, co-funding The pedagogical approach adopted in the MPSS can be seen to differ from the so-called learning through doing method, in which the main goal usually is to train a person to carry out routine tasks at work. In the problem-solving oriented approach of the MPSS, a student was encouraged to look for innovative solutions for practical problems. By using a so-called permanent networking scheme, this was achieved by combining the special features of university teaching and research with the special features of real-world environments in research and development oriented organizations. The output of the MPSS program was some ten Master s degrees per year. Since 2005, the activity was continued at University of Jyväskylä in a more restricted format, as a joint effort of Statistics Finland and the Department of Economics of the University of Jyväskylä. Cooperation focuses on education of experts in areas relevant to the production of economic statistics. Here, the main activity is the preparation of Master s Thesis on topics in economics and econometrics, the focus being in empirical micro econometrics. The current agreement continues to the end of A central property of the recent agreement between Statistics Finland and University of Jyväskylä is the provision of access to statistical micro data for research. Research work is the duty of the student but the university supervisor follows her/his work intensively and participates in joint meetings with Statistics Finland experts. The thesis topics have been decided together but many topics are related to regional statistics since this is a top area of the university. There has been a yearly call for students to entry to the training. The preparation of the theses has been quite demanding since both methodological and subject-matter knowledge are needed. However, most of the thesis projects have been very successful. Several Masters have been hired to Statistics Finland. This has also concerned students who have graduated from other sciences. Case study 2: Masters studies in Social statistics with cooperation between University of Helsinki and Statistics Finland The University of Helsinki has established close cooperation with Statistics Finland in research and teaching affairs. Currently, there are three professors working in this area, partly or completely funded by the agency: two professors in statistics at Department of Social Research and one professor in econometrics at Department of Political and Economic Studies (both departments belong to the Faculty of Social Sciences). We discuss here the case of Department of Social Sciences. When starting his or her Master s studies, a student with major in statistics has an option to specialize in social statistics. The organization of teaching and studying resembles many of the

6 features of a Master s program in official statistics, for example: the two professors in statistics are jointly funded by the university and Statistics Finland or, have a shared position in both organizations; teaching modules include courses relevant to official statistics (Sampling methods, Survey methodology, Survey measurement, Imputation methods, Weighting techniques, Survey estimation and analysis, Small area estimation, Statistical disclosure control); the production of Master s thesis follows the scheme of a joint research project with the university and Statistics Finland. We also regularly invite visiting professors from abroad who give advanced courses in statistics. Examples of topics are advanced survey sampling, model-assisted survey sampling, panel survey methodology, multilevel statistical modeling. Some Master s theses in social statistics have been prepared in cooperation with other statistics bodies (see above). The basic principles in these projects are similar to those used with Statistics Finland. For example, three students are currently working with the survey data on a large security survey that was funded by Eurostat and coordinated by Heuni. This project exploits three data collection modes: face-to-face interviewing, telephone interviewing and web. Another recent example is a Master s thesis project with the Research Department of the Kela (Social Insurance Institution of Finland). In this project, administrative data from several sources was combined to analyze the regional patterns of the use of sickness insurance benefits. International exchange constitutes an important feature of Master s studies in social statistics. Students are encouraged (with financial support) to participate in international conferences in statistics, and they can gain some credit units when giving a paper or poster based on their research. This is useful for students preparing a PhD thesis in particular. A good example of this type of cooperation is presented by the annual workshops and summer schools of the Baltic- Nordic-Ukrainian Network in Survey Statistics, see A special feature of this network is that in addition to university departments of the Nordic and Baltic countries, the national statistical institutes are involved in. These workshops are useful contact points especially for junior statisticians since they will meet also senior (and very senior) researchers. For example, we want to mention that Professor Gunnar Kulldorff of Umeå University (Sweden), who has been the initiator of this activity (in 1992), has paid much attention to promote this type of international networking. The activity has been successful in many respects: joint papers, Master s degrees, and a big number of PhD s have been produced. Important type of international cooperation in studies and research takes place in international research projects and networks. Typically, Master and PhD students of social statistics are recruited in the project staff to contribute to the project, produce materials for a thesis report, and to have experiences in international team work. Good examples are the EU 7th Framework Programme project AMELI (Advanced Methodology for European Laeken Indicators), international network on the Comparative Analysis of Enterprise Data 2 (CAED), and the European Social Survey (ESS). 2 Websites:

7 Case study 3: Cooperation between University of Helsinki and Statistics Finland in Econometrics According to the agreement between Statistics Finland and the University of Helsinki, Statistics Finland provides financing for a five-year professorship (starting in 2007) in empirical macroeconomics in the Department of Economics. The duties of the professor are divided between Statistics Finland and the University such that the professor spends 70% of total work time at the University and the rest at Statistics Finland. In addition, it was agreed that 3 7 students of economics are hired annually by Statistics Finland to work on their Master s theses on topics of interest to Statistics Finland, potentially utilizing their data sets. The main goal of this project was to increase interest in empirical macroeconomics in general and macroeconomic data in particular by introducing new courses and supervision of theses at different levels. At the university, the appointment facilitated the introduction of a number of optional special courses relevant to the field of empirical macroeconomics. At the BSc level, a course on national accounts and other economic statistics was introduced. At the MSc level, there are two new courses, empirical macroeconomics and macroeconometrics. Also, a couple of lectures are annually given to first-year students on these topics. In addition, there is a Master s thesis seminar in empirical macroeconomics, and the activities of the professors include the supervision of a number of graduate students doing research in empirical macroeconomics and closely related fields. So far, the course in national accounts has been offered twice. The course consists of lectures, group assignments and a term paper, with the latter two being the most important. To some extent, the system of national accounts is covered, but more importantly, issues related to the use of economic statistics in economic research and practical work is discussed. In particular, things like chain-linking and revisions are thoroughly addressed, and the emphasis is on hands-on data searches, calculations, comparisons and interpretation. The course has been welcomed by students who otherwise are very little exposed to such data issues although they are essential in the practical work of an economist. The first of the two MSc level courses, Empirical Macroeconomics, deals with the statistical analysis of business cycles. In particular, the topics include the extraction of the cyclical components of macroeconomic time series, determining turning points, identifying lead-lag relationships and forecasting business cycle phases. Throughout, data issues are emphasized and taking data revisions into account is explicitly addressed. The latter MSc level course, macroeconometrics, concentrates on taking economic theory to data, i.e., the estimation of macroeconomic models and testing their implications. After taking these two courses, a student should have the necessary skills to critically attack empirical macroeconomic problems. Annually 3 4 students have been working on their Master s theses at Statistics Finland for a period of six months. They as well as approximately four additional students each year attend the Master s thesis seminar in empirical macroeconomics. Typically they start their thesis project by writing a literature review and specifying the exact research topic during the first semester of the seminar after which they start the empirical work, either working at Statistics Finland or individually. Topics have ranged from the revision process in the GDP releases to constructing house price indices. A

8 few students have used the detailed consumer survey data to study the formation of inflation expectations and to test the permanent income hypotheses. It is especially projects like these that would not have been feasible without the possibility to work at Statistics Finland. After graduation, the majority of these students have been employed by Statistics Finland for periods of varying length after their apprenticeship. The duties of the professor include the supervision of the thesis work of quite a few students coming from other universities. In the summer of 2009, a graduate level course on empirical macroeconomics organized together with the Finnish Doctoral Program in Economics was mostly financed by Statistics Finland. The course was taught by Professor Dean Croushore, who is an expert on data issues in macroeconomic research, and this was the first time a PhD course on this topic was offered in Finland. Among the staff of Statistics Finland, there are a number of graduate students whose supervision the professor participates in, in addition to the graduate students of empirical macroeconomics at the University of Helsinki. The professor acts as a member of the Scientific Council of Statistics Finland and the Board of the Research Laboratory of Statistics Finland. The former involves a number of professors from different Finnish universities as well as representatives of Statistics Finland, and its main purpose is to discuss current issues related to statistics and data collection, especially from the viewpoint of research. Through the Research Laboratory, Statistics Finland makes data available for research purposes. At Statistics Finland, the professor occasionally gives talks related to the use of statistics in economic research and participates in a number of expert groups on national accounts. In general, at least from the point of view of the University of Helsinki, the arrangement has been successful. The amount of research on empirical macroeconomics in Finland has increased, the field is now better-known among students than it used to be, and awareness of the subtleties of macroeconomic data has presumably improved. It also seems that as a result of increased teaching in economic statistics as well as the apprenticeships, Statistics Finland is now more popular among economics students, and quite a few of them have even found employment there. 3. Summary and discussion Finnish active research experience between NSI and academia is about 25 years old. Earlier, politicians had decided that the NSI should concentrate on statistics, not on research that should be carried out by universities and research-oriented institutions. Statistical micro data were in fact just gathered in archives, not used after statistical figures were published. At the first stage, from the mid of the 1980, our big surveys (income, family expenditure, living conditions, time use) were desired to be used more broadly for research and the first outside researchers arrived at Statistics Finland. In the mid of 1990 s, enterprise micro data begun also to be of high interest and more and more extensively used (the first Finnish results and a lot of international results, see Laaksonen 1997). During these years, research cooperation between NSI s and academia increased, not only in Finland but everywhere in Europe, US, Canada and so on. These same periods also raised the need to train new generations since it was very well seen that seniors (with not high competence) will be retired in some years. So, we had a challenge to improve

9 the qualifications of the staff while the reality was that the resources tended to be rather decreasing than increasing. Fortunately, some universities also understood that they are needed in this training and changed their overly theoretical study strategy to more applied orientation and became more interested in empirical real data. At the same time, many new Masters and PhD s became more qualified for NSI s and other institutes. Also, EU research projects were pushing forward research and we were able to train new statisticians in these projects. After the fifth framework programme (around 2005) we have participated in only few projects. The role of the University of Helsinki has been become more important in these projects whereas that of Statistics Finland has been decreased. Moreover, due to the economic recession, new obstacles have been arisen. We believe that stronger European cooperation in all respects would help, also in recruiting new specialists for official statistics. As far as the University of Helsinki is concerned, two activities are directly related to official statistics, Social statistics at Department of Social Research and Empirical econometrics at Department of Political and Economic Studies. Future plans of these departments comprise strengthening their mutual cooperation in further development of Master studies on social statistics, econometrics and official statistics at University of Helsinki. We naturally are interested in joining in a Master s Program in areas related to official statistics, if such a program will be developed for example as a multi-node distributed (virtual) network activity of European universities, national statistical agencies, and other interested actors (including Eurostat). How this could be arranged in practice? It is a big issue to be discussed further. In any case, some additional funding is needed (fortunately, it is already started when arranging this workshop). Of course, there are lighter and heavier options to continue in this road. We present some below: (i) A semi-short (one week minimum) course on a topic of common interest, organized by a voluntary university. There are models already in various areas for such courses. The host university needs basic funding for cost and teaching. In addition, students should be reimbursed at minimum level (travel, accommodation). There should be call for applications. A Master s student should have an opportunity to participate in one international course, at minimum. (ii) Funded visiting opportunities for joint research, especially when the thesis requires crosscountry data. This could be rational already for Master students but of course more important for PhD students. (iii) Exchange of micro data that is not automatically possible since confidentiality should be taken into account. But there are various tools to use micro data so that individuals have not been recognized (remote access, common program codes, exchange of results). (iv) Certification exam for European Masters: a good and challenging target but how to administrate it well? There could be the general requirements for that exam but each accomplished university should be entitled to accept it.

10 (v) Distance learning and similar modern technologies. A European Masters supplemented with a virtual networking scheme (including online web courses, video courses, student-teacher communication exchange technologies etc.) could provide a possible additional solution. References Laaksonen, S. (1997) (ed.). The Evolution of Firms and Industries. Statistics Finland Research Reports pp.. Start of the CAED (Comparative Analysis of Enterprise data) global network. Lehtonen, R., Pahkinen, E. and Särndal, C.-E. (2002). Research and Development in official statistics and scientific co-operation with universities: an empirical investigation. Journal of Official Statistics, 18, Lehtonen, R. and Särndal, C.-E. (2009). Research and Development in official statistics and scientific co-operation with universities: a follow-up study. Journal of Official Statistics, 25, Pahkinen, E. and Lehtonen, R. (2001). Master s program in statistics as platform for co-operation between university and official statistics. Invited paper, Bulletin of the International Statistical Institute, 53 rd Session, Seoul, August 2001, Vol. LIX, Book 1, Statistics Finland (2005). Main lines of research policy in Helsinki: Statistics Finland.