Misha has been active in official statistics for a long time. Many of you know him from his position at the World Bank and as co-founder of Open Data Watch (ODW) and of course as a pleasant and experienced colleague. In this interview we aim to give a bit more insight in Misha’s background and shed light on his plans and strategies for the IAOS in his role as president.
Interviewer: Thank you for allowing me to interview you and especially as we are because of the COVID-19 pandemic, still not able to travel freely abroad, to do this interview via video-conferencing. The pandemic has been both a hindrance to progress and an opportunity for creating new approaches tp the work by statistical organizations, individual statisticians and other scientists. I am curious to hear about your professional experiences and also how in your private life you and your wife have dealt with the restrictions of the pandemic?
At the early stages of the pandemic here in the US (March 2020) my wife and I locked ourselves in our house in Maryland. We were scared and did not socialize with anybody. We used to leave the house daily for a walk and once every three weeks to shop for food and wine. This situation gave us both more time to work. I was doing my IAOS related tasks and some consultancy work. My wife did not play live concerts, but she gave violin and viola lessons to her students via Skype.
I followed data on COVID cases in US and worldwide closely. The variety of data collected and derived by modeling showed that the statistical systems are not well positioned to cope with such an extreme situation. Like many other people, I was lost in the conflicting information universe.
Interviewer: Thanks. Good to hear that you and your wife are well.
Before moving in detail to your role and your strategy as IAOS president, I invite you to tell us more about your background and why you chose a career in official statistics.
I grew up in a small town in Lithuania, in the Samogitia region., The people there are very friendly and yet very tough and stubborn. After finishing high school there, I entered a Vilnius University Master’s Program to study mathematical economics. After graduating and teaching at the university for two years, I was admitted to the prestigious PhD program of the Central Economical Mathematical Institute of the Academy of Sciences of the USSR in Moscow. At age 27, I came back to Vilnius as a young PhD and continued teaching and doing research at Vilnius University. For my modeling (input-output and econometrics work), I used statistical information. I did not care too much about how the data were collected and compiled. I worked at the University in different capacities until 1987 when I got my chance to leave the Soviet Union. I came to the USA as a political refugee and was ready to do any job to support my family. I was lucky to get a contract with the Center for International Research at the US Census Bureau to study the Soviet economy. Among other tasks, I joined a team that did the USSR GDP calculations. This was my first serious entry into the world of statistics. With a colleague from Georgetown University, I did an estimation of the size of the economies of the Soviet Republics
I started by doing research and estimates on the formerly centrally planned economies. From 1989-91, I worked at the WEFA. I led the Centrally Planned Economies Department, providing clients with economic and political analysis and economic forecasts of the USSR, Yugoslavia, Czechoslovakia, China and the rest of the COMECON countries. These were the years of the USSR opening and my clients such as Boeing, Siemens and others were very interested in the forecasts and opportunities to enter new markets. The discussions with the economics departments of large companies scared me as they were basing multimillion investment decisions on our forecasts. As a commercial company you have to demonstrate to the client that you are right to be paid for your services. The forecasts, therefore, were very balanced.
This led me to the World Bank where I started in 1991 by leading a team which worked on statistical issues of the countries which joined the IMF and the World Bank after the USSR collapsed.
Interviewer: So your first experiences come from graduating and teaching in Lithuania and working for WEFA. These are experiences from working in formerly centrally planned economies. Can you tell us what you find that has changed and how it changed?
At the World Bank, I was dealing with data from centrally planned economies and even published a few issues of the Statistical Handbook: States of the Former USSR and other publications about data and data quality. I followed the development of the statistical systems of these countries. Unfortunately, they are not as far advanced as I would like them to be. When the countries joined the world statistical system they were embraced and received a lot of help – the OECD, the IMF, the World Bank, and others were all there. They quickly (1993) introduced the System of National Accounts (SNA), meaningful price indexes, household surveys, other surveys and other statistical products and techniques used to measure economic and social developments in a market economy. As time passed, interest in these countries by the international organizations and the broader donor community diminished. The requirements for change and improvement, however, have increased. Factors to be addressed include theSNA (2008), a new system of Balance of Payment (BOP), Sustainable Development Goal indicators and abilities to adjusting surveys to get data of higher granularity, data to track the COVID-19 pandemic, and changes in the data collection systems during the Pandemic. Other issues have emerged such as globalization, climate change, the implementation of the UN Fundamental Principles of Official Statistics (UNFPOS), improvement in the legal environment and the modification of organizations to cope with change.
Interviewer: You have been involved in many large global statistical projects. Can you tell us a bit more about your involvement in and assessment of these large global statistical projects, their successes and failures?
In the department in the World Bank, we created an arm which provided financing in the form of loans and grants to support improvements in national statistical systems. Several projects were delivered and national strategies for statistics were created. We celebrated these successes, but we also saw that, while many National Strategies for the Development of Statistics (NSDSs) were created,only a few of them had a chance to be implemented. The biggest project I worked on was the International Comparison Project (ICP). However, I was never fully satisfied with the results of that program.
Interviewer: Why were you never satisfied with the results from the International Price Comparison (ICP)?
I wondered why we could not cover the whole globe with the ICP program? The 2005 round was a different round than any of the previous ones. It was a full worldwide round with all the structures put in place, global and regional governance structures, and high level technical advisory committees checks and balances. However, some countries did not like the preliminary results, and we had to do a lot of work to explain it. We also warned these countries that if they did not accept the results, they would be treated as if they had not participated and their results would be imputed using econometric technics. In almost all cases, it worked. I was not fully satisfied because there were several countries which were ready to participate but could not for political or financial reasons. That was my big worry.
Interviewer: On a more recent subject, there will be many younger colleagues who will associate you with Open Data Watch (ODW). Can you explain, as you are one of the founders of Open Data Watch, why Open Data is so important and what led to the creation of the ODW?
We live in the age of all kinds of fake news, misinformation, and misinterpretation. The only way to find the truth or something close to it is to make data open. By that we mean that data should be complete, primary, timely, accessible, machine processable, non-discriminatory, non-proprietary, and license free. Most importantly, metadata should accompany data sets. Understanding the importance of open data, I co-founded the non-profit organization, Open Data Watch, which deals with the openness of statistical systems.
We founded ODW in 2013 when all three co-founders left the World Bank. Our main goal was to create the index of openness of NSSs. It took some time before an acceptable methodology was developed, and funds secured. The first output was in 2015. The first ODIN covered only developing countries. We realized, however, that not everything is nice and clear with openness in developed countries and therefore we included all the countries for which we could get information.
It is relatively easy to obtain open data in other areas of governments, such as lists of government decrees, number and locations of local parks and other factors. Opening statistical data is a process which must go through many stages. Therefore, the openness of the NSS is very important for the functioning of democratic institutions and societies.
Interviewer: Thanks for the information about your earlier career. Clearly you have a rich expertise based on working in Official Statistics for over 35 years in a variety of domains. Is there a domain or are there domains that you find more interesting than others?
The most interesting and challenging for me is the institutional set-up of National Statistical Offices (NSOs) and the whole national statistical system (NSS). It is worth noting that the issue of NSO restructuring is usually tackled only in comprehensive capacity development programs, which are financed with the World Bank loans. In discussions with clients, you would see that there is not much interest in the institutional restructuring, as they want IT equipment or a consultancy to improve some statistical domains or training sessions abroad. The development of comprehensive projects is difficult as you have to persuade the client that minor changes will not eventually lead to a good statistical system. The comprehensive programs are even more important today as the statistical ecosystems are expanding with more administrative data, big data, etc.
Interviewer: You mentioned earlier that while you were at the World Bank you were involved with creating an area which provided financing in the form of loans and grants to support improvement in the national statistical systems. I personally remember especially the Trust Fund on Statistical Capacity Building (TFSCB). Can you share with us some of the very specific experiences that you remember from working with countries and regions?
Each regional and national statistical set-up is unique. In some regions there are regional or sub-regional organizations, which can help to improve statistical systems in their member countries. I have worked with many regional banks, UN agencies and others to support countries. You work in tandem with an intermediary to gain experience which can be replicated in other countries in the region. In some cases, it does not work, and the intervention needs to be focused on one country. In most cases, the World Bank worked with countries directly as borrowing is done by countries and the projects are country specific. However, regional projects are becoming increasingly prominent in recent years.
Interviewer: Based on all these experiences, is there some specific advice on how funding of capacity development best can be organized in these difficult times with such global challenges as the pandemic and climate change?
Capacity development is a broad concept – you need to make changes in the set-up of the statistical system, changes in statistical production, changes in IT architecture and equipment and, most importantly, changes in Human Resource systems and training and retraining of staff. This is the menu which should be followed when organizing a capacity development project. Financing is a tricky issue as well. We see from Paris21’s PRESS publications and cries coming out of the Bern Network that the desired financing is not coming through. On the other hand, many estimates of needs are so high that it may scare the donors, as donors want to see results.
Interviewer: Okay, let’s now move to your new role as president of the IAOS. I think the readers of the Journal will be interested in hearing how you - also based on your background - see the role of the IAOS for the former centrally planned economies?
We need to note that statisticians from countries of centrally planned economies became exposed to the world statistical system after 1991. They joined the Conference of European Statisticians, the UN Statistical Commission, and the ISI. The IAOS has a broad membership of experienced statisticians, statistical managers, data scientists and others who can help. It is important for the IAOS to position itself to be able to extend a helping hand. The IAOS would need to have seed money to establish the work modalities in countries to support change. On the other hand, the IAOS needs the NSOs and other data suppliers and data user organizations to join the IAOS and get more involved in the international issues of statistics. This is particularly important to the statisticians working in regional offices in countries lacking knowledge about and exposure to requirements of official statistics beyond their country.
Interviewer: and coming back to the issue of statistical capacity building, what role do you see the IAOS can play in capacity building and in its funding?
I am very interested in capacity building as a task for the IAOS. It is one of the strands in our strategy. We are participating in the ISI Statistical Capacity Building Committee, but I would like to do more. I am thinking about how we can raise funds for the IAOS which would go to improve national statistical systems. Most of the work the IAOS does is linked to statistical capacity – the discussions and articles in the SJIAOS, the webinars, conferences and other worldwide, regional or national activities are geared towards improving statistical capacity.
Interviewer: During the last 20 years, a revolution has taken place with respect to available data sources, new methodologies andIT applications. How do you think especially the technological revolution has influenced official statistics?
Technology has a huge influence on official statistics. Geospatial data coming from the satellites is a game-changer.So is data coming from social media, credit card companies, trade, health and other organizations. Within NSOs, new technology for data collection (CAPI, CATI) and data processing changes the work conditions of staff and increases quality and timeliness. New IT applications, more data sources and Artificial Intelligence(AI) techniques supplemented by improved computing power makes the work more interesting and challenging. We need also to note that the unequal access to IT around the world slows down improvements in the global statistical system.
Interviewer: … and how did you experience the last two years, with the pandemic. How do you think the official statistics can or have to draw lessons from this?
The main lesson is flexibility of the system. We need to be able to shift from collecting usual data to collecting new types of data for policy makers and the public at large. The second lesson is to learn to change routine operations such as data collection via interviews to data collection via internet, phone, etc.
Interviewer: In your role as IAOS president, what do you think are the most striking challenges for official statistics and the IAOS in the next 2 to 5 years?
The official statistics community must learn to work and live in a rapidly changing environment when they are no longer the only game in town. This is no longer possible with the data revolution. NSOs should reestablish themselves as the head of an enlarged national statistical system. That is already happening. The first shock from the data revolution is already behind. The same is true for the IAOS. The IAOS is becoming--or should become— an organization embracing national and international statisticians, data scientists, and -- most importantly — data users (including politicians, academia, NGOs, journalists and others).
Interviewer: The IAOS sets every year and especially with a new president, its objectives via a strategic plan. As president you can have a strong influence on the direction of the IAOS. From this role, what are concretely the objectives that you have set for your presidency?
Looking back at the impressive list of the past presidents of the IAOS, I understand that I am stepping into big shoes. I believe I am the first non-statistician to be elected as president of the IAOS. I will try to do my best to make the IAOS more inclusive, more flexible, more vibrant and more prosperous. I understand the limitations including the two-year time limit for the presidency. We will try our best.
Interviewer: … and what are the main issues you would like to include in the strategy for the period 2021-2023?
The two-year strategy relies heavily on the previous strategies. It is impossible and unreasonable to change the course of action completely. This is true for the current strategy which is being drafted. However, I consider the following two issues tob e important targets: The membership, particularly institutional membership, is of great concern. We will work hard to increase and broaden the membership. We need to look at all the carrots we can use to encourage institutions and their members to join.
The second issue deals with misuse of and compliance with the UN Fundamental Principles (UNFPOS). We should find the cases of misuse of UNFPOS and — particularly ethical issues — and address them using all the means we have. As an NGO we have much more “power” than governments of neighboring countries and international and regional organizations of countries in violation of the principles.
Interviewer: Indeed, beyond the strategy for initiatives and actions, the IAOS is first and foremost a community of members. You mention as the first issue of concern for the period 2021-23 the institutional membership. What are your expectations for the IAOS community?
I expect to be able to have an interested community which is ready to help each other and work toward common goals. I expect the community to actively participate in webinars, conferences, SJIAOS publications and online discussions, to contribute to the process of the young statistician’s competition. I also would like to be able to work with a broad IAOS membership base by attracting new members and soliciting more funds to have more activities.
Interviewer: The second issue to which you dedicate a lot of importance is the compliance to theUNFOPS. This and the Declaration on Professional Ethics for Statisticians would guarantee in many aspects a high quality of official statistics. How do you assess the current quality of official statistics compared to 20 years ago?
The issue of quality of official statistics will keep coming back as long as the statistical services exist – there are several issues which we need to consider. The first one is the situation when statisticians are under pressure to produce indicators of questionable quality to satisfy their superiors. Second, when the capacity of the NSO does not allow it to produce data of reasonably good quality. Third, when the capacity is there but the requirements for new data increase so dramatically that it becomes impossible to produce data to meet certain standards. As you can see, I am trying to avoid comparisons across time, but you can draw conclusions. We need to hold more discussions on the implementation of the Fundamental Principles worldwide and to adherence to the ten principles by national governments. We also need to discuss if the Fundamental Principles are fit for the enhanced ecosystems of national statistics. We are planning to discuss some of those issues during 18th IAOS conference in Krakow in 2022.
Interviewer: Thanks for elaborating on these two important priorities; they sound obvious, but what I missed are issues like the SDG’s or other statistical domains. Why are these not more profound in the strategy?
We need to focus on several issues and try to make a difference – we will look at SDGs including those indicators which are derived by international organizations or companies like Gallup and see where we can fit in this process. Another topic of global interest is climate change.
Interviewer: … and how do you see the role of the IAOS in data science and data ecosystem development?
I am not sure how much the IAOS can do in these fields, particularly with data science. On the ecosystem developments, we should do more by embracing colleagues from the broad ecosystem. We are reaching out to the broadest possible audience by inviting them to our conferences, webinars and other events. We are reaching out to all NSOs, to all international organizations, the private sector involved in data production and statistical capacity building, and to the wide list of academic institutions. We are very interested in participating in international events such as the UN World Data Forum, meetings of the American Statistical Association, the Royal Statistical Society and others.
Interviewer: As last question I would like to invite you to give a specific message to the IAOS members?
I am looking forward to the next two years working with all of you to make the IAOS more visible and stronger. For that, I need understanding and support from the IAOS Executive Committee and each member of the IAOS.
Interviewer: Thank you. This is a great message and I think you have provides us us insight in your background and ideas and plans with the IAOS. Thanks for this interview, and on behalf of the IAOS community I would like to wish you success in the coming years.