Ilja Kristian Kavonius
Statistics
- Division
-
External Statistics &Sector Accounts
- Current Position
-
Principal Economist - Statistician
- Fields of interest
-
Economic Growth,Macroeconomics and Monetary Economics,Other Special Topics
- Other current responsibilities
- 2022-
Member of the European Commission Expert Group on Sectoral Accounts
- 2022-
Vice-chairperson - University of Helsinki Docents' Association (Helsingin yliopiston dosenttiyhdistys)
- 2022-
Member of Teaching Skills Evaluation Committee - University of Helsinki/Faculty of Social Sciences
- 2018-
Adjunct Professor (dosentti)/University researcher (25%) - University of Helsinki/Centre for Consumer Society Research, Finland
- 2016-
Secretary of the ESCB Expert Group on Distributional Financial Accounts (EG DFA)
- 2014-
Adjunct Professor (dosentti) - University of Eastern Finland/Faculty of Social Sciences and Business Studies, Joensuu, Finland
- 2011-
Member of the OECD Expert Group on Disparities in a National Accounts Framework (EG DNA)
- Education
- 2000-2011
Doctor of Social Sciences, University of Helsinki, Finland
- 1994-1999
Master of Arts, University of Joensuu (University of Eastern Finland), Finland
- Professional experience
- 2018-
Adjunct Professor (dosentti)/University researcher (25%) - University of Helsinki, Centre for Consumer Society Research, Finland
- 2003-
Principal Economist-Statistician (Senior Economist-Statistician until 2019 and Economist-Statistician until 2010) - External Statistics & Sector Accounts Division, Directorate General Statistics, European Central Bank
- 2021-2022
External expert (consultant) - European Court of Auditors, Luxembourg
- 2008-2010
Researcher (half-time) - University of Helsinki, Department of Political and Economic Studies, Finland
- 2009
Economist (half-time) - Fiscal Policies Division, Directorate General Economics, European Central Bank
- 1998-2008
Senior Statistician (2002 onwards on unpaid leave) - Statistics Finland, National Accounts Division, Helsinki, Finland
- 2002
Statistician - United Nations Economic Commission for Europe, Geneva, Switzerland
- Teaching experience
- 2022
Introduction to the Framework of Economic Statistics (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 2022
Challenges of Globalisation, Sustainable Development and Changing Society to the Measurement of Economies and Welfare (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 2021
Introduction to the Framework of Economic Statistics (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 2021
Challenges of Globalisation, Sustainable Development and Changing Society to the Measurement of Economies and Welfare (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 2020
Challenges of Globalisation, Sustainable Development and Changing Society to the Measurement of Economies and Welfare (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 2019
Challenges of Globalisation, Sustainable Development and Changing Society to the Measurement of Economies and Welfare (5 ECTS course) - Faculty of Social Sciences, University of Helsinki, Finland
- 11 August 2022
- WORKING PAPER SERIES - No. 2707Details
- Abstract
- Globalisation has a major impact on the levels and distribution of wealth. The financial markets are highly integrated, and valuations of financial assets follow international patterns, which has contributed to large increases in financial wealth over the past 25 years. Nonetheless, this has not led to an equally large increase in property income because the rates of return have decreased during the same era. Moreover, changes in functional income distribution (capital/labour shares) have not been fully transmitted to the distribution of primary income between households because other institutional sectors – particularly the government sector – hold considerable amounts of financial assets. At least in the short term, the decrease in rates of return seems to contradict claims that, due to an increase in both financial and inherited wealth, we are entering an era of increasing income inequality. In this article, the link between financial wealth and pre-tax household income distribution is scrutinised for three European countries using a conceptually fully consistent macro framework. First, national balance sheets are combined with the related income flows. After this, income flows that are not property income but are considered part of national income (e.g., wages and salaries) are added, the national income flows are broken down by institutional sector and the household sector income flows separated. Finally, distributional household micro data are used to break down the aggregate household sector income flows by income decile. The article utilises this framework to analyse the evolution of rates of return and capital and labour shares as well as how the property income flows created by financial wealth have affected household primary income distribution.
- JEL Code
- D10 : Microeconomics→Household Behavior and Family Economics→General
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
D32 : Microeconomics→Distribution
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
G51 : Financial Economics
- 22 July 2022
- WORKING PAPER SERIES - No. 2683Details
- Abstract
- The last few decades have been accompanied by disruptive changes to the structure ofemployment which have led to deterioration in demand for middle-skill occupations, a processknown as job polarisation. As the demand for middle-skill workers shrinks, expectationsabout households’ income through their lifetime horizon are adjusted. It is unclear whetherthese expectations can loop back into the credit system, and affect the lending behaviour ofcredit institutions, or whether this process impacts on the households’ self-assessment of theiropportunities to borrow money. In this paper, we study how the process of job polarisationaffects credit demand and supply, studying its relationship with credit constraint and creditquality.
- JEL Code
- G51 : Financial Economics
J24 : Labor and Demographic Economics→Demand and Supply of Labor→Human Capital, Skills, Occupational Choice, Labor Productivity
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
O15 : Economic Development, Technological Change, and Growth→Economic Development→Human Resources, Human Development, Income Distribution, Migration
- 22 July 2020
- STATISTICS PAPER SERIES - No. 37Details
- Abstract
- The Expert Group on Linking Macro and Micro Data for the household sector (EG-LMM) was established in December 2015 within the European System of Central Banks (ESCB) with the aim of comparing and bridging macro data (i.e. National Accounts/Financial Accounts) and micro data (i.e. the Household Finance and Consumption Survey) on wealth. Furthermore, the Expert Group also focused on developing distributional results for household macro balance sheets, starting with national data from the euro area Member States. The Expert Group assessed the extent to which these two sets of statistics could be compared and was able to link most balance sheet items. Since, following adjustments, the estimates yielded from the micro data were still lower than the macro data, an estimation method was developed to gross up the micro data to be in line with the macro data results. The methodology delivers estimates of the distribution of household wealth that are closely aligned with Financial Accounts aggregates, thereby offering valuable new information for the purposes of macroeconomic analyses based on such Financial Accounts. Further research is needed to examine the robustness of these results and to improve the estimation method taking into account country-specific features and information. The Expert Group has therefore recommended further work be undertaken with a view to compiling experimental distributional results by end-2022.
- JEL Code
- D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
G51 : Financial Economics
- 16 October 2018
- WORKING PAPER SERIES - No. 2187Details
- Abstract
- The financial accounts of the household sector within the system of national accounts report the aggregate asset holdings and liabilities of all households within a country. In principle, when household wealth surveys are explicitly designed to be representative of all households, aggregating these micro data should correspond to the macro aggregates. In practice, however, differences are large. We first discuss conceptual and generic differences between those two sources of data. Thereafter we investigate missing top tail observation from wealth surveys as a source of discrepancy. By fitting a Pareto distribution to the upper tail, we provide an estimate of how much of the gap between the micro and macro data is caused by the underestimation of the top tail of the wealth distribution. Conceptual and generic differences as well as missing top tail observations explain part of the gap between financial accounts and survey aggregates.
- JEL Code
- C46 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Specific Distributions, Specific Statistics
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts - Network
- Household Finance and Consumption Network (HFCN)
- 11 July 2016
- STATISTICS PAPER SERIES - No. 14Details
- Abstract
- Integrated quarterly sector accounts (QSA) provide an analytical tool to understand the generation, allocation and use of income for all institutional sectors in the economy. They also provide a tool to analyse production from a sectoral point of view instead of an industry point of view. However, since QSA are published in current prices only, sectoral volume and price measures are lacking as an important toolkit for economic analysis and forecasting, notably in the case of gross value added. This paper introduces a methodology to estimate sectoral price and volume measures for euro area value added at a quarterly frequency and provides a comparison of alternative estimation methods. It presents a benchmark method which yields robust estimates of sectoral volumes and prices in the euro area.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
- 27 November 2013
- WORKING PAPER SERIES - No. 1619Details
- Abstract
- The report on the Measurement of Economic Performance and Social Progress by Stiglitz, Sen and Fitoussi concludes that in the measurement of household welfare all material components should be covered, i.e. consumption, income and wealth, from both the micro as well as the macro perspective. Additionally, several other initiatives like the G20 finance ministers
- JEL Code
- D30 : Microeconomics→Distribution→General
D31 : Microeconomics→Distribution→Personal Income, Wealth, and Their Distributions
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth - Network
- Household Finance and Consumption Network (HFCN)
- 7 December 2009
- WORKING PAPER SERIES - No. 1124Details
- Abstract
- The financial crisis has highlighted the need for models that can identify counterparty risk exposures and shock transmission processes at the systemic level. We use the euro area financial accounts (flow of funds) data to construct a sector-level network of bilateral balance sheet exposures and show how local shocks can propagate throughout the network and affect the balance sheets in other, even seemingly remote, parts of the financial system. We then use the contingent claims approach to extend this accounting-based network of interlinked exposures to risk-based balance sheets which are sensitive to changes in leverage and asset volatility. We conclude that the bilateral cross-sector exposures in the euro area financial system constitute important channels through which local risk exposures and balance sheet dislocations can be transmitted, with the financial intermediaries playing a key role in the processes. High financial leverage and high asset volatility are found to increase a sector’s vulnerability to shocks and contagion.
- JEL Code
- C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G01 : Financial Economics→General→Financial Crises
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
- 18 September 2008
- WORKING PAPER SERIES - No. 940Details
- Abstract
- The present System of National Accounts (SNA93) treats durable consumption goods as consumption goods rather than investment although rentals for owner occupied households is imputed into GDP. We argue that households de facto treat the purchase of durable goods as investments and thus, the treatment of durables as capital assets conceptually does not differ from the present treatment of owner occupied dwellings. This is not captured by the economic analysis based on current statistical conventions. The purpose of this paper is to estimate the effect of durable goods and ICT on euro area economic growth and productivity change; when expenditure on consumer durables is recorded as capital investment. The capitalization of consumer durables impacts both the levels and growth rates of the capital stock, productivity and GDP. Our growth accounting computations demonstrated that the capital services of durables contributed one-tenth of economic growth and one-eight of labour productivity growth in 1995-2004. ICT's impacts were larger, i.e., one-fifth of GVA growth and one-sixth of labour productivity growth.
- JEL Code
- E01 : Macroeconomics and Monetary Economics→General→Measurement and Data on National Income and Product Accounts and Wealth, Environmental Accounts
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
J24 : Labor and Demographic Economics→Demand and Supply of Labor→Human Capital, Skills, Occupational Choice, Labor Productivity
O11 : Economic Development, Technological Change, and Growth→Economic Development→Macroeconomic Analyses of Economic Development
- 23 May 2007
- WORKING PAPER SERIES - No. 755Details
- Abstract
- The purpose of this paper is to estimate the impact of capitalising durable goods on the Euro area household saving ratios and disposable incomes for the first time. The reason for this exercise is twofold. Firstly, it is generally accepted that individual households regard consumer durables as assets even though they are not treated as such in the System of National Accounts 1993. Secondly, the issue is related to the definition of household saving ratios. For instance, the U.S. Federal Reserve Board publishes three household saving measures. The main difference between these saving ratios is that one is derived by treating expenditure on consumer durables as investments while the other ones are compiled by considering them to be household final consumption expenditure. We find that the effect of capitalising consumer durables on EA saving ratios is moderate. The impact is lower than it is in the US.
- JEL Code
- E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
- 2022
- Journal of Financial Stability
- 2020
- Statistical Journal of the IAOS
- 2019
- Journal of Official Statistics
- 2016
- Statistical Journal of the IAOS
- 2015
- Journal of Network Theory in Finance
- 2013
- Journal of Economic and Social Policy
- 2010
- Scandinavian Economic History Review
- 2009
- The Review of Income and Wealth
- 2006
- Journal of Official Statistics
- 2003
- Statistical Journal of the United Nations Economic Commission for Europe
- 2011
- Statistics Finland
- 2013
- Handbook of Systemic Risk, edited by Fouque, J.-P. and Langsam, J. A., Cambridge University Press