Self-Employment Incomes in the Italian EU-SILC Measurement and International Comparability Marco Di Marco
|
|
|
- Dwayne Ryan
- 5 years ago
- Views:
Transcription
1 Incomes in the Italian EU-SILC Measurement and International Comparability Marco Di Marco Eurostat and Statistics Finland International Conference on Comparative EU Statistics on Income and Living Conditions: Issues and Challenges Session on Income Measurement in EU SILC Helsinki, 6th November 2006
2 CONTENTS COMPARABILITY: WHAT DOES IT MEAN?
3 CONTENTS COMPARABILITY: WHAT DOES IT MEAN? SELF-EMPLOYMENT INCOMES IN THE ITALIAN EU SILC
4 THE CHALLENGE OF COMPARABILITY EU SILC Framework Regulation (art. 1): international comparability is a fundamental aim, to be pursued through methodological studies, carried out in close co-operation between Member States and Eurostat
5 THE CHALLENGE OF COMPARABILITY EU SILC Framework Regulation (art. 1): international comparability is a fundamental aim, to be pursued through methodological studies, carried out in close co-operation between Member States and Eurostat Now also endorsed in the European Code of Statistical Practices
6 THE CHALLENGE OF COMPARABILITY EU SILC Framework Regulation (art. 1): international comparability is a fundamental aim, to be pursued through methodological studies, carried out in close co-operation between Member States and Eurostat the EU SILC project has been started with two ambitious purposes: to provide a set of harmonised statistics on incomes and living conditions following the best practices available to launch a co-ordinated experiment in improving the state of the art in the collection/measurement of incomes and living conditions
7 DEFINING COMPARABILITY Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability.
8 DEFINING COMPARABILITY Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data A multidimensional complex concept! Can (should) we have a simple definition?
9 DEFINING COMPARABILITY COMPARABILITY IS A PROPERTY OF THE DATA Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability.
10 DEFINING COMPARABILITY COMPARABILITY IS A PROPERTY OF THE DATA (i.e. of the data production processes) Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability.
11 DEFINING COMPARABILITY Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability. OF THE STATISTICS
12 DEFINING COMPARABILITY Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability. OF THE INTERPRETATIONS
13 DEFINING COMPARABILITY Verma (2002 and 2006): [ ] may defy precise definition [ ] we mean that data (estimates) for different populations can be legitimately (i.e. in a statistical valid way) put together (aggregated), compared (differenced), and interpreted (given meaning) in relation to each other and/or against some common standard. Comparability is a relative concept: we can only have degrees of comparability, not absolute comparability. WE SHOULD SEEK FOR ORDINAL MEASURES OF COMPARABILITY
14 DEFINING COMPARABILITY the dataset (the statistic, the interpretation) A is more suitable for international comparisons than B. Such ordinal assessments are the only way to evaluate the success of the endeavours to produce: datasets indicators analyses
15 DEFINING COMPARABILITY the dataset (the statistic, the interpretation) A is more suitable for international comparisons than B. Such ordinal assessments are the only way to evaluate the success of the endeavours to produce: datasets indicators analyses harmonised at the international level
16 DEFINING COMPARABILITY COMPARABILITY IS THE ULTIMATE AIM OF HARMONISATION
17 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Welfare comparability: statistics and interpretations
18 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Welfare comparability: statistics and interpretations Data comparability ( = comparable data production processes)
19 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Welfare comparability: statistics and interpretations Data comparability ( = comparable data production processes) is a necessary condition for welfare comparability
20 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Welfare comparability: statistics and interpretations Data comparability ( = comparable data production processes) is a necessary condition for welfare comparability Not always sufficient: PPP s equivalence scales
21 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Welfare comparability: statistics and interpretations Data comparability ( = comparable data production processes) is a necessary condition for welfare comparability Not always sufficient: PPP s equivalence scales In these cases, HOWEVER, data production processes are not directly concerned
22 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Conversely, under-estimation of income calls for improvements in measurement accuracy
23 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Conversely, under-estimation of income calls for improvements in measurement accuracy and the presence of non-monetary components of income (self-production, imputed rents, social transfers in kind) for a more comprehensive definition of income
24 DEFINING COMPARABILITY DATA COMPARABILITY AND WELFARE COMPARABILITY Conversely, under-estimation of income calls for improvements in measurement accuracy and the presence of non-monetary components of income (self-production, imputed rents, social transfers in kind) for a more comprehensive definition of income In these cases, data production processes ARE CONCERNED
25 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs)
26 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs) that permits meaningful comparisons, within and across countries (regions, sub-groups),
27 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs) that permits meaningful comparisons, within and across countries (regions, sub-groups), meaningful means useful for welfare analysis (a bridge between data and welfare comparability)
28 DEFINING COMPARABILITY A TENTATIVE DEFINITION MEANINGFUL IF: semantic consistency of the national definitions with the common EU SILC Target Variable definition
29 DEFINING COMPARABILITY A TENTATIVE DEFINITION MEANINGFUL IF: semantic consistency of the national definitions with the common EU SILC Target Variable definition total disposable income as comprehensive as possible (AS INCOME IS USED AS A PROXY FOR WELFARE)
30 DEFINING COMPARABILITY A TENTATIVE DEFINITION MEANINGFUL IF: semantic consistency of the national definitions with the common EU SILC Target Variable definition total disposable income as comprehensive as possible (AS INCOME IS USED AS A PROXY FOR WELFARE) a partial measure of income reduces comparability
31 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs) that permits meaningful comparisons, within and across countries (regions, sub-groups), between any couple of statistical units.
32 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs) that permits meaningful comparisons, within and across countries (regions, sub-groups), between any couple of statistical units. MICRO COMPARABILITY
33 DEFINING COMPARABILITY DATA COMPARABILITY = MICRO COMPARABILITY Comparability at the micro level, i.e. between the incomes of any couple of households/individuals living in any of the countries,
34 DEFINING COMPARABILITY DATA COMPARABILITY = MICRO COMPARABILITY Comparability at the micro level, i.e. between the incomes of any couple of households/individuals living in any of the countries, is a necessary condition for meaningful welfare comparisons at the aggregated level, too
35 DEFINING COMPARABILITY DATA COMPARABILITY = MICRO COMPARABILITY Comparability at the micro level, i.e. between the incomes of any couple of households/individuals living in any of the countries, is a necessary condition for meaningful welfare comparisons at the aggregated level, too WHY? the preliminar step for the correct computation of most well-known inequality indexes consists in ranking the statistical units from the poorest to the richest
36 DEFINING COMPARABILITY WITHIN AND ACROSS Micro comparability within country ( any couple of statistical units of country A can be compared )
37 DEFINING COMPARABILITY WITHIN AND ACROSS Micro comparability within country ( any couple of statistical units of country A can be compared ) and across countries ( any statistical unit of country A can be compared to any statistical unit of country B )
38 DEFINING COMPARABILITY WITHIN AND ACROSS Micro comparability within country ( any couple of statistical units of country A can be compared ) and across countries ( any statistical unit of country A can be compared to any statistical unit of country B ) Both are required for the international comparability of income data
39 DEFINING COMPARABILITY Within country to compare national inequality indexes (for example, Gini indexes for Italy and France)
40 DEFINING COMPARABILITY Within country to compare national inequality indexes (for example, Gini indexes for Italy and France) Across countries to compare all countries against a common benchmark (for example a European Poverty Line)
41 DEFINING COMPARABILITY A TENTATIVE DEFINITION Comparability of income data is a property (a set of properties) of the data production processes (inputs, techniques and outputs) that permits meaningful comparisons, within and across countries (regions, sub-groups), between any couple of statistical units. a circular definition!!!
42 DEFINING COMPARABILITY WHAT IS A COMPARISON? In mathematics, the elements of a set are comparable if, for any couple of elements x and y of the set, there exist a relation R such that at least one of the two following statements is true: x R y ; y R x
43 DEFINING COMPARABILITY WHAT IS A COMPARISON? In mathematics, the elements of a set are comparable if, for any couple of elements x and y of the set, there exist a relation R such that at least one of the two following statements is true: x R y ; y R x Each one of the preceding statements (as well as their logical union) is a comparison.
44 DEFINING COMPARABILITY WHAT IS A COMPARISON? In mathematics, the elements of a set are comparable if, for any couple of elements x and y of the set, there exist a relation R such that at least one of the two following statements is true: x R y ; y R x Each one of the preceding statements (as well as their logical union) is a comparison. For the income variable, an obvious choice for the relation is the greater than or equal one
45 DEFINING COMPARABILITY WHAT IS A COMPARISON? In mathematics, the elements of a set are comparable if, for any couple of elements x and y of the set, there exist a relation R such that at least one of the two following statements is true: x R y ; y R x Each one of the preceding statements (as well as their logical union) is a comparison. For the income variable, an obvious choice for the relation is the greater than or equal one, because it permits to rank the statistical units from the poorest to the richest (PENS S PARADE)
46 DEFINING COMPARABILITY A TENTATIVE DEFINITION in short: COMPARABILITY AS MEANINGFUL ACCURACY (at the micro level)
47 IMPROVING COMPARABILITY UNDER-ESTIMATION IS THE MAJOR CHALLENGE TO THE INTERNATIONAL COMPARABILITY OF INCOME DATA
48 IMPROVING COMPARABILITY UNDER-ESTIMATION IS THE MAJOR CHALLENGE TO THE INTERNATIONAL COMPARABILITY OF INCOME DATA If under-estimated components of income are dropped: the income definition is not comprehensive (! lower comparability)
49 IMPROVING COMPARABILITY UNDER-ESTIMATION IS THE MAJOR CHALLENGE TO THE INTERNATIONAL COMPARABILITY OF INCOME DATA If under-estimated components of income are dropped: the income definition is not comprehensive (! lower comparability) If under-estimated components of income are included: the income measure is less accurate (! lower comparability)
50 IMPROVING COMPARABILITY UNDER-ESTIMATION IS THE MAJOR CHALLENGE TO THE INTERNATIONAL COMPARABILITY OF INCOME DATA If under-estimated components of income are dropped: the income definition is not comprehensive (! lower comparability) If under-estimated components of income are included: the income measure is less accurate (! lower comparability) Since it reduces comparability anyway, under-estimation should be MINIMISED
51 SELF-EMPLOYMENT INCOMES TAX AVOID. & DEDUCTIONS GROSS INCOME TAXABLE INCOME TAXES + CONTRIB. NET TAXABLE INCOME DISPOSABLE INCOME UNDER- REPORTING INCOME REPORTED
52 SELF-EMPLOYMENT INCOMES ADMINISTRATIVE DATA TAX AVOID. & DEDUCTIONS GROSS INCOME TAXABLE INCOME TAXES + CONTRIB. NET TAXABLE INCOME DISPOSABLE INCOME UNDER- REPORTING INCOME REPORTED
53 SELF-EMPLOYMENT INCOMES SURVEY DATA TAX AVOID. & DEDUCTIONS GROSS INCOME TAXABLE INCOME TAXES + CONTRIB. NET TAXABLE INCOME DISPOSABLE INCOME UNDER- REPORTING INCOME REPORTED
54 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The alternative sources of microdata on earnings from self-employment may not contain the item disposable income as such.
55 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The alternative sources of microdata on earnings from self-employment may not contain the item disposable income as such Survey data may be affected by underreporting. Administrative data gathering the individual tax returns do not take account, of course, of illegal tax evasion and may not display all the authorized deductions allowed in the calculation of taxable income (tax avoidance)
56 SELF-EMPLOYMENT INCOMES TAX AVOIDANCE the tax authorities may allow special deductions (e.g. for the profits retained and invested in the business)
57 SELF-EMPLOYMENT INCOMES TAX AVOIDANCE the tax authorities may allow special deductions (e.g. for the profits retained and invested in the business) Also, departures from standard accounting rules (e.g. depreciation costs)
58 SELF-EMPLOYMENT INCOMES TAX AVOIDANCE the tax authorities may allow special deductions (e.g. for the profits retained and invested in the business) Also, departures from standard accounting rules (e.g. depreciation costs) Some categories of taxpayers (e.g. family business, farmers, starting-up companies ) may be subject to a preferential tax regime that grants them special benefits
59 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH For the, when both the administrative and the survey datasources report it, income from self-employment is set equal to the maximum value between: (i) the (net) self-empl. income resulting in the tax return (ii) the (net) self-empl. income reported by the interviewee
60 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH For the, when both the administrative and the survey datasources report it, income from self-employment is set equal to the maximum value between: (i) the (net) self-empl. income resulting in the tax return (ii) the (net) self-empl. income reported by the interviewee This departure from the standard definition is adopted in order to minimise either: under-estimation due to tax avoidance/evasion in the administrative data or: under-reporting in the survey data
61 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH For the, when both the administrative and the survey datasources report it, income from self-employment is set equal to the maximum value between: (i) the (net) self-empl. income resulting in the tax return (ii) the (net) self-empl. income reported by the interviewee This departure from the standard definition is adopted in order to minimise either: under-estimation due to tax avoidance/evasion in the administrative data or: under-reporting in the survey data depending on which of the two is larger!
62 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH the underlying assumption is that no individual over-reports her/his incomes either in the survey or in the tax return under this assumption, the highest value is closer to the true value
63 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH The procedure increases the degree of international comparability of the Italian income data under the assumption that self-employment income in the benchmark country is not under-estimated
64 SELF-EMPLOYMENT INCOMES THE ITALIAN APPROACH The procedure increases the degree of international comparability of the Italian income data under the assumption that self-employment income in the benchmark country is not under-estimated The true national income should be set as the comparable benchmark in all EU SILC countries
65 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The two datasources do not perfectly overlap: some individuals report self-employment incomes in only one datasource
66 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The two datasources do not perfectly overlap: some individuals report self-employment incomes in only one datasource This is the case of some individuals whose professional status at the time of the interview is different from that of the income reference period For example, a shopkeeper, who went on pension during the income reference period, may disregard his past self-employment incomes in the survey questionnaire
67 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The two datasources do not perfectly overlap: some individuals report self-employment incomes in only one datasource This is the case of some individuals whose professional status at the time of the interview is different from that of the income reference period an employee, who has been unemployed during the income reference period, may disregard his past unemployment benefits in the survey questionnaire
68 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The two datasources do not perfectly overlap: some individuals report self-employment incomes in only one datasource This is the case of some individuals whose professional status at the time of the interview is different from that of the income reference period and of many percipients of small and/or secondary self-employment incomes the incomes of baby-sitters may be reported in the survey questionnaire while being un-noticed for tax purposes
69 SELF-EMPLOYMENT INCOMES CONTENT OF DATASOURCES The two datasources do not perfectly overlap: some individuals report self-employment incomes in only one datasource This is the case of some individuals whose professional status at the time of the interview is different from that of the income reference period and of many percipients of small and/or secondary self-employment incomes minor additional incomes of employees may be reported in the tax return and ignored in the survey questionnaire
70 SELF-EMPLOYMENT INCOMES SURVEY SELF-EMPLOYMENT INCOMES The collection of self-employment incomes through personal interviews aims at: minimising reporting errors devising suitable imputation procedures
71 SELF-EMPLOYMENT INCOMES SURVEY SELF-EMPLOYMENT INCOMES The collection of self-employment incomes through personal interviews aims at: minimising reporting errors devising suitable imputation procedures The setup of the imputation procedures has been eased: by the rich qualitative information available in the survey by the reduction of the unreliable answers retained among the valid cases.
72 SELF-EMPLOYMENT INCOMES SURVEY SELF-EMPLOYMENT INCOMES the interviewers were asked: not to compel reluctant individuals A MISSING INCOME IS BETTER THAN A FALSE ONE
73 SELF-EMPLOYMENT INCOMES SURVEY SELF-EMPLOYMENT INCOMES the interviewers were asked: not to compel reluctant individuals A MISSING INCOME IS BETTER THAN A FALSE ONE to assess, after the interview, the reliability of the income answers UNRELIABLE ANSWERS HAVE BEEN REMOVED
74 SELF-EMPLOYMENT INCOMES SURVEY SELF-EMPLOYMENT INCOMES the amount of self-employment income is asked after a reminder question that suggests a definition of income that is close to the: money drawn out concept
75 SELF-EMPLOYMENT INCOMES
76 SELF-EMPLOYMENT INCOMES
77 SELF-EMPLOYMENT INCOMES
78 SELF-EMPLOYMENT INCOMES
79 SELF-EMPLOYMENT INCOMES MAIN RESULTS With respect to the exclusive use of survey data, the linkage with administrative data has
80 SELF-EMPLOYMENT INCOMES MAIN RESULTS With respect to the exclusive use of survey data, the linkage with administrative data has increased substantially the number of percipients %
81 SELF-EMPLOYMENT INCOMES MAIN RESULTS With respect to the exclusive use of survey data, the linkage with administrative data has increased substantially the number of percipients % and the average self-employment income %
82 SELF-EMPLOYMENT INCOMES MAIN RESULTS With respect to the exclusive use of survey data, the linkage with administrative data has increased substantially the number of percipients and the average self-employment income Among the individuals for which both sources contain self-employment incomes, the record linkage reveals that under-estimation is more frequently observed in the tax data
83 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4%
84 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% at the moment of the interview
85 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% In the tax file there is an higher proportion of percipients of secondary ( employees ) and of marginal/temporary ( unemployeds, other inactive ) self-employment incomes
86 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% as well as larger shares of the corresponding incomes
87 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% in both sources (and in the final data as well), these sub-groups are the ones with the highest degree of inequality
88 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% More generally, there is more inequality in the tax data (for all sub-groups)
89 SELF-EMPLOYMENT INCOMES Table 1 Gini decomposition of the self-employment incomes, by datasource and sub-group of percipients (all percipients of self-employment incomes in each datasource) SURVEY DATA TAX DATA FINAL DATA Overall Gini % % % - between groups % % % - within groups % % % - crossover % % % group specific Gini share of population share of income group specific Gini share of population share of income group specific Gini share of population share of income Employees % 2.4% % 7.7% % 5.6% Enterpreneurs % 12.2% % 9.5% % 11.6% Professionals % 24.8% % 27.4% % 23.4% Artisans/shopkeepers % 40.3% % 38.0% % 37.4% Co-helpers % 5.8% % 3.8% % 5.1% Coop. stockholders % 2.3% % 0.9% % 1.9% Co.co.co % 9.2% % 2.1% % 7.6% Unemployeds % 0.7% % 1.0% % 1.0% Other inactive % 2.4% % 9.6% % 6.4% That is why, in the final data, self-employment incomes are more unequally distributed w.r.t. survey data
90 SELF-EMPLOYMENT INCOMES Table 2 Records retained in the final dataset, by datasource and sub-group of percipients (all percipients of self-employment incomes in the final dataset) survey tax all Employees Enterpreneurs Professionals Artisans/shopkeepers Co-helpers Coop. stockholders Co.co.co Unemployeds Other inactive All In the final data, the majority of retained records for the marginal sub-groups of percipients of self-employment incomes ( employees, unemployeds and other inactive ) comes from the tax datasource
91 SELF-EMPLOYMENT INCOMES Table 2 Records retained in the final dataset, by datasource and sub-group of percipients (all percipients of self-employment incomes in the final dataset) survey tax all Employees Enterpreneurs Professionals Artisans/shopkeepers Co-helpers Coop. stockholders Co.co.co Unemployeds Other inactive All whilst the majority of retained records for the ordinary self-employed ( entrepreneurs, professionals, artisans etc.) comes from the survey
92 SELF-EMPLOYMENT INCOMES Table 2 Records retained in the final dataset, by datasource and sub-group of percipients (all percipients of self-employment incomes in the final dataset) survey tax all Employees Enterpreneurs Professionals Artisans/shopkeepers Co-helpers Coop. stockholders Co.co.co Unemployeds Other inactive All this means that, for these ordinary self-employed, survey data are usually higher than tax data (i.e. survey under-reporting is lower than the sum of tax evasion and tax avoidance)
93 SELF-EMPLOYMENT INCOMES Table 3 Content of the datasources, by sub-group of percipients (all percipients of self-employment incomes in the final dataset) reported TAX DATA not reported observed SURVEY DATA missing (imputed) NO to S.E. question FINAL DATA Employees Enterpreneurs none Professionals none Artisans/shopkeepers Co-helpers none Coop. stockholders none Co.co.co Unemployeds Other inactive All
94 SELF-EMPLOYMENT INCOMES Table 3 Content of the datasources, by sub-group of percipients (all percipients of self-employment incomes in the final dataset) reported TAX DATA not reported SURVEY DATA YES to S.E. missing observed question (imputed) NO to S.E. question FINAL DATA Employees Enterpreneurs none Professionals none Artisans/shopkeepers Co-helpers none Coop. stockholders none Co.co.co Unemployeds Other inactive All
95 SELF-EMPLOYMENT INCOMES Table 3 Content of the datasources, by sub-group of percipients (all percipients of self-employment incomes in the final dataset) reported TAX DATA not reported observed SURVEY DATA missing (imputed) NO to S.E. question FINAL DATA Employees Enterpreneurs none Professionals none Artisans/shopkeepers Co-helpers none Coop. stockholders none Co.co.co Unemployeds Other inactive All Both datasources miss a substantial amount of information
96 SELF-EMPLOYMENT INCOMES Table 3 Content of the datasources, by sub-group of percipients (all percipients of self-employment incomes in the final dataset) reported TAX DATA not reported observed SURVEY DATA missing (imputed) NO to S.E. question FINAL DATA Employees Enterpreneurs none Professionals none Artisans/shopkeepers Co-helpers none Coop. stockholders none Co.co.co Unemployeds Other inactive All Of all the percipients of self-employment incomes in the integrated dataset: 40.9% would have been ignored (or misclassified as percipients of pure capital incomes) by using exclusively the tax records
97 SELF-EMPLOYMENT INCOMES Table 3 Content of the datasources, by sub-group of percipients (all percipients of self-employment incomes in the final dataset) reported TAX DATA not reported observed SURVEY DATA missing (imputed) NO to S.E. question FINAL DATA Employees Enterpreneurs none Professionals none Artisans/shopkeepers Co-helpers none Coop. stockholders none Co.co.co Unemployeds Other inactive All Of all the percipients of self-employment incomes in the integrated dataset: 13.5% do not report themselves as percipients of self-employment incomes in the survey
98 SELF-EMPLOYMENT INCOMES Figure 1 Frequency distribution of self-employment incomes in the survey and in the final data final 12 survey 10 8 % thousands of euros
99 SELF-EMPLOYMENT INCOMES Figure 1 Frequency distribution of self-employment incomes in the survey and in the final data final 12 survey % The final (i.e. integrated) dataset contains a lower percentage of self-employment incomes in the range 2,000-12,000 per year thousands of euros
100 SELF-EMPLOYMENT INCOMES Figure 1 Frequency distribution of self-employment incomes in the survey and in the final data final 12 survey 10 8 The final (i.e. integrated) dataset contains % 6 and an higher proportion of incomes > 20, thousands of euros
101 FINAL REMARKS SURVEY DATA: miss most secondary self-employment incomes
102 FINAL REMARKS SURVEY DATA: miss most secondary self-employment incomes typical self-employment incomes are less likely to be underestimated w.r.t. tax data
103 FINAL REMARKS SURVEY DATA: miss most secondary self-employment incomes typical self-employment incomes are less likely to be underestimated w.r.t. tax data however, when they are lower than tax data, the difference is about 50% (about 2/5 of matching records)
104 FINAL REMARKS TAX DATA: do not always match the EU SILC definition
105 FINAL REMARKS TAX DATA: do not always match the EU SILC definition Because: 1. NON TAXABLE INCOME IS NOT ALWAYS REPORTED IN THE TAX RETURN
106 FINAL REMARKS TAX DATA: do not always match the EU SILC definition Because: 1. NON TAXABLE INCOME IS NOT ALWAYS REPORTED IN THE TAX RETURN 2. SOME SELF-EMPLOYMENT INCOMES (EU SILC definition) ARE CLASSIFIED IN THE TAX RETURN AS (i.e. maybe confused with) CAPITAL INCOMES OF SLEEPING PARTNERS
107 FINAL REMARKS TAX DATA: do not always match the EU SILC definition ordinary self-employment incomes are usually lower w.r.t. survey data (tax avoidance)
108 FINAL REMARKS TAX DATA: do not always match the EU SILC definition ordinary self-employment incomes are usually lower w.r.t. survey data (tax avoidance) when they are lower than survey data, the difference is also about 50% (about 3/5 of matching records)
109 FINAL REMARKS BYFUGLIEN (2001): Multi-country analysis of ECHP [ ] in no country administrative sources alone are sufficient for providing all necessary data for studying all specific aspects of poverty and social exclusion.
110 FINAL REMARKS BYFUGLIEN (2001): Multi-country analysis of ECHP [ ] in no country administrative sources alone are sufficient for providing all necessary data for studying all specific aspects of poverty and social exclusion. A linked survey can also be necessary [ ] to identify non taxable income [ ].
111 FINAL REMARKS BYFUGLIEN (2001): Multi-country analysis of ECHP [ ] in no country administrative sources alone are sufficient for providing all necessary data for studying all specific aspects of poverty and social exclusion. A linked survey can also be necessary [ ] to identify non taxable income [ ]. That is what we has been done for the
INCOME DISTRIBUTION DATA REVIEW ESTONIA
INCOME DISTRIBUTION DATA REVIEW ESTONIA 1. Available data sources used for reporting on income inequality and poverty 1.1. OECD reporting: OECD income distribution and poverty indicators for Estonia are
STATISTICS ON INCOME AND LIVING CONDITIONS (EU-SILC))
GENERAL SECRETARIAT OF THE NATIONAL STATISTICAL SERVICE OF GREECE GENERAL DIRECTORATE OF STATISTICAL SURVEYS DIVISION OF POPULATION AND LABOUR MARKET STATISTICS HOUSEHOLDS SURVEYS UNIT STATISTICS ON INCOME
COUNCIL OF THE EUROPEAN UNION. Brussels, 5 November /01 LIMITE SOC 415 ECOFIN 310 EDUC 126 SAN 138
COUNCIL OF THE EUROPEAN UNION Brussels, 5 November 2001 13509/01 LIMITE SOC 415 ECOFIN 310 EDUC 126 SAN 138 FORWARDING OF A TEXT from : Permanent Representatives Committee (Part 1) to : The Council (Employment
Using registers in BE- SILC to construct income variables. Eurostat Grant: Action plan for EU-SILC improvements
Using registers in BE- SILC to construct income variables Eurostat Grant: Action plan for EU-SILC improvements Version 12/02/2018 1 Introduction In the context of the modernization of European social statistics
Breakdown of key aggregates at the sub-national level
Motivations of the project Breakdown of key aggregates at the sub-national level Poverty risks are unequally distributed within countries across sub-national units. High policy demand for up-to-date information
Social Situation Monitor - Glossary
Social Situation Monitor - Glossary Active labour market policies Measures aimed at improving recipients prospects of finding gainful employment or increasing their earnings capacity or, in the case of
Asset-Related Measures of Poverty and Economic Stress
Asset-Related Measures of Poverty and Economic Stress Andrea Brandolini Banca d Italia, Department for Structural Economic Analysis Silvia Magri Banca d Italia, Department for Structural Economic Analysis
Interaction of household income, consumption and wealth - statistics on main results
Interaction of household income, consumption and wealth - statistics on main results Statistics Explained Data extracted in June 2017. Most recent data: Further Eurostat information, Main tables and Database.
Trends in Income Inequality in Ireland
Trends in Income Inequality in Ireland Brian Nolan CPA, March 06 What Happened to Income Inequality? Key issue: what happened to the income distribution in the economic boom Widely thought that inequality
Challenges in income comparability. Experiences from the use of register data in the Norwegian EU-SILC
Challenges in income comparability. Experiences from the use of register data in the Norwegian EU-SILC Jon Epland Statistics Norway Paper prepared for VII International Meeting on Quantitative Methods
Using the EU-SILC for policy simulation: prospects, some limitations and some suggestions. Francesco Figari Horacio Levy Holly Sutherland
Using the EU-SILC for policy simulation: prospects, some limitations and some suggestions Francesco Figari Horacio Levy Holly Sutherland ISER, University of Essex Draft 26th October 2006 Paper prepared
Basic income as a policy option: Technical Background Note Illustrating costs and distributional implications for selected countries
May 2017 Basic income as a policy option: Technical Background Note Illustrating costs and distributional implications for selected countries May 2017 The concept of a Basic Income (BI), an unconditional
Workshop, Lisbon, 15 October 2014 Purpose of the Workshop. Planned future developments of EU-SILC
Workshop, Lisbon, 15 October 2014 Purpose of the Workshop Planned future developments of EU-SILC Didier Dupré and Emilio Di Meglio 1 ( Eurostat ) Abstract The current crisis has generated a number of challenges
Introduction to the European Union Statistics on Income and Living Conditions (EU-SILC) Dr Alvaro Martinez-Perez ICOSS Research Associate
Introduction to the European Union Statistics on Income and Living Conditions (EU-SILC) Dr Alvaro Martinez-Perez ICOSS Research Associate 2 Workshop overview 1. EU-SILC data 2. Data Quality Issues 3. Issues
Social exclusion, long term poverty and social transfers in the EU: Evidence from the ECHP
Panos Tsakloglou Athens University of Economics and Business, IZA & IMOP and Fotis Papadopoulos Athens University of Economics and Business Social exclusion, long term poverty and social transfers in the
Harmonized Household Budget Survey how to make it an effective supplementary tool for measuring living conditions
Harmonized Household Budget Survey how to make it an effective supplementary tool for measuring living conditions Andreas GEORGIOU, President of Hellenic Statistical Authority Giorgos NTOUROS, Household
Evaluation of ESF. US-EU Exchange on workforce development programmes. Brussels, 04 September Barbara ROUBICEK, DG EMPL
Evaluation of ESF US-EU Exchange on workforce development programmes Brussels, 04 September 2015 Barbara ROUBICEK, DG EMPL Evaluation and Impact Assessment Unit Cohesion Policy 1 Presentation 1. Introduction
Intermediate Quality Report Swedish 2010 EU-SILC
Intermediate Quality Report Swedish 2010 EU-SILC The 2010 cross-sectional component Statistics Sweden 2011-12-22 Table of contents 1. Common cross-sectional European Union indicators... 3 1.1 Common cross-sectional
INCOME DISTRIBUTION DATA REVIEW - IRELAND
INCOME DISTRIBUTION DATA REVIEW - IRELAND 1. Available data sources used for reporting on income inequality and poverty 1.1 OECD Reportings The OECD have been using two types of data sources for income
Intermediate Quality Report for the Swedish EU-SILC, The 2007 cross-sectional component
STATISTISKA CENTRALBYRÅN 1(22) Intermediate Quality Report for the Swedish EU-SILC, The 2007 cross-sectional component Statistics Sweden December 2008 STATISTISKA CENTRALBYRÅN 2(22) Contents page 1. Common
Central Statistical Bureau of Latvia INTERMEDIATE QUALITY REPORT EU-SILC 2011 OPERATION IN LATVIA
Central Statistical Bureau of Latvia INTERMEDIATE QUALITY REPORT EU-SILC 2011 OPERATION IN LATVIA Riga 2012 CONTENTS Background... 5 1. Common cross-sectional European Union indicators... 5 2. Accuracy...
Unemployment and economic crisis: stress
Unemployment and economic crisis: stress testing the welfare systems in Europe Mariña Fernandez, Francesco Figari, Holly Sutherland and Alberto Tumino Università dell Insubria and ISER University of Essex
POVERTY ANALYSIS IN MONTENEGRO IN 2013
MONTENEGRO STATISTICAL OFFICE POVERTY ANALYSIS IN MONTENEGRO IN 2013 Podgorica, December 2014 CONTENT 1. Introduction... 4 2. Poverty in Montenegro in period 2011-2013.... 4 3. Poverty Profile in 2013...
FSO News. Poverty in Switzerland. 20 Economic and social Situation Neuchâtel, July 2014 of the Population. Results from 2007 to 2012
Federal Department of Home Affairs FDHA Federal Statistical Office FSO FSO News Embargo: 15.07.2014, 9:15 20 Economic and social Situation Neuchâtel, July 2014 of the Population Poverty in Switzerland
INCOME DISTRIBUTION DATA REVIEW PORTUGAL
INCOME DISTRIBUTION DATA REVIEW PORTUGAL 1. Available data sources used for reporting on income inequality and poverty 1.1. OECD reporting: OECD income data currently available for Portugal refer to income
MEETING OF PROVIDERS OF OECD INCOME DISTRIBUTION DATA: AGENDA (Version 20 th February 2013)
MEETING OF PROVIDERS OF OECD INCOME DISTRIBUTION DATA: AGENDA (Version 20 th February 2013) OECD Conference Centre, 21-22 February 2013 Room D (21/02 all day and 22/02 until 13.00); Room CC13 (22/02 from
Intermediate Quality Report Swedish 2011 EU-SILC
Intermediate Quality Report Swedish 2011 EU-SILC The 2011 cross-sectional component Statistics Sweden 2012-12-21 1 Table of contents 1. Common cross-sectional European Union indicators... 3 1.1 Common
The at-risk-of poverty rate declined to 18.3%
Income and Living Conditions 2017 (Provisional data) 30 November 2017 The at-risk-of poverty rate declined to 18.3% The Survey on Income and Living Conditions held in 2017 on previous year incomes shows
WORKING DOCUMENT. EN United in diversity EN. European Parliament
European Parliament 2014-2019 Committee on Budgetary Control 24.4.2017 WORKING DOCUMT on ECA Special Report 5/2017 (2016 Discharge): Youth unemployment - have EU policies made a difference? An assessment
Inequality, poverty and the crisis in Greece
Inequality, poverty and the crisis in Greece Manos Matsaganis & Chrysa Leventi Department of International and European Economics Athens University of Economics and Business ETUI Monthly Forum Brussels
INSTITUTO NACIONAL DE ESTADÍSTICA. Descriptive study of poverty in Spain Results based on the Living Conditions Survey 2004
INSTITUTO NACIONAL DE ESTADÍSTICA Descriptive study of poverty in Spain Results based on the Living Conditions Survey 2004 Index Foreward... 1 Poverty in Spain... 2 1. Incidences of poverty... 3 1.1.
Copies can be obtained from the:
Published by the Stationery Office, Dublin, Ireland. Copies can be obtained from the: Central Statistics Office, Information Section, Skehard Road, Cork, Government Publications Sales Office, Sun Alliance
Final Quality report for the Swedish EU-SILC. The longitudinal component
1(33) Final Quality report for the Swedish EU-SILC The 2005 2006-2007-2008 longitudinal component Statistics Sweden December 2010-12-27 2(33) Contents 1. Common Longitudinal European Union indicators based
MONTENEGRO. Name the source when using the data
MONTENEGRO STATISTICAL OFFICE RELEASE No: 50 Podgorica, 03. 07. 2009 Name the source when using the data THE POVERTY ANALYSIS IN MONTENEGRO IN 2007 Podgorica, july 2009 Table of Contents 1. Introduction...
Agenda. Background. The European Union standards for establishing poverty and inequality measures
Workshop on Computing and Analysing Poverty Measures Budapest, - December The European Union standards for establishing poverty and inequality measures Eva Menesi Senior statistician Living Standard, Employment-
Final Quality report for the Swedish EU-SILC. The longitudinal component. (Version 2)
1(32) Final Quality report for the Swedish EU-SILC The 2004 2005 2006-2007 longitudinal component (Version 2) Statistics Sweden December 2009 2(32) Contents 1. Common Longitudinal European Union indicators
The Consistency of Cross-sectional and Longitudinal Data in EU-SILC Countries when Measuring Income Levels, Inequality, and Mobility
The Consistency of Cross-sectional and Longitudinal Data in EU-LC Countries when Measuring Income Levels, Inequality, and Mobility Joachim R. Frick & Kristina Krell
Inequality and Poverty in EU- SILC countries, according to OECD methodology RESEARCH NOTE
Inequality and Poverty in EU- SILC countries, according to OECD methodology RESEARCH NOTE Budapest, October 2007 Authors: MÁRTON MEDGYESI AND PÉTER HEGEDÜS (TÁRKI) Expert Advisors: MICHAEL FÖRSTER AND
Copies can be obtained from the:
Published by the Stationery Office, Dublin, Ireland. Copies can be obtained from the: Central Statistics Office, Information Section, Skehard Road, Cork, Government Publications Sales Office, Sun Alliance
Reconciling Micro and Macro Data on Household Wealth: A Test Based on Three Euro Area Countries
Journal of Economic and Social Policy Volume 15 Issue 2 Article 3 1-1-2013 Reconciling Micro and Macro Data on Household Wealth: A Test Based on Three Euro Area Countries Ilja Kristian Kavonius European
CYPRUS FINAL QUALITY REPORT
CYPRUS FINAL QUALITY REPORT STATISTICS ON INCOME AND LIVING CONDITIONS 2010 CONTENTS Page PREFACE... 6 1. COMMON LONGITUDINAL EUROPEAN UNION INDICATORS 1.1. Common longitudinal EU indicators based on the
CYPRUS FINAL QUALITY REPORT
CYPRUS FINAL QUALITY REPORT STATISTICS ON INCOME AND LIVING CONDITIONS 2009 CONTENTS Page PREFACE... 6 1. COMMON LONGITUDINAL EUROPEAN UNION INDICATORS 1.1. Common longitudinal EU indicators based on the
INCOME DISTRIBUTION DATA REVIEW POLAND
INCOME DISTRIBUTION DATA REVIEW POLAND 1. Available data sources used for reporting on income inequality and poverty 1.1. OECD reporting: OECD income distribution and poverty indicators for Poland are
Impact Assessment (IA)
Title: Abolition of Assessed Income Periods for Pension Credit IA No: Lead department or agency: Department for Work and Pensions Other departments or agencies: Impact Assessment (IA) Date: October 2013
The distribution of wealth between households
The distribution of wealth between households Research note 11/2013 1 SOCIAL SITUATION MONITOR APPLICA (BE), ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS (EL), EUROPEAN CENTRE FOR SOCIAL WELFARE POLICY
Households capital available for renovation
Households capital available for Methodical note Copenhagen Economics, 22 February 207 The task at hand has been twofold: firstly, we were to calculate an estimate of households average capital available
INCOME DISTRIBUTION DATA REVIEW SPAIN 1. Available data sources used for reporting on income inequality and poverty
INCOME DISTRIBUTION DATA REVIEW SPAIN 1. Available data sources used for reporting on income inequality and poverty 1.1. OECD reporting: The OECD series for Spain starts back in the 1980 s and is based
Central Statistical Bureau of Latvia FINAL QUALITY REPORT RELATING TO EU-SILC OPERATIONS
Central Statistical Bureau of Latvia FINAL QUALITY REPORT RELATING TO EU-SILC OPERATIONS 2007 2010 Riga 2012 CONTENTS CONTENTS... 2 Background... 4 1. Common longitudinal European Union Indicators based
Attempt of reconciliation between ESSPROS social protection statistics and EU-SILC
1 EU-SILC methodological workshop (Helsinki): attempt of reconciliation between ESSPROS social protection statistics and EU-SILC Attempt of reconciliation between ESSPROS social protection statistics and
CHAPTER \11 SUMMARY OF FINDINGS, CONCLUSION AND SUGGESTION. decades. Income distribution, as reflected in the distribution of household
CHAPTER \11 SUMMARY OF FINDINGS, CONCLUSION AND SUGGESTION Income distribution in India shows remarkable stability over four and a half decades. Income distribution, as reflected in the distribution of
INCOME DISTRIBUTION AND INEQUALITY IN LUXEMBOURG AND THE NEIGHBOURING COUNTRIES,
INCOME DISTRIBUTION AND INEQUALITY IN LUXEMBOURG AND THE NEIGHBOURING COUNTRIES, 1995-2013 by Conchita d Ambrosio and Marta Barazzetta, University of Luxembourg * The opinions expressed and arguments employed
Advanced Methodology for European Laeken Indicators
Advanced Methodology for European Laeken Indicators New Techniques and Technologies for Statistics Advanced Methodology for European Laeken Indicators Brussels, 23. February 2011 University of Trier, Faculty
Indebted households in the euro area: a micro perspective using the EU-SILC
Indebted households in the euro area: a micro perspective using the EU-SILC 2 nd European User Conference for EU-LFS and EU-SILC Mannheim 31 March-1 April 211 Ramon Gomez-Salvador, Adriana Lojschova and
Online Appendix. Long-term Changes in Married Couples Labor Supply and Taxes: Evidence from the US and Europe Since the 1980s
Online Appendix Long-term Changes in Married Couples Labor Supply and Taxes: Evidence from the US and Europe Since the 1980s Alexander Bick Arizona State University Nicola Fuchs-Schündeln Goethe University
Guide on Poverty Measurement: Chapter 2 Monetary Poverty
Guide on Poverty Measurement: Chapter 2 Monetary Poverty Richard Tonkin Assistant Director Well-being, Inequalities, Sustainability & Environment UNECE Seminar on Poverty Measurement 12-13 July 2016 Introduction
Income Inequality Within and Between European Countries
Thema 4: Income Inequality Within and Between European Countries European User Conference for EU-LFS and EU-SILC Mannheim, 6 th March 2009 Judith Niehues GK SOCLIFE, University of Cologne Introduction
Income Inequality Measurement in Greece and Alternative Data Sources:
Journal of Applied Economics and Business Income Inequality Measurement in Greece and Alternative Data Sources: 1957-2010 Kostas Chrissis *1, Alexandra Livada 2, 1 Department of Statistics, Athens University
Imputed Rents in EU-SILC. Results from Net-SILC2 work package on imputed rents
Imputed Rents in EU-SILC Results from Net-SILC2 work package on imputed rents Meeting of providers of OECD income distribution data Paris 21-22 February 2013 Veli-Matti Törmälehto, Statistics Finland 22/02/2013
EU-SILC USER DATABASE DESCRIPTION (draft)
EUROPEAN COMMISSION EUROSTAT Directorate D: Single Market, Employment and Social statistics Unit D-2: Living conditions and social protection Luxembourg, 15 June 2006 EU-SILC/BB D(2005) EU-SILC USER DATABASE
Measuring poverty and inequality in Latvia: advantages of harmonising methodology
Measuring poverty and inequality in Latvia: advantages of harmonising methodology UNITED NATIONS Inter-regional Expert Group Meeting Placing equality at the centre of Agenda 2030 Santiago, Chile 27 28
Automated labor market diagnostics for low and middle income countries
Poverty Reduction Group Poverty Reduction and Economic Management (PREM) World Bank ADePT: Labor Version 1.0 Automated labor market diagnostics for low and middle income countries User s Guide: Definitions
Exhaustiveness, part 3 Underground Economy 1
Exhaustiveness, part 3 Underground Economy 1 Introduction This paper continues the series dedicated to extending the contents of the Handbook Essential SNA: Building the Basics 2. One of the main themes
Europe 2020 targets: Redening linkages and a modied inequality index
Europe 2020 targets: Redening linkages and a modied inequality index Deniz Sevinc Regional Studies Association Winter Conference 28 Nov 2014 Agenda Rising income inequalities in Europe Modied Inequality
Background Notes SILC 2014
Background Notes SILC 2014 Purpose of Survey The primary focus of the Survey on Income and Living Conditions (SILC) is the collection of information on the income and living conditions of different types
TRADE-OFF BETWEEN TIMELINESS AND ACCURACY
Directorate General Statistics Division General Economic and Financial Statistics Werner Bier and Henning Ahnert * TRADE-OFF BETWEEN TIMELINESS AND ACCURACY ECB REQUIREMENTS FOR GENERAL ECONOMIC STATISTICS
Estimating Zero-Hour Contracts from the Labour Force Survey
Estimating Zero-Hour Contracts from the Labour Force Survey What are zero-hours contracts? Estimates of people working on zero-hours contracts are available from the Labour Force Survey (LFS). A zerohours
Baseline results from the EU28 EUROMOD ( )
EM 3/16 Baseline results from the EU28 EUROMOD (2011-2015) Chrysa Leventi and Sanja Vujackov May 2016 Baseline results from the EU28 EUROMOD (2011-2015) 1 Chrysa Leventi a and Sanja Vujackov a with Silvia
Advancing Methodology on Measuring Asset Ownership from a Gender Perspective
Advancing Methodology on Measuring Asset Ownership from a Gender Perspective Technical Meeting on the UN Methodological Guidelines on the Production of Statistics on Asset Ownership from a Gender Perspective
Eurostat Questionnaire on. Recording of flows and stocks relating to pension schemes in national accounts. August 12, 2003
Eurostat Questionnaire on Recording of flows and stocks relating to pension schemes in national accounts August 12, 2003 i Auxiliary list and instructions Categories of pensions 1) disability pensions
Some reflections on the comments and recommendations on the project Data fusion of EU-SILC and HBS at ISTAT
Some reflections on the comments and recommendations on the project Data fusion of EU-SILC and HBS at ISTAT One of the main issues in the project can be summarized by the following question. Given the
P R E S S R E L E A S E Risk of poverty
HELLENIC REPUBLIC HELLENIC STATISTICAL AUTHORITY Piraeus, 23 / 6 / 2017 P R E S S R E L E A S E Risk of poverty 2016 SURVEY ON INCOME AND LIVING CONDITIONS (Income reference period 2015) The Hellenic Statistical
Prepared by Giorgos Ntouros, Ioannis Nikolalidis, Ilias Lagos, Maria Chaliadaki
GENERAL SECRETARIAT OF THE NATIONAL STATISTICAL SERVICE OF GREECE GENERAL DIRECTORATE OF STATISTICAL SURVEYS DIVISION OF POPULATION AND LABOUR MARKET STATISTICS HOUSEHOLD S SURVEYS UNIT SSTATIISSTIICSS
The impact of the current crisis on the Italian labour market
The impact of the current crisis on the Italian labour market Francesco D Amuri January 27, 2010 Preliminary draft: please do not quote. To be updated with the latest LFS data (2009:3) available shortly.
Tax and fairness. Background Paper for Session 2 of the Tax Working Group
Tax and fairness Background Paper for Session 2 of the Tax Working Group This paper contains advice that has been prepared by the Tax Working Group Secretariat for consideration by the Tax Working Group.
Poverty and Poverty Reduction: Relationship between alternative measures of social spending and poverty rates across countries.
Poverty and Poverty Reduction: Relationship between alternative measures of social spending and poverty rates across countries Koen Caminada Invited Guest Lecture Central University of Finance and Economics,
CYPRUS FINAL QUALITY REPORT
CYPRUS FINAL QUALITY REPORT STATISTICS ON INCOME AND LIVING CONDITIONS 2008 CONTENTS Page PREFACE... 6 1. COMMON LONGITUDINAL EUROPEAN UNION INDICATORS 1.1. Common longitudinal EU indicators based on the
UK Labour Market Flows
UK Labour Market Flows 1. Abstract The Labour Force Survey (LFS) longitudinal datasets are becoming increasingly scrutinised by users who wish to know more about the underlying movement of the headline
Poverty and social inclusion indicators
Poverty and social inclusion indicators The poverty and social inclusion indicators are part of the common indicators of the European Union used to monitor countries progress in combating poverty and social
Using Register information to estimate (early) monthly unemployment rates for EU aggregates
Slide 1 of 22 Session 2: Register-based Social Statistics Using Register information to estimate (early) monthly unemployment rates for EU aggregates Carsten Olsson Eurostat F2 "Labour Market Statistics
1. Poverty and social inclusion indicators
POVERTY AND SOCIAL INCLUSION INDICATORS BASED ON THE EUROPEAN SURVEY ON INCOME AND LIVING CONDITIONS (EU-SILC) IN THE CONTEXT OF THE OPEN METHOD FOR COORDINATION The open method of coordination is an instrument
4 Distribution of Income, Earnings and Wealth
NERI Quarterly Economic Facts Autumn 2014 4 Distribution of Income, Earnings and Wealth Indicator 4.1 Indicator 4.2a Indicator 4.2b Indicator 4.3a Indicator 4.3b Indicator 4.4 Indicator 4.5a Indicator
Gini coefficient
POVERTY AND SOCIAL INCLUSION INDICATORS (Preliminary results for 2010) 1 Poverty and social inclusion indicators are part of the general EU indicators for tracing the progress in the field of poverty and
1. Which foreign entities need to be classified?
1. Which foreign entities need to be classified? Determining whether a non-resident entity is subject to company taxation implicitly answers the previous question of what can be considered to be an entity
Using the EU-SILC to Model the Impact of the Economic Crisis on Inequality
DISCUSSION PAPER SERIES IZA DP No. 7242 Using the EU-SILC to Model the Impact of the Economic Crisis on Inequality Cathal O Donoghue Jason Loughrey Karyn Morrissey February 2013 Forschungsinstitut zur
Creating Labor Market Diagnostics in LICs and MICs
Creating abor Market Diagnostics in ICs and MICs March 2009 otation ational level variables: P- Poverty measure population U number of unemployed in the economy number of economically active (employed
2 USES OF CONSUMER PRICE INDICES
2 USES OF CONSUMER PRICE INDICES 2.1 The consumer price index (CPI) is treated as a key indicator of economic performance in most countries. The purpose of this chapter is to explain why CPIs are compiled
Comment on Counting the World s Poor, by Angus Deaton
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Comment on Counting the World s Poor, by Angus Deaton Martin Ravallion There is almost
Joint Research Centre
Joint Research Centre the European Commission's in-house science service Serving society Stimulating innovation Supporting legislation The use of microsimulation model for fiscal policy analysis: Evidence
Incomes Across the Distribution Dataset
Incomes Across the Distribution Dataset Stefan Thewissen,BrianNolan, and Max Roser April 2016 1Introduction How widely are the benefits of economic growth shared in advanced societies? Are the gains only
Gross-net conversion issues
Conference and Methodological Workshop on "Comparative EU-Statistics and Living Conditions: Issues and Challenges" Gross-net conversion issues Gianni Betti and Vijay Verma Università degli Studi di Siena
Income and Wealth Inequality A Lack of Equity
Income and Wealth Inequality A Lack of Equity Increasing inequality in the distribution of income and wealth is an example of market failure. Resources are not distributed equitably. Income Income is a
Maintaining Adequate Protection in a Fiscally Constrained Environment Measuring the efficiency of social protection systems
Maintaining Adequate Protection in a Fiscally Constrained Environment Measuring the efficiency of social protection systems May 27, 2013 Brussels, Belgium Ramya Sundaram. rsundaram@worldbank.org The World
Final Technical and Financial Implementation Report Relating to the EU-SILC 2005 Operation. Austria
Final Technical and Financial Implementation Report Relating to the EU-SILC 2005 Operation Austria Eurostat n 200436400016 STATISTICS AUSTRIA T he Information Manag er Vienna, 28th September 2007 Table
ILO World of Work Report 2013: EU Snapshot
Greece Spain Ireland Poland Belgium Portugal Eurozone France Slovenia EU-27 Cyprus Denmark Netherlands Italy Bulgaria Slovakia Romania Lithuania Latvia Czech Republic Estonia Finland United Kingdom Sweden
growth but still remains at approximately 1.5% of potential GDP.
THE UK ECONOMY IN FOCUS/APPLICATIONS Reminder of key objectives: Low and positive inflation (inflation rate target of 2%/- 1%) Sustainable growth of real GDP (no target) falling unemployment (no target)
Irish Employment Trends, Competitiveness or Structural Shifts?
Irish Employment Trends, Competitiveness or Structural Shifts? NERI (Nevin Economic Research Institute) Dublin & Belfast Dr. Tom McDonnell Tom.mcdonnell@nerinstitute.net Key Economic Trends, (2007-2013)
Pay rise campaign Minimum wages Minimum wages should not be poverty wages
Pay rise campaign Minimum wages Minimum wages should not be poverty wages Throughout Europe, minimum wages are an established tool of labour market regulation. They play a particularly important role in
Working Group Public Health Statistics
Directorate F: Social Statistics and Information Society Unit F-5: Health and food safety statistics Doc. ESTAT/F5/11/HEA/04 Working Group Public Health Statistics Luxembourg, 28-29 June 2011 Item 5 of
The Purchasing Power Parities pilot project (PPP)
The Purchasing Power Parities pilot project (PPP) Document CARDS/PGSC/2003/06 SECOND CARDS POLICY GROUP ON STATISTICAL CO-OPERATION OF 23 AND 24 OCTOBER 2003 EUROSTAT UNIT A5 CARDS TEAM PURCHASING POWER
Active Labour market policies for the EUROPE 2020-strategy. Ways to move Forward
Active Labour market policies for the EUROPE 2020-strategy Ways to move Forward ALMPs, key components in the EES? Chaired by Ann VAN DEN CRUYCE, Tom BEVERS (EMCO Indicators Group) Sabine GAGEL (EUROSTAT)