HLEG workshop on Measuring Inequalities of Income and Wealth, 15-16 September 2015, Berlin, Germany, More information at: http://oe.cd/hleg-workshop-inequalities-income-and-wealth

1. Towards a system of
Distributional National Accounts
‘Reconciling’ Survey Data with National
Accounts
François Bourguignon
Paris School of Economics
Bertlesmann Fondation, Berlin, Sept. 15
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2. Motivation
• ‘Linking’, more than ‘reconciling’, household survey (HS)
distribution data and National Account (NA)
• Ideally, NA should not only show how the size of the pie
but, ideally, also the shares going to various people
change over time
• An ancestor approach: the ‘Social Accounting Matrix’
(SAM)
• Distributional National Accounts (DNA) would focus on
‘income’ groups rather than ‘social groups’, although
the latter is more easily observable
Question: How to make the ‘link’ between HS and NA??
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3. Outline
1. Basic conceptual differences between NA and HS
2. The under-estimation issue in HS data: to adjust or not
to asjust to NA?
– The example of Chile
– Pragmatic recommendations: don’t adjust but monitor
discrepancies
3. Conclusion: Is it hopeless? Not necessarily so.
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4. National Accounts
Generation of income account All
…
Mixed income gross 15.3
Distribution of income account
Compensation of employees, receivable 77.2
Property income, receivable 27.9
Property income payable 4.3
Social contributions and social benefits,
other than social transfers in kind,
receivable 29.4
Other current transfers, receivable 5.0
Current taxes on income, wealth, etc.,
payable 15.1
Social contributions and social benefits,
other than social transfers in kind,
payable 30.1
Other current transfers, payable 5.3
Disposable income net 100.0
Use of disposable income account
Adjustment of the change in net equity of
households in pension funds 1.6
Final consumption expenditure 89.9
Saving, net 11.7
Capital account
…
Simplified account for households and NPISH
1. Basic conceptual differences between NA and HS
The basic NA framework
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5. National Accounts
Generation of income account All Quintile 1 Quintile 2 Quintile 3 Quintile 4 Decile 9 Vintile 19
Centiles
96-99 Top 1%
…
Mixed income gross 15.3 aq1 aq2 aq3 aq4 ad9 av19 ac96-99 ac100
Distribution of income account
Compensation of employees, receivable 77.2 bq1 bq2 bq3 bq4 bd9 bv19 bc96-99 bc100
Property income, receivable 27.9 cq1 cq2 cq3 cq4 cd9 cv19 cc96-99 cc100
Property income payable 4.3 dq1 dq2 dq3 dq4 dd9 dv19 dc96-99 dc100
Social contributions and social benefits,
other than social transfers in kind,
receivable 29.4 eq1 eq2 eq3 eq4 ed9 ev19 ec96-99 ec100
Other current transfers, receivable 5.0 fq1 fq2 fq3 fq4 fd9 fv19 fc96-99 fc100
Current taxes on income, wealth, etc.,
payable 15.1 gq1 gq2 gq3 gq4 gd9 gv19 gc96-99 gc100
Social contributions and social benefits,
other than social transfers in kind,
payable 30.1 hq1 hq2 hq3 hq4 hd9 hv19 hc96-99 hc100
Other current transfers, payable 5.3 iq1 iq2 iq3 iq4 id9 iv19 ic96-99 ic100
Disposable income net 100.0 jq1 jq2 jq3 jq4 jd9 jv19 jc96-99 jc100
Use of disposable income account
Adjustment of the change in net equity of
households in pension funds 1.6 kq1 kq2 kq3 kq4 kd9 kv19 kc96-99 kc100
Final consumption expenditure 89.9 lq1 lq2 lq3 lq4 ld9 lv19 lc96-99 lc100
Saving, net 11.7 mq1 mq2 mq3 mq4 md9 mv19 mc96-99 mc100
Capital account
…
Simplified account for households and NPISH The ideal distributional account
The ideal DNA
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6. Trying to make NA and HS fit conceptually
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National Accounts
Generation of income account All Quintile 1 Quintile 2 Quintile 3 Quintile 4 Decile 9 Vintile 19
Centiles
96-99 Top 1%
…
Mixed income gross
15.3
Distribution of income account
Compensation of employees, receivable 77.2
Property income, receivable 27.9
Property income payable 4.3
Social contributions and social benefits,
other than social transfers in kind,
receivable
29.4
Other current transfers, receivable
5.0
Current taxes on income, wealth, etc.,
payable
15.1
Social contributions and social benefits,
other than social transfers in kind,
payable
30.1
Other current transfers, payable
5.3
Disposable income net 100.0
Use of disposable income account
Adjustment of the change in net equity of
households in pension funds
1.6
Final consumption expenditure
89.9
Saving, net 11.7
Capital account
…
Simplified account for households and NPISH
Issue of imputed rents, interest or dividend payments not always explicit
Available in household expenditure surveys
Not always clear whether included or not in 'earnings'.
Private pensions, insurance benefit, lottery, …
Marginal
Available in household expenditure survey: available with some detail in
developing countries in SSA, EAP and LAC
Extremely imprecise in household expenditure survey (imprecise too in NA)
Data available in typical household surveys
Not always clear whether included or not in 'net income'. Most often
necessary to simulate on the basis of official schedules but necessary data
not always available
Typically, insurance premium. Available in household expenditure surveys.
The key information in HS
Not always clear this is correctly calculated - e.g. farmers in developing
countries
Isue of the periodicity, ambiguity about inclusion of over time, bonuses, …

7. Other frictions in matching NA and HS
• Incomplete sampling coverage
• Missing (or inconsistent) data or imprecision of some incomes
(self-employment)
• Under- (and over-) reporting of various types
• Different periodicity in reporting income (week/month/year for
earnings), in tax payments or in some social benefits
• Incomplete information to impute taxes and benefits when not
directly reported (problem of the take-up)
• …
• Key warning: NA are themselves far from perfect!! (HH
consumption as a residual, HH income obtained from other
aggregate agent accounts (firms, administrations, ..)
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8. 2. The mean income under-estimation in
HS : to correct or not to correct for it?
a) Evidence on HS under-
estimation:
Ratio of HS income over NA
household consumption
expenditure in Latin America
Country
Bolivia 1.21
Brazil 0.84
Colombia 0.65
Costa-Rica 0.80
Dominican Republic0.48
Ecuador 0.66
El Salvador 0.49
Honduras 1.03
Mexico 0.43
Paraguay 0.98
Peru 0.73
Uruguay 0.71 8

9. Under-estimation in HS and adjustment to NA
• The case of Chile (2011): the CEPALSTAT adjustment
Year 2000 2003 2006 2009 2011 NA HS
Wage and salaries 0.96 1.00 1.01 1.10 1.09 55.3 60.3
Self-employment 1.83 1.98 1.98 2.05 2.05 27.4 15.9
Pensions and benefits 1.47 1.15 1.13 0.98 0.98 7.4 9.0
Property 2.43 1.84 2.14 1.94 3.51 4.8 1.7
Imputed rents 0.45 0.44 0.44 0.42 0.48 5.1 13.1
Total 1.15 1.14 1.15 1.19 1.19 100.0 100.0
Source: Bravo and Valderrama Torres (2011) for 1996-2000, Cepal (2012) for 2003-2011
Table 1. Chile: Household Survey to National Account adjustment factors by income source a)
Structure of total income in
2011 (%)
NA/HS income ratio (all households)
Adjustment rules:
- Adjust all income sources proportionally, except if NA/HS <1
- Exceptions: a) impute all the discrepancy in property income to
the top quintile proportionally to market income; b) adjust imputed
rents proportionally downard 9

10. Rough estimate of the effect of the NA
adjustment in the case of Chile
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Household
survey (HS)
NA-HS
gap as %
of HS total
income
National
Accounts
(NA)
Household
survey
NA-
Adjusted
Chile (2011)
Labor income 76.3 19.9 82.7 0-20% 4.8 4.6
Property income 1.7 3.4 4.8 20-40% 8.5 8.2
Transfers 9.0 0.0 7.4 40-60% 12.2 11.8
Imputed rents 13.1 -5.7 5.1 60-80% 19.1 18.4
Total 100 17.6 100 80-100% 55.5 57.0
Gini 44.8 46.0
Table 2. Inequality effect of adjusting the NA/HS property income gap on the top quintile:
rough calculation on Chile 2011
Aggregate income by source (%) Quintile shares (%)

11. b) To adjust or not to adjust ?
• Adjustment may be more devastating than shown on
previous table (reason why Chile stopped doing it)
• Main issue: there is under-estimation of some income
component but we don’t know how it is distributed
• Proportional adjustment largely arbitrary
• Clearly inappropriate for (absolute) poverty measurement
• Probably inappropriate for inequality measurement
because too much conditioned on a few macro indicators
(capital income , imputed rents) and missing important
counterparts (payable vs. Receivable)
• Besides, isn’t HS better than NA for some income
component –e.g. self-employment?
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12. Should we ignore NA??
• Not really, but the relationship between HS and NA should
be closely monitored.
• Implicit assumption = important bias between mean HS
income and mean NA income but this bias should be more
or less constant
• Any significant departure from past values means: a)
change in NA or HS data collection/definition; b)
potentially a distributional change.
• Monitor the NA/HS ratios, as shown in the case of Chile,
for the various income source. Any big change should
trigger in depth investigation
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13. Monitoring the HS /NA mean ‘income’ ratio
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Country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Bolivia 125.6 107.3 100.7 108.0 108.3 116.9 118.8 117.2 121.4 126.8 126.2 126.6
Brazil 83.8 84.1 85.5 82.0 82.0 83.9 86.1 83.2 83.9 81.7 77.9 81.3
Colombia 49.8 66.7 60.5 63.0 65.5 65.2 68.4 70.8 70.7 66.9
Costa-Rica 80.3 79.5 80.2 74.8 75.6 75.4 80.0 80.2 89.7
Dominican Rep. 92.4 88.1 82.2 69.4 57.6 59.6 56.7 59.3 48.2 54.6 49.4 46.5 49.8
Ecuador 46.6 65.7 86.6 69.9 74.8 75.0 66.3 66.2 70.0 69.2 70.9
El Salvador 57.1 55.6 53.2 53.6 49.1 55.1 52.3 50.5 51.4
Honduras 112.8 93.1 95.1 95.5 90.7 91.7 98.4 102.7 103.4 100.7 98.2
Mexico 43.8 49.0 47.5 43.3 43.0 42.9 43.2 42.3 43.8
Paraguay 143.8 134.0 131.9 122.4 125.5 115.0 117.6 108.2 106.9 98.0 109.8 105.7 105.6
Peru 73.7 81.0 81.4 70.3 67.4 75.8 71.5 72.2 67.3 71.5 74.8 72.7 77.2 77.7 76.1 76.9
Uruguay 75.6 80.3 82.7 82.2 75.6 71.1 69.8 70.3 68.6 68.5 70.9 81.5 74.0 73.0 69.6
Source: Sedlac and WDI, author's calculation
Table 3. Ratio of the mean income in household survey to the mean household final consumption expenditure per capita in National Accounts

14. 3. Is it hopeless? Not necessarily so.
• The real issue is the macro-micro relationship:
– What can we say from the probable impact of macro changes
(NA) on the micro distribution (HS)
• Thus, the point is not about adjusting HS aggregates to NA.
– It is about understanding the relationship between macro
changes (NA) and distributional changes in HS.
• One possible approach is through reduced form
econometrics – OECD type – on short-run inequality
determinants
• A more structural approach should be possible…
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15. A more structural distributional approach
• Using changes in aggregate income sources (as in the
example above) but with more detail:
– wages by skill and sector, farm income, reforms in the tax-benefit
system, changes in relative prices, …
• Also using ‘population’ changes coming with NA account:
level and sectoral structure of employment
• Micro-simulation framework should permit identifying
likely changes in the distribution due to macro evolution
shown by NA.
• ‘Grossing-up’ methods in distributional micro data, CGE-
type and micro-simulation models might be useful tools
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