Indicator 10.4.2 Redistributive impact of fiscal policy

Goal 10: Reduce inequality within and among countries

Target 10.4: Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality

Indicator 10.4.2: Redistributive impact of fiscal policy

March 2018

The Impact of Fiscal Policy on Poverty (see Lustig, 2018, chapter 6).

Kenya National Bureau of Statistics

Director of Statistical Coordination and Methods

Directorate of Statistical Coordination and Methods

Statistical Coordination and Methods

+254-202-911-000

30266-00100, Nairobi- Kenya

dscm@knbs.or.ke

Definitions:

The Redistributive Impact of Fiscal Policy indicator is defined as the Gini Index of pre-fiscal per capita (or equivalized) income less the Gini Index of post-fiscal per capita (or equivalized) income. These terms are elaborated below and can be calculated with some different variations.

Concepts:

-Gini Index: a commonly used measure of inequality capturing the statistical dispersion in the distribution of income over a population (Gini, 1936). A Gini Index of zero expresses perfect equality: that is, every individual in the population has the same income. A Gini Index of 100 expresses Last updated: 2021-02-05

maximum inequality: that is, all income accrues to a single individual, and all other individuals have zero income

Gini Index points: The Redistributive Impact of Fiscal Policy indicator is the difference between pre-fiscal Gini Index and the post-fiscal Gini Index. Thus, if a simple difference is applied the measure is the change in Gini Index points.

Not Applicable

KIHBS 2015/2016 report

Surveys

2015/2016

March 2018

Households

Kenya National Bureau of Statistics

According to the Statistics Act of 2006, Kenya National Bureau of Statistics is mandated to collect, compile, analyze, publish and disseminate official statistics for public use

The Redistributive Impact of Fiscal Policy indicator demonstrates in an accounting framework the total amount by which current income inequality is reduced or increased by the current execution of fiscal policy (including direct and indirect taxes; social insurance and old-age pension contributions; direct cash or near-cash transfers; and subsidies). For example, if the Redistributive Impact of Fiscal Policy is positive, that indicates that the net effect of Fiscal Policy is to reduce the Gini index from what it otherwise would be without Fiscal Policy (in an accounting sense, not as an economic counterfactual). The indicator allows policy makers and the broader stakeholder and advocacy communities to systematically track progress at the country level in the contribution of fiscal policy to more equitable societies.

Reporting on assumptions: The choice of whether to report the Redistributive Impact of Fiscal Policy indicator under the pensions as deferred income or pensions as transfers scenario will be left to the country authority or international agency in charge of submitting this indicator, but the choice must be clearly indicated in the reporting document. For countries for which the data exist, pre-fiscal and post-fiscal inequality should be calculated for both pension scenarios, and the default included in the SDGs database is pension as deferred income. If only data treating pensions as transfers are available, it is recommended to report them only for the working age population (under 65 years of age). Some authorities may also choose to use equivalized income instead of per capita income as the welfare indicator. This too should be clearly indicated in the reporting document. Last, some authorities may report these data based on a micro-data set using income or expenditure as the relevant welfare concept. Once these decisions are taken, they should be maintained in subsequent years in order to assure comparability, except that all countries are encouraged to provide data with pension as Last updated: 2021-02-05

deferred income. The data reported in the UN Global Database try, to the extent possible, to distinguish between the different concepts used for different countries.

Feasibility: The Redistributive Impact of Fiscal Policy indicator can be estimated for any country with a micro-data set detailing incomes or expenditures (or both) at the household or individual level and with a set of fiscal, administrative, or budgetary records detailing public expenditures at the program level and revenue collections at the revenue-collection instrument level.

Suitability/Relevance: The Redistributive Impact of Fiscal Policy indicator provides a direct estimate of the current impact of fiscal policy on redistribution (of incomes). It therefore provides a direct estimate of progress on SDG Target 10.4: “Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equality.”

Limitations: The Redistributive Impact of Fiscal Policy indicator does not address wage policy. It does not include the benefits of public provision of in-kind benefits, such as health, education, sanitation and housing services, which may have both present-day and longer-term impacts on present-day and future inequality.

Pre-fiscal income can be derived from a nationally-representative micro-data set (an Income and Expenditure Survey, for example). Post-fiscal income is estimated via the allocation of the tax burdens and the expenditure-based benefits that stem from fiscal policy (direct and indirect taxes, social contributions, direct cash and near-cash transfers, subsidies, et cetera). Procedures for constructing pre-fiscal and post-fiscal income concepts and estimating their distribution from an underlying microdata set are detailed comprehensively in Lustig (2018) (Chapters 1, 6, and 7).

The Gini Index is calculated rescaling the Gini Coefficient by a factor of 100. The Gini Coefficient is calculated according to standard formulas for a (generalized) Gini Coefficient. See, for example, Duclos and Araar (2006):

where X is a random variable of interest with mean μ(X), F(X) is its cumulative distribution function, υ is a parameter tuning the degree of ‘aversion to inequality’. The standard Gini corresponds to υ = 2. Cov is a Covariance estimate.

Statistics produced undergoes a rigorous process of peer review from Technical Working Groups, data providers and editorial teams

The Bureau employed use of best standards and compilation guides when coming up with the reports

The Kenya National Bureau of Statistics is ISO certified based on 9001:2015 Standard requirements. The processes of compilation, production, publication and dissemination of data, including quality control, are carried out following the methodological framework and standards established by the KNBS, in compliance with the Internationally acceptable standards

The KNBS adheres to Kenya Statistical Quality Assurance Framework (KesQAF) that underlines principles to be assured in managing the statistical production processes and output.

Data consistency and quality checks are conducted through Technical Working Groups (TWGs) before publication and dissemination.

The processes of compilation, production, publication and dissemination of data, including quality control are subjected to a set criteria and standards to ensure conformity.

Data is available on the KNBS website

None

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