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Fiscal Space Profiles of Countries in
Eastern and Southern Africa
Case Study – Kenya Fiscal Space Analysis
May 2017
Table of Contents
3
Abbreviations 5
Executive Summary 7
1 Introduction and methodology 9
2 Macroeconomic and fiscal characteristics 13
3 Kenya’s priority expenditure and fiscal space, FY2013/14-FY2015/16 17
3.1 Historical spending on the priority sectors 18
3.2 Education 20
3.3 Health 21
3.4 Social Protection 23
3.5 Historical analysis of the fiscal space profile 24
4 Kenya’s options for enhancing the fiscal space 27
4.1 Base scenario and fiscal-space “mapping” 27
4.2 Options to increase the fiscal space 28
4.2.1 Increasing tax and non tax revenue 29
4.2.2 Improving budget execution on priority expenditures 34
4.2.3 Increasing external grants for budget support and projects 35
4.2.4 Enhanced GDP growth 36
4.3 Less appropriate options to enhance fiscal space 36
4.3.1 Reducing non-priority expenditure 37
4.3.2 Reducing external-debt service through agreements with creditors 37
4.3.3 Increasing external-debt disbursements 37
4.3.4 Increasing net internal borrowing flows 38
5 Conclusion 39
Annex 1 List of references 41
Annex 2 Fiscal Space projections 43
5
Abbreviations
FSA Fiscal space analysis
FY Fiscal Year
GDP Gross Domestic Product
IMF International Monetary Fund
Ksh Kenyan Shillings
PER Public Expenditure Review
UNICEF United Nations Children’s Fund
US United States
VAT Value-added tax
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Preface
This report is part of a series of country studies carried out by Ecorys and associates for UNICEF in
Eastern and Southern Africa. The project aims to strengthen UNICEF’s advocacy efforts through a
better understanding of the role of political economy factors in processes and decisions around the
creation and use of fiscal space for investments in children.
This report was written by Andrea Dijkstra, Paul Beckerman, Dafina Dimitrova, Gabriele Pinto and
Ivo Gijsberts.
The writers of this report wish to thank the staff from UNICEF Kenya for their support and guidance.
They also express gratitude to the various government officials and other stakeholders who
provided inputs.
The findings, interpretations and conclusions expressed in this report are those of the authors and
do not necessarily reflect the policies or views of UNICEF or of the United Nations. The text has not
been edited to official publication standards, and UNICEF accepts no responsibility for errors. The
designations in this publication do not imply an opinion on legal status of any country or territory, or
of its authorities, or the delimitation of frontiers.
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Executive Summary
Though Kenya has experienced strong economic growth over the last four years, relatively
high external debt, ongoing devolution processes and a relatively high fiscal deficit limit
Kenya’s overall fiscal space. On average, Kenya’s economy has been growing at 5.5% in recent
years. Debt has also increased significantly, from 44% to 54% of GDP between 2013 and 2016,
although the International Monetary Fund (IMF) considers the country to have a low risk of external
debt. Of more serious concern is the overall budget deficit, which has averaged nearly 8% of GDP
since fiscal year (FY) 2008/09. This continuously forces the government to keep both the deficit and
debt under control, which often means limiting government expenditure, including for priority
sectors. Finally, devolution poses challenges in revenue mobilization and budgeting at the county
level largely due to capacity constraints, which adversely affects service delivery.
Among priority sectors – defined as education, health and social protection – government
spending has remained steady, but budget execution rates could be improved particularly in
the health sector. Education typically accounts for the lion’s share of the government’s priority
expenditure. This is evident in the latest FY (2016/17): 26% of the total budget was directed to the
three priority sectors, of which 20.4%% went to education, 3.6% to health, and 2.0% to social
protection, culture and recreation. When looking at spending performance, the education and social
protection sectors were characterized by strong overall absorption rates (91% and 87%,
respectively) based on the latest data (FY2015/16). However, the aggregate figures mask important
differences across spending categories, in particular for education where the budget execution rate
for development spending was under 60%. The health sector similarly underperforms, with an
overall budget execution rate below 70% coupled with significant variations in the level and
efficiency of health spending across counties.
In a baseline status-quo scenario where economic growth is in line with recent trends,
increasing spending on priority sectors based on projected needs will lead to a fiscal-space
financing “gap”. Looking at the spending needs of priority sectors over the medium term, per child
spending would cost an average of US$270 per child through FY2020/21 (based on FY2015/16
prices and exchange rate). The spending requirements translate into an average of 7.3% of GDP
between FY2016/17 and FY2020/21, which is significantly higher than the roughly 6.0% of GDP
average in recent years. Overall, this would to a higher budget deficit, which would rise from 7.6%
to 8.4% of GDP. At the same time, increases in overall expenditure will lead to rising debt (both
internal and external), reaching around 72% of GDP in FY2020/21.
One option to reduce fiscal space gap is to improve tax administration system. An
improvement of 20% in domestic and import VAT tax collection efficiency would increase the tax
revenue/GDP ratio by 0.5% over the projection period. This, in turn, would reduce the government
debt-GDP ratio by 2.7%age points by FY2020/21. In a different scenario that combines improved
VAT administration with increases in staff in the health and education sectors, the additional tax
revenue collected would be sufficient to fund increases in real priority expenditure per child and
would help to reduce the overall deficit. On the other hand, given the relatively smaller proportion of
company income tax revenues, improved corporate tax administration would only result in a modest
increase in the tax revenue/GDP ratio over the projection period.
Strengthening the efficiency of tax administration at the county level could also help to
create fiscal space and reduce the financing gap. With improvements in county tax revenue
collection, the total government debt-GDP ratio would end up at around 65.0% in FY2020/21, an
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improvement of 6.6%age points as compared to the baseline scenario. Another scenario shows
that gains from more efficient county tax collection could be used to fund additional non-recurrent
health spending with only minor implications for fiscal space gap. In addition, assuming that county
tax collection grows at an elasticity of 3 (rather than 2 in the base scenario), this could reduce the
fiscal gap by about 1.5%age points which would be sufficient to fund priority expenditures.
Reducing infrastructure expenditure and taking on more debt are less viable options to
support greater spending on priority sectors. While there might be some potential for enhancing
fiscal space by reducing or improving efficiency in non-priority expenditure, such as in
infrastructure, it is unlikely that this approach is as effective as improving tax administration,
especially given the connection to economic growth. In terms of using current debt arrangements,
non-concessional internal or external borrowing arrangements are not recommended for funding
education and health expenditure given the long-term nature of returns which extend far beyond
this type of debt.
Despite the challenges presented by current debt levels, devolution processes and a high
fiscal deficit, Kenya has options to boost spending on sectors that matter for children.
Continuing efforts to improve tax administration systems at national and county levels can go a long
way to address the fiscal gap in support of greater investments in children. At the same time,
strengthening the efficiency and effectiveness of resources, especially in the health sector, can
immediately lead to much higher levels of expenditure without requiring additional funding, and
thereby contribute to improving the lives of children across the country.
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1 Introduction and methodology
This report describes an analysis of the Kenyan government’s recent and future financial capacity
to carry out expenditure on which children depend for their human development and general
welfare. This financial capacity is understood to be the “fiscal space” for such child-friendly
expenditure. The fiscal space analysis (FSA) has been carried out using a fiscal-projection exercise
in Excel (KeFS.xlsm).1
Definition of ‘priority expenditure’
This chapter refers to expenditure regarded as beneficial to children as “priority” expenditure. For
Kenya, priority expenditure comprises the following three “institutional” expenditure categories:
1. Education;
2. Health;
3. Social-protection.
The composition of the government expenditure defined as priority is, inevitably, somewhat
arbitrary. Government expenditure classified for this report as “non-priority” includes some
expenditure that matters for children’s welfare as well (notably, water and sanitation expenditure),
while expenditure classified in this report as priority includes aspects that are unrelated, or only
loosely related, to children’s welfare (such as higher education expenditure). This is important to
bear in mind when considering whether to reduce non-priority expenditure to increase priority
expenditure. Future analyses of this kind could work with different definitions of priority expenditure.
Even so, the methodological approach this paper describes could work in the same way. That is,
the methodological approach is one of the report`s fundamental recommendations.
It is also important to bear in mind that the fiscal space discussion concerns only the expenditure
carried out by the government within its budget, as reflected in the budget of the respective national
institutions. Government expenditure on education and health plainly constitutes the bulk of the
resources dedicated to education and health in Kenya. Much of this expenditure is in categories
that only the government carries out, or could carry out. Nevertheless, non-governmental and
private expenditure in these sectors is also significant. Especially in the health and social protection
sector, some programmes are entirely donor-funded and not included in the government budget.
Related information on expenditure and funding sources for such programmes has proven
challenging to identify. Thus, the present focus is the expenditure flows in the priority sectors that
flow through Kenya’s fiscal accounts.
An additional point worth bearing in mind is that the expenditure categories – education, health, etc.
– are defined “institutionally” rather than “functionally.” That is, expenditure is classified according to
the government agency that carries it out, rather than the function the expenditure serves. For
present purposes, the functional classification would be preferable, but the such data was not
available in the extent needed to populate the projection model.
Priority expenditure ‘identity’ and analysis
To analyse the fiscal space for priority expenditure, the methodology first sets the “identity” that
governs the relationship of priority spending with its underlying fiscal space.
1 The Excel file is a deliverable under the Terms of reference of the assignment.
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This identity states that total expenditure (comprising current, non-interest, interest, and capital
expenditure) less the sum of total revenue and external grants is equal to the overall deficit, which
is in turn equal to the net flow of external and internal financing. If total expenditure is broken down
into the three categories of (1) priority and (2) non-priority
non-interest expenditure and (3) interest expenditure, this
identity can be rearranged for any year as shown in the box.
The “below-the-line” accounts taken together constitute the
fiscal space for the priority-expenditure flow. For a
retrospective analysis – that is, for analysis of fiscal
performance in historical years – this structure can be applied
directly to show how the below-the-line flows (the
retrospective fiscal space) combined to finance the priority
expenditure flows. Section 1.3 describes the historical
quantitative analysis for Kenya, for the fiscal years (FY)
2013/14-FY2015/16.2
For the projection analysis, the accounting identity is applied in a different way. For each projection
year, the priority-expenditure flow is projected on the basis of programming assumptions,
encompassing the various determinants of recurrent and non-recurrent expenditure in the
education, health, and social protection categories. Similarly, the below-the-line accounts, except
for the net internal financing flows, are projected on the basis of programming assumptions. The
total net internal financing flow for each year is then calculated residually, to ensure that the
accounting identity is satisfied.
For any projection year, this net internal financing flow is the fiscal-space “gap”, that is, the
difference between the projected priority-expenditure flow and the fiscal space. If this gap is “too
large,” then the programming assumptions, taken together, would be considered unfeasible. The
criteria for “too large” include the limits on the government’s capacity to borrow in domestic financial
markets and the implied increase in the government’s debt ratio to Gross Domestic Product (GDP).
Policy-makers would presumably want to evade having the net internal borrowing flow exceed
2-3 per cent of GDP in coming years, to avoid having the internal-debt burden rise as a percentage
of GDP.
The projection exercise is formulated by applying various assumptions, together constituting a
“scenario,” to the historical data base. The relatively simplified, illustrative projection exercise
applies scenarios to historical data (as discussed in Appendix 1). Each scenario comprises
programming assumptions for FY2016/17-FY2020/21, covering:
world economic conditions;
basic Kenyan macroeconomic variables;
merchandise exports and imports;
tax and non-tax revenue;
external grants to the government;
government expenditure in the priority and non-priority categories; and
external and internal debt.
For each scenario, some of the assumptions lines are set as simple numbers (growth rates,
percentages of GDP, etc.). Many of the assumptions, however, are constructed from other
assumptions. For example, the growth rates of real GDP and of the price level are numbers that the
2 The Fiscal Year in Kenya runs from 1 July until 30 June.
Fiscal identity
Priority expenditure
=
Tax and non-tax revenue
+ External grants
- Non-priority expenditure
- External debt service
- Internal interest
expenditure
+ External debt
disbursements
+ Net internal financing flows
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analyst chooses for any given scenario. It is straightforward to combine these assumptions into an
assumed growth rate for nominal GDP.
Organisation of the FSA
The remainder of this chapter is organised as follows. Section 1.2 summarises Kenya’s present
macroeconomic and fiscal circumstances. Section 1.3 briefly describes the recent evolution of the
priority expenditure flows. Section 1.4 discusses various options available to policy makers to
enhance the fiscal space with an illustrative projection exercise for the priority expenditure flows
and the fiscal space that would fund them for FY2016/17-FY2020/21. The exercise consists of a
base scenario, comprising a broad range of macroeconomic and fiscal-policy assumptions, and
various alternative scenarios. Section 1.5 summarises the main findings from the analysis. Further
projection details are included in Annex 1.
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2 Macroeconomic and fiscal characteristics
Kenya’s overall economic performance has been relatively steady in recent years. As Table 2.1
shows, real GDP has grown at a moderate rate since FY2010/11, but per-capita real GDP has risen
steadily. Real growth is estimated to have reached 5.8 per cent in FY2015/16. Given Kenya’s
recent growth experience, it seems reasonable to assume that growth will continue at a rate on
roughly the same order of magnitude. The International Monetary Fund (IMF) has recently
projected that Kenya will grow at an annual rate of 6 per cent over the next few years.3
Table 2.1 Kenya: Selected macroeconomic indicators, FY2010/11-FY2015/16
Fiscal year: 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16
Gross domestic product (US$ m) * 46,787 48,879 51,393 54,217 57,173 60,493
Growth rate (%) 5.1 4.5 5.1 5.5 5.5 5.8
Per-capita:
Gross domestic product (US$
m) ** 1,144.68
1,164.32 1,191.92 1,224.46 1,257.76 1,313.63
Growth rate (%) 2.3 1.7 2.4 2.7 2.7 4.4
Non-government consumption
(US$ m) ** 888.9 928.8 929.9 948.5 1.004.0 1.075.1
Growth rate (%) 4.3 4.5 0.1 2.0 5.9 7.1
Per cent of GDP:
Gross fixed capital formation
(%) 20.1 20.2 20.4 20.4 20.4 19.8
General-government fiscal
surplus (%) -9.3 -4.5 -6.4 -6.1 -8.2 -7.6
Merchandise-trade surplus (%) -15.6 -18.1 -19.0 -20.0 -21.2 -21.1
Growth rate:
Consumer prices (December)
(%)
14.5 10.0 4.9 7.4 7.0 7.0
Exchange rate (December) (%) 9.9 -4.8 0.8 2.5 11.5 3.5
Growth rate:
Population (%) 2.7 2.7 2.7 2.7 2.7 1.3
Population under fifteen (%) 2.5 2.5 2.4 2.3 2.2 1.0
* US$ million at 2016 prices and exchange rate.
** US$ at 2016 prices and exchange rate.
Data sources: Kenya National Bureau of Statistics, Kenya Ministry of Finance, International Financial Statistics, World
Development Indicators.
Kenya’s growth has remained steady for several reasons. Since Kenya is an oil importer, lower oil
prices have eased pressure on the external accounts. Agricultural performance has remained
strong, which is crucial given the importance of agriculture in the economy. Monetary policy has
held inflation to single digits, even after a sharp exchange-rate depreciation in June 2016.
Information technology has contributed to significant real growth in the services economy. The large
3 IMF, Kenya : First Review Under the Twenty-Four Month Stand-By Arrangement and the Arrangement Under the Standby
Credit Facility and Requests for Waivers of Applicability, Rephasing of Disbursements, and Modification of Performance
Criterion-Press Release; Staff Report; and Statement by the Executive Director for Kenya, 2 February 2017,
http://www.imf.org/en/Publications/CR/Issues/2017/02/02/Kenya-First-Review-Under-the-Twenty-Four-Month-Stand-By-
Arrangement-and-the-Arrangement-44607, p. 27.
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number of infrastructure projects has stimulated growth in the construction sector, while the
completion of energy projects has gradually reduced energy costs.
Challenges for the future
Despite this relatively strong growth performance, external debt, the on-going devolution process,
and the relatively high fiscal deficit are important considerations for the future and are likely to
shape the overall fiscal space analysis.
The public debt has been rising as a percentage of GDP, and policy-makers will clearly want to
monitor it closely to ensure that it remains under control. Gross public debt has risen from 44 per
cent of GDP at end-2013 to 52 per cent at end-September 2015. Most recent (2017) IMF estimates
point to debt reaching 54.4 per cent of GDP in 2016.4 Half of the public debt is to external creditors,
although most of this is on concessional terms. Half of the external creditors are multilaterals, while
the other half are bilateral partners. Roughly half of the bilateral lenders are Paris Club creditors;
the other half are others, mainly China (semi-concessional loans).5 As discussed below, the loans
from China for infrastructure development have become politically sensitive. The debt to China has
been rising rapidly, reaching US$821 million in 2014 from US$146 million in 2010.6 Kenya’s
bilateral debt to China is the largest amount it owes any single nation. The commercial financing
component has increased in Kenya’s debt, including sovereign bonds and syndicated loans - Kenya
placed its first sovereign bond in 2014. A Debt Sustainability Analysis done by the IMF early 2016
argues that Kenya still has a low risk of external-debt distress, but that the growth of the external
debt has been high. The IMF expects overall public debt to stabilise around 54–55 per cent of GDP
in 2017–19 and gradually decline thereafter.7
A second source of concern is the devolution effort. Since 2013, Kenya’s national government has
been legally obligated to transfer a minimum of 15 per cent of overall tax resources to the nation’s
47 county governments, to enable them to execute a range of devolved functions. Devolution was
partly introduced in response to widespread political discontent in 2007-2008, which gave
expression to long-standing regional and ethnic disputes. One of the demonstrators’ complaints
was that national-level expenditures provided uneven benefits to Kenya’s different regions, and
devolution was intended to help reverse this. Devolution was also intended to improve the efficiency
and efficacy of public service delivery and to implement the principle of subsidiarity, according to
which expenditure is best allocated and executed at the level it is supposed to affect. Devolution
was one of the main reforms introduced in the new 2010 Constitution.
As in many other countries, implementing devolution in Kenya has been a complex and challenging
process. Some difficulties were inevitable and even predicted, but they added to the pressure on
the public finances. Revenue transfers to counties have been organised straightforwardly and
generally effectively, but revenue mobilisation and administration at the country level is still work in
progress. Budget planning and execution at the county level also requires further efforts, especially
as concerns capital (development) expenditure programs. Current reforms to the procurement
regulations are expected to bring some improvement in this respect. An additional burden has been
the pressure of personnel emoluments.
A third source of concern, closely related to the debt and devolution concerns, is the fiscal
imbalance. The general government deficit averaged 7.6 per cent of GDP over the FY2008/09-
4 IMF, Debt sustainability analysis update, 23 December 2016,
https://www.imf.org/external/pubs/ft/dsa/pdf/2017/dsacr1725.pdf. 5 IMF, Debt sustainability analysis update, 1 March 2016, https://www.imf.org/external/pubs/ft/dsa/pdf/2016/dsacr1685.pdf. 6 Apurva Sanghi and Dylan Johnson, Deal or no deal: Strictly business for China in Kenya? World Bank Policy Research
Working Paper, March 2016, http://documents.worldbank.org/curated/en/801581468195561492/pdf/WPS7614.pdf. 7 IMF, Debt sustainability analysis update, 1 March 2016.
15
FY2014/15. Even though the most recent projections of the IMF are a somewhat lower deficit of 6.9
per cent, this improvement is at least partially the result of significant underspending, albeit some
increase in revenue collection is also at play. There are worrisome signs that the FY2015/16 deficit
will turn out even higher. To keep the deficit within bounds, and therefore ensure that the
government`s debt remains under control, policy-makers may find they will need to not only further
focus on reducing inefficiencies, but possibly also limit expenditure. This outlook conditions the
limitations for the fiscal space for priority expenditure.
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3 Kenya’s priority expenditure and fiscal space, FY2013/14-FY2015/16
Over the years FY2013/14-FY2015/16 Kenya’s priority expenditure and the fiscal-space flows
evolved as shown in Table 3.1.
Table 3.1 Kenya: Priority expenditure and its fiscal space (per cent of GDP), FY2013/14-FY2015/16
Fiscal year (FY) 2013/14 2014/15 2015/16
Per cent (%) of GDP:
Total priority expenditure: 6.0 5.7 6.2
Total education expenditure 5.0 4.7 4.9
National government 4.6
Other government 0.2
Total health expenditure 0.7 0.6 0.8
National government 0.7
Other government 0.2
Total social-protection expenditure 0.3 0.4 0.4
National government 0.4
Other government 0.0
Overall fiscal space: 6.0 5.7 6.2
Tax and non-tax revenue (excl. external grants) (+) 19.2 19.0 19.7
External grants (+) 0.5 0.5 0.5
Total non-priority non-interest expenditure (-) -17.6 -16.5 -19.0
External-debt disbursements (+) 2.6 5.2 4.9
External debt service (-) -0.8 -1.9 -1.1
Net internal financial flows (incl. internal interest) (+) 2.2 -0.5 1.2
Per-child expenditure (US$ at 2016 prices and exchange rate):
Total priority non-interest expenditure: 174.76 171.81 194.68
Total education expenditure 144.72 141.95 155.03
National government 149.24
Other government 5.79
Total health expenditure 20.10 17.87 26.36
National government 20.85
Other government 5.51
Total social-protection expenditure 9.94 11.99 13.29
National government 13.28
Other government 0.01
Data source: Office of the Controller of Budget, Central Bank of Kenya, Ministry of Finance, International Financial Statistics.
As explained in section 1.1, the fiscal space for priority expenditure comprises all the components
of the fiscal accounts. Logically, increases in tax and non-tax revenue, external grants, external
loan disbursements, and net internal financing flows enhance the fiscal space, while increases in
non-priority expenditure and external-debt service diminish the fiscal space. In what follows, the
discussion of the retrospective and prospective fiscal space is structured on this principle.
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3.1 Historical spending on the priority sectors
In the period FY2013/14-FY2015/16, the structure of priority expenditure as defined for present
purposes has remained steady in terms of GDP, ranging between 5.7 and 6.2 per cent. Total real
expenditure per child has been relatively steady over the three years, with a modest decline in
FY2014/15 followed by a substantial rebound in FY2015/16. Education expenditure has
consistently accounted for about 80 per cent of total priority expenditure while health expenditure
has remained at just over 10 per cent. One of the clear objectives of the devolution policy has been
to enable county administrations to increase spending on public health and on construction and
operation of clinics, hospitals, and other medical facilities (including pharmaceutical supply
facilities). It is therefore probable that devolved expenditure on health, which currently comprises
around a quarter of the counties’ total actual spending, would be more likely to address children’s
needs. Social protection is the smallest of the three “priority” sectors, with such expenditure being
between 0.3 and 0.4 per cent of GDP over the period FY2013/14-FY2015/16.
Budget Statements in recent years have promised that education, health and social protection
expenditure would be prioritised, but it is difficult to say for sure that this has turned out to be the
case. “Taken as a whole, the budget for Financial Year 2016/17 will focus on enhancing support to
social sectors (social protection, health and education). These will continue to receive the bulk of
budgetary resources, especially education and health sectors. The social sectors will receive 29.8
per cent of total discretionary expenditures,” says National Treasury in its plans.8 These three
sectors indeed received around 29 per cent in the approved Budget Policy Statement. However, the
final tabled estimates for the budget FY2016/17 showed that 26 per cent of the funds were
allocated to these three sectors.9 Education received 20.4 per cent, Health 3.6 per cent and Social
Protection, Culture and Recreation 2 per cent.
When it comes to budget execution, like most sectors, the priority sectors, and in particular the
health sector, have been unable to fully absorb the funds they had been originally allocated. For
FY2015/16 the actual expenditure in the health sector was 68.5 per cent of the budgeted amount
(see Figure 3.1). Whereas this represents a deterioration from the previous year, when health
spending was 70.7 per cent, absorption rates for both education and social protection have actually
improved. Actual spending for education reached 90.7 per cent of the budget allocation, and for
social protection this figure was 86.5 per cent. Importantly though, these figures mask a significant
difference between absorption of recurrent and development expenditures, in particular for
education. In FY2015/16, actual development spending in education only reached 59.1 per cent of
the allocation.
8 Brian Ngugi, Next budget to focus more on education, health sectors, Daily Nation, 2 February 2016,
http://www.nation.co.ke/business/Next-budget-to-focus-more-on-education-and-health-sectors/996-3057980-
4028tn/index.html. 9 John Kinuthia and Jason Lakin, Kenya: Analysis of the 2016/17 National Budget Estimates, June 2016,
http://www.internationalbudget.org/wp-content/uploads/ibp-kenya-analysis-of-2016-17-national-budget-estimates-6-
2016.pdf.
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Figure 3.1 Comparison of Overall Sector Budget Allocations and Expenditure for FY2015/16 for both
Development and Recurrent Expenditure (in Ksh. Billion)
Data source: Report of the Controller of Budget on the FY2015/16.
The priority sectors differ in terms of devolved functions. The education sector remains essentially a
national government function. Only the relatively small early-childhood functions and vocational
education programs have been devolved. The opposite is true for the health sector: here, counties
are made responsible for the service delivery, which is estimated to be about 40 per cent of the
entire health budget. Social protection is a relatively smaller sector, with no significant functions
devolved. Figure 3.2 provides an overview of the division of tasks between national and county
governments for the three sectors.
Figure 3.2 Overview national and devolved functions
Below a brief past spending profile is presented for the three selected sectors.
31.2
61.7
323.9
2742.3
293.8
0
50
100
150
200
250
300
350
Social Protection, Cultureand Recreation
Health Education
Ksh
. b
illi
on
20
3.2 Education
Education is by far the largest of the three priority sectors of child-friendly expenditure. For
FY2015/16 it received 21.7 per cent of the allocated national budget. In the current budget for
FY2016/17, 20.4 per cent is again allocated to education. Of the total FY2015/16 budget for
education, 6.2 per cent was allocated to development or capital expenditure, whereas the large
share of resources goes to fund recurrent expenditure.
Table 3.2 Budget estimates and outturn in the education sector FY2015/16 (Ksh. Billions)
Education
sector
FY2015/16
Development expenditure Recurrent expenditure Total
Rev
gross
estimate
Expendit
ure
(actual)
Expend
iture
rate
Rev
gross
estimate
Expendit
ure
(actual)
Expend
iture
rate
Rev
gross
estimate
Expendit
ure
(actual)
Expend
iture
rate
Ksh. Billions % Ksh. Billions % Ksh. Billions %
State
Department
for Education
8.4 3.4 40.5 58.7 53.1 90.5 67.1 56.5 84.2
State
Department
for Higher
Education,
Science
and
Technology
11.9 8.6 72.3 58.3 53.1 91.1 70.2 61.7 87.9
Teachers
Service
Commission
0.1 0 0.0 186.5 185.8 99.6 186.6 185.8 99.6
Total 20.3 12 59.1 303.6 281.7 92.8 323.9 293.7 90.7
Data source: Report of the Controller of Budget on the FY2015/16.
Regarding allocations to sub-sectors (primary, secondary and tertiary education), analysis of
expenditure figures that consider recurrent expenditure on teachers at each of those levels
demonstrate that primary education receives the highest share of resources. The allocations to
primary education and primary teachers are about 42 per cent, to secondary education and
secondary school teachers 27 per cent, and to university education and tertiary school teachers 23
per cent. This finding is in line with a recent study on education spending in Kenya10, which also
finds that per-child spending on education has increased faster than the population in school age,
while total spending has almost doubled in market prices between 2010 and 2015. This suggests
that spending per child has increased in real terms. The study also emphasises the relative stability
of budget allocations in this sector and the fact that it assumes more than a quarter of total
domestic revenues, which underlines its priority status for the country’s development.
As shown in Figure 3.2, counties have responsibility for pre-primary education. It is estimated that
on average, counties spent 1.3 per cent of their recurrent expenditures and 3.2 per cent of their
development expenditures on this area, but large variations exist.
Finally, it is worth noting the key role of development partners regarding education funding.
Appropriations-in-aid are included in the budget for FY2016/17. This gives an indication of the
amount of donor funding, although no recent figures of actual disbursements are available. Looking
at the FY2016/17 budget, the appropriations-in-aid amount to Ksh 25.5 billion or 7.5 per cent of the
10 OPM, Analysis of Kenya’s expenditure in education, future sector cost scenarios and benefits of curriculum reform, 2016.
21
total education budget. The absolute contribution of aid is higher for the recurrent aid budget (Ksh
18.3 billion) compared to the appropriations-in-aid to the development budget (Ksh 7.2 billion). In
relative terms, aid makes up 5.8 per cent of the allocations to the education recurrent budget and
29.7 per cent of the allocations to the education development budget. The noted inefficiencies for
the education development budget that are demonstrated by the low absorption rate are not likely
to bypass aid-funded development expenditure. This increases the chances for such funding to be
reconsidered, and in turn this may put more pressure on the education budget financed through
domestic revenue.
In sum, given the historical and current allocations and performance in the education sector, it is
doubtful whether there is room for additional budgetary increases. It seems more likely that
additional fiscal space could be achieved through eliminating inefficiencies within the sector.
3.3 Health
Looking at the level of expenditures in FY2013/14-2015/16, health appears to be less a priority
when compared to education. At the national level, the sector was allocated Ksh 61.7 billion (4.1
per cent of the total budget) in the budget for the FY2015/16.
Table 3.3 Budget estimates (development and recurrent estimates) and outturn development and
recurrent actual expenditures) in the health sector FY2015/16 (Ksh billions)
Health Sector’s Programme Performance FY2015/16 (Ksh. Billions)
Ministry of Health Estimates Actual expenditures
Dev. Est. Rec.
Est.
Total
gross. Est
Share of
total
Dex.
exp
Rec.
Exp.
Total
Exp.
Share
Ksh. Billion % Ksh. Billion %
Preventive & Promotive
Health Services
6.9 1.8 8.7 14% 2.5 1.7 4.2 10%
Curative Health Services 7.9 16.2 24.1 39% 6 13.1 19.1 45%
Health Research and
Development
0.3 5.2 5.5 9% 0.3 4.4 4.7 11%
General Administration
Planning & Support services
9.9 5.9 15.7 25% 3.6 5.9 9.5 22%
Maternal and Child Health 7.7 0.04 7.7 12% 4.7 0.04 4.8 11%
Total 32.5 29.2 61.7 100% 17.1 25.2 42.3 100%
Source: Office of the Controller of Budget, Annual National Government Budget Implementation Review Report FY15/16.
Actual expenses were Ksh 42.3 billion, reflecting an absorption rate of 69 per cent. The absorption
rate is higher for recurrent expenditures (86.3 per cent), which make up about half of the health
budget. The development spending has an execution rate of 52.6 per cent, which is lower than in
the previous FY (54 per cent). This points out to significant inefficiencies, most probably related to
lack of capacity. Although unconfirmed, allegations of mismanagement of resources by the Ministry
of Health may be another important explanatory factor in this respect. Most funds (39 per cent) are
allocated on curative health services, while preventive services assume 13 per cent of the total
budget allocation to the Ministry of Health (Table 3.4).
Table 3.4 Budget allocation to the health sector FY2016/17 (Ksh Billions)
Ministry of Health Recurrent Development Total Share
Ksh. Billions %
Preventive, Promotive & RMNCAH 1.53 6.06 7.59 13
22
Ministry of Health Recurrent Development Total Share
Ksh. Billions %
National Referral & Specialized Services 16.55 7.03 23.58 39
Health Research and Development 5.39 0.21 5.60 9
General Administration, Planning & Support
Services
5.48 9.94 15.42 26
Health Policy, Standards, and Regulations 0.05 8.04 8.09 13
Total 28.99 31.28 60.27 100
Source: Republic of Kenya, 2016/2017 Programme Based Budget of the National Government of Kenya for the Year ending 30th
June, 2017.
Health is now largely a devolved function, however the report at hand could not obtain consolidated
county-level data on actual expenditures on health at that level.11 It has been argued that it is
difficult to collect exact numbers on the expenditures of counties, because counties use a different
administrative classification in their budgets: while some have a separate department for ‘health
services’, others combine it in an administrative unit called ‘health and sanitation’, etc. However, an
impression can be given on the allocations and expenditures of the counties based on the figures
included in the latest Annual County Governments Budget Implementation Review Report
FY2015/16 by the Office of the Controller of the Budget. An analysis of the allocated and executed
budget for respective departments12 demonstrates that counties budget 23.7 per cent on average of
their funds for health, while actual spending is slightly higher at 24.4 per cent. However, there is
wide variation among counties, ranging from a budget allocation of only 4 per cent of total budget to
health (Bomet) to as high as 35.6 per cent (Embu). In terms of actual expenditures, the difference is
even larger: Nyeri spent as much as 40.9 per cent of its budget on health, while in Taita Taveta this
was only 3.7 per cent.
Counties allocate on average three-quarters (74 per cent) of their budget to recurrent costs, and the
remaining (26 per cent) to development expenditures. Again, the balance differs per county: three
counties allocate even more than half of their budget to development expenditures. The absorption
rate of the recurrent budget is 90 per cent on average; for the development budget this is 61 per
cent. This indicates that counties have encountered pronounced difficulties in absorbing available
funding and planning for its efficient and effective use.13
Those findings are in line with a 2015 budget analysis done for six counties that also concludes
substantial variation in health spending between counties.14 Importantly, this study also examines
the respective health needs in the county and notes that the observed variation cannot be
explained by differences in sectoral health needs. This suggests prioritisation problems in certain
areas. It is important to realise that the counties are under no obligation to reserve a specific part
for health. Nor do they work on the basis of costed policies.
Finally, it is important to note that a significant part of the health sector is funded by donors outside
the government budget.15 The Public Expenditure Review (PER) estimates that donors fund about
one-third of the total health spending, focusing on a few diseases and providing aid largely off-
11 The Health PER and Social Sector Budget Analysis commissioned by UNICEF which is currently being drafted will provide
more insight. 12 Such departments are mainly named “health”, “health services”, “health and sanitation”, “medical services and public
health”. 13 Taylor Williamson and Aaron Mulaki, Devolution of Kenya’s Health System: the role of HPP, Brief, Health Policy Project,
RTI International, January 2015, http://www.healthpolicyproject.com/pubs/719_KenyaDevolutionBrief.pdf. 14 J. Mutua, R. Muya and D. Otieno, Child Budget Analysis in Kenya: National Government and Six County Governments,
Institute of Economic Affairs (IEA), May 2015. 15 World Bank, Decision Time: Spend More or Spend Smart? Kenya Public Expenditure Review (PER), Volume 1, December
2014.
23
budget.16 Examples are the large share of donor funds in the Kenya Expanded Programme on
Immunization – which raises questions about the sustainability of this programme.17 As most donor
funds are provided off-budget, it at times interferes with the overall priority setting. Donors tend to
work more with non-governmental organisations than with the government, which is not beneficial
to comprehensive management of the sector and at times results in overlaps.
In all, it is plainly difficult for the Kenyan authorities to determine expenditure needs in the health
sector, and this inevitably complicates budgeting, financing, and multiannual planning. The
problems of absorption at both national and county level for the development budget suggest that
there is significant room for improvement within the current budgetary envelope. However, the large
variations in spending at the county level hint that there may be significant additional funding needs
and allocative inefficiencies.
3.4 Social Protection
Compared to the previous two sectors, the social protection sector is rather small. It is for a large
part funded by donors. In the latest annual report of the Office of the Controller of Budget
(FY2015/16), social protection is reported upon as part of the Ministry of Labour, Social Services
and Security (the previous name of the Ministry). The total budget allocated to social protection was
Ksh 24.5 billion (1.6 per cent of the total government budget); total actual expenditure was Ksh 20.4
billion (1.8 per cent of total government spending). Despite its small size, the sector has benefitted
from annual increases in allocated funds for the last three financial years.
The bulk of the funds is allocated to the national social safety net. The increase in budget over the
years has also been mainly attributed to the scaling up of cash transfer programmes.18
Table 3.5 Budget allocation to the social protection sector FY2016-17 in Ksh Billion
Allocated budget FY2016-2017 ( Ksh Billion) Rec. budget Dev. Budget Total
State Department for Social Protection 8.11 14.82 22.93
Social Development and Children Services 3.01 0.85 3.86
Social Welfare and vocational
rehabilitation
1.11
Community Mobilization and
development
0.15
Child Community Support Services 2.16
Child Rehabilitation and Custody 0.44
National Social Safety Net 5.05 13.97 19.01
Social Assistance to Vulnerable Groups 19.01
General Administration Planning and
Support Services
0.05 0.004 0.05
Source: Republic of Kenya, 2016/2017 Programme Based Budget of the National Government of Kenya for the Year ending 30th
June, 2017.
A small part of the budget of the State Department for Social Protection consists of appropriations
in aid: Ksh 45,175,000 (2 per cent). However, some donors are involved in assistance to social
protection that may not be fully reflected in the aid figures in the budget, such as UNICEF, the
16 Ibidem. 17 Mutua et.al., Child Budget Analysis in Kenya, 2015, p. 23. 18 Republic of Kenya, 2016/2017 Programme Based Budget of the National Government of Kenya for the Year ending 30th
June, 2017.
24
Swedish International Development Cooperation Agency (SIDA), DFID, the World Bank and the
World Food Programme.19 This suggests further expansion of the funds is still necessary. The total
amount of donor support to social protection, and what its proportion is to government support, is
not known. Some reports mention that social protection programmes are highly donor-dependent.20
3.5 Historical analysis of the fiscal space profile
Examining the historical data of the fiscal components other than the priority expenditure helps to
understand quantitatively how the various fiscal-space components “contribute” to the growth of the
priority expenditure. Since the priority-expenditure flow is equal to the sum of the various fiscal-
space components, the growth rate of the real per-child year-over-year priority-expenditure flow can
be analysed as the sum of the real per-child “contributions” from the fiscal-space components.
In any year, the “contribution” of each fiscal-space component to the growth rate of real per-child
priority expenditure is defined as the product of (1) the ratio of the value of the preceding year’s
component to the preceding year’s total priority expenditure and (2) the growth rate of the
component. Each contribution indicates how much that component contributed to (or subtracted
from) the growth rate of priority expenditure. The sum of all the fiscal-space contributions is equal to
the growth rate of priority expenditure.
Unfortunately, historical data for Kenya’s priority-expenditure flow and fiscal space are complete
only for the three years FY2013/14, FY2014/15 and FY2015/16, and so the contribution analysis
can be carried out only for the two years FY2014/15 and FY2015/16. Table 3.6 shows the
contribution analysis for the two years.
Table 3.6 Kenya: Contributions of fiscal-space components to the real per-child growth rate of priority
expenditure, FY2013/14-FY2015/16
Fiscal year (FY) 2013/14 2014/15 2015/16
Growth rates (%):
Total priority non-interest expenditure: -4.9 8.2
Participation in the growth of total priority expenditure:
Total education expenditure -4.2 3.6
Total health expenditure -1.6 4.2
Total social-protection expenditure 1.0 0.4
Contribution to the growth of total priority expenditure:
Tax and non-tax revenue (excl. external grants) (+) -3.7 12.0
External grants (+) -0.1 -0.7
Total non-priority non-interest expenditure (-) 17.5 -41.2
External-debt disbursements (+) 43.2 -5.2
External debt service (-) -17.6 14.8
Net internal financial flows (incl. internal interest) (+) -44.1 28.7
Growth rates:
Total priority non-interest expenditure: -4.9 8.2
Total education expenditure -5.1 4.3
Total health expenditure -13.9 40.8
19 UNICEF, Kenya launches a Single Registry to strengthen social protection, 14 September 2016,
https://www.unicef.org/kenya/reallives_18743.html. 20 SOLIDAR, Kenya: Social Protection Monitoring, Country Study, April 2016.
25
Fiscal year (FY) 2013/14 2014/15 2015/16
Growth rates (%):
Total social-protection expenditure 16.8 5.9
Overall fiscal space: 0.0 0.0
Tax and non-tax revenue (excl. external grants) (+) -1.2 3.6
External grants (+) -1.4 -8.7
Total non-priority non-interest expenditure (-) -6.0 14.3
External-debt disbursements (+) 99.9 -5.7
External debt service (-) 126.3 -44.5
Net internal financial flows (incl. internal interest)
(+)
-121.8 -345.7
Per cent (%) of total priority expenditure:
Total priority non-interest expenditure: 100.0 100.0 100.0
Total education expenditure 82.8 82.6 79.6
Total health expenditure 11.5 10.4 13.5
Total social-protection expenditure 5.7 7.0 6.8
Overall fiscal space:
Tax and non-tax revenue (excl. external grants) (+) 318.5 330.8 316.8
External grants (+) 8.3 8.6 7.3
Total non-priority non-interest expenditure (-) -292.2 -288.8 -305.0
External-debt disbursements (+) 43.2 90.8 79.1
External debt service (-) -13.9 -33.2 -17.0
Net internal financial flows (incl. internal interest)
(+)
36.2 -8.3 18.8
Data source: Office of the Controller of Budget, Central Bank of Kenya, Ministry of Finance, International Financial Statistics.
In real per-child terms, priority expenditure diminished 4.9 per cent in FY2014/15 but then grew
8.2 per cent in FY2015/16. Table 1.7 shows how the growth in the various components of the fiscal
space contributed to the growth of per-child priority expenditure:
The contribution of tax and non-tax revenue was negative for FY2014/15, however the trend
reversed in FY2015/16 with a strong positive performance of 12 per cent, which was
substantially higher than the growth rate of priority expenditure;
The contribution of external grants was negative in both FY2014/15 and FY2015/16, but was
small in both years;
Non-priority expenditure diminished in per-child real terms in FY2014/15, and so its
contribution was actually positive in this FY. In FY2015/16, expenditure on infrastructure
increased (largely financed by the external financing) proceeds), and so in that year the
contribution to priority expenditure was strongly negative;
Largely because of the (external financing) issue, the contribution of external-debt
disbursement was strongly positive in FY2014/15, but then slightly negative in FY2015/16;
The contribution of external-debt service was negative in FY2014/15. Since the total flow
diminished in FY2015/16, however, it contributed positively in FY2015/16;
Finally, the contribution of net internal debt was significant in both years, but negative in
FY2014/15 and positive in FY2015/16.
In evaluating these figures, it is important to bear in mind that the FY2015/16 fiscal-accounts figures
are still preliminary. Revised figures could significantly change the FY2015/16 contribution patterns.
In any case, it is unclear how much the recent past will serve as a meaningful guide to the future
evolution of the fiscal space. For reasons discussed in the following section, potential sources of
26
future additional fiscal space for priority spending will be largely in the area of tax revenue, through
improved administration. The next section considers the most likely future sources of enhanced
fiscal space.
27
4 Kenya’s options for enhancing the fiscal space
The first part of this section discusses a multiannual projection of Kenya’s fiscal space under a set
of “base-scenario” assumptions (Appendix 1 describes these assumptions in detail). This scenario
embodies the idea that government policy will continue along present lines while real GDP
continues to grow at a 6 per cent annual rate. The next part of this section describes some options
for enhancing the fiscal space, and describes the consequences of applying these options by
setting out alternative projection scenarios. Each option takes account of Kenya’s specific
circumstances. It is nevertheless important to remember that all the projection results are based on
specified, quantitative programming assumptions, and in no case should be regarded as forecasts.
The final part of the section discusses some options that are probably not viable in present
circumstances but are part many governments’ fiscal-reform approaches.
4.1 Base scenario and fiscal-space “mapping”
Appendix 1 describes the base scenario’s programming assumptions and the projection results.
The real-GDP growth rate is assumed to rise gradually from 5.8 per cent in FY2016/17 to 6 per cent
in FY2020/21. Most of the remaining programming assumptions are intended as “neutral”, non-
controversial, base-line assumptions that would produce no significant changes in the fiscal
structure as the real economy grows. The results of the base scenario provide a basis of
comparison with alternative scenarios incorporating some assumptions different from those of the
base scenario.
Under the projections resulting from the base-scenario assumptions, overall priority expenditure
would average 7.3 per cent of GDP over the years FY2016/17-FY2020/21. Total priority
expenditure would average US$269.90 per child at FY2015/16 prices and exchange rate. Under the
base-scenario assumptions regarding tax and non-tax revenue, external grants, non-priority
expenditure, and external- and internal-debt stocks and flows, the projected priority-expenditure
flows would produce a fiscal-space financing “gap” that would have to be covered with internal
financing. The required internal-financing flow would average 5 per cent of GDP. This would
undoubtedly be higher than policy-makers would prefer: it would exceed the FY2008/09-FY2015/16
average of 4.1 per cent. Even with the diminished financing requirement, the government’s total
external and internal debt would rise from an estimated 58.6 per cent of GDP at the end of
FY2015/16 to 71.6 per cent of GDP.
These figures are indicative of the fiscal-adjustment effort the authorities now face. To increase
priority expenditure by more than the base scenario assumes while limiting the budget deficit,
policy-makers would need to find ways to enhance their funding sources, improve efficiency in
priority spending, or reduce non-priority expenditure.
The “mapping” of the Kenyan government’s funding sources to its expenditure programs, and its
priority expenditure, can be characterised straightforwardly. The government’s overall funding flows
comprise (1) tax and non-tax revenue, (2) external grants, and (3) the fiscal deficit. The fiscal deficit
comprises the net external and internal financing flows. Over any time interval, total funding flows
identically equal total expenditure flows. Overall expenditure comprises the three broad categories
of (1) priority, (2) non-priority non-interest, and (3) interest expenditure. With just a few exceptions,
28
no category of expenditure can be said to be directly linked with any specific funding source, and no
funding source can be said to be linked with any specific expenditure. The exceptions are that
certain grants and loan disbursements are provided to fund specific project expenditures, and these
would be in specific sectors. Apart from these exceptions, all funding effectively flows into a single
general fund, and this general fund is used for any budgeted expenditure.
Figure 4.1 is a fiscal-mapping chart, with FY2016/17-FY2020/21 projections according to the base
scenario. The projections are set out as percentages of GDP. In the “stacked-bar” presentation,
funding sources are above and expenditure flows below the horizontal axis. The sum of everything
above the horizontal axis funds everything below. By definition, the sum of the net external and
internal financing flows is the same as the overall fiscal deficit. For the base scenario, the
expenditure flows would imply a continuing but moderating deficit, with financing from external and
internal sources. As discussed in Appendix 1, under the base scenario the overall deficit would rise
from 7.6 per cent of GDP in FY2015/16 to 8.4 per cent of GDP in FY2020/21. The net internal
borrowing flow would rise from 3.3 per cent of GDP in FY2015/16 to 5.0 per cent of GDP in
FY2020/21.
Figure 4.1 Mapping of fiscal space profile-base scenario
Source: Estimates and calculations from the projection workbook KeFS.xlsm.
4.2 Options to increase the fiscal space
In principle, policy-makers have the following general options for enhancing the fiscal space for
priority expenditure: (1) increasing tax and non-tax revenue and possibly earmarking some of this
for priority expenditure; (2) reducing spending in priority sectors (possibly by increasing expenditure
efficiency); (3) reducing non-priority expenditure; (4) reducing external debt service through
agreements with creditors; (5) increasing external debt disbursements; and (6) increasing net
internal borrowing flows. Appendix 2 includes an illustrative list with a number of additional high-
level options for increasing the fiscal space. Apart from government policy choices, changes in the
macroeconomic context can affect the fiscal space. For example, increased GDP growth would
increase the fiscal space by increasing tax revenue. The following sub-sections discuss these
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
40.0
2014 2015 2016 2017 2018 2019 2020 2021
% o
f G
DP
Net internal financial flows(incl. internal interest) (+)
External-debt disbursements(+)
External grants (+)
Tax and non-tax revenue(excl. external grants) (+)
External debt service (-)
Total non-priority non-interest expenditure (-)
Total priority expenditure (-)
FUNDING (+)
SPENDING (-)
29
options in the light of the circumstances likely to prevail in Kenya. Whenever feasible, the options
are illustrated with quantitative results from the macro-fiscal projection framework. These alternative
scenarios are intended to be illustrative, and should not be understood as specific policy
recommendations.
4.2.1 Increasing tax and non tax revenue
Like many African economies, Kenya faces the likelihood of somewhat tighter financial conditions in
coming years. Some fiscal adjustment is bound to be necessary, given the rapid recent growth of
public indebtedness. The base scenario assumes that Kenya will maintain its present 6-per-cent
growth rate, but it is unlikely that the rate could go higher. Most Kenyans will still feel a strong sense
of economic pressure. At the same time, Kenya’s political balance remains delicate. In such
circumstances, explicit tax increases are best regarded as politically unfeasible. One exception in
this regard would be that it may be possible to increase some county-level taxes in the context of
decentralisation. At the same time, however, both at the national and at the county level, there is
probably some scope for improvement in tax administration, and this would enhance actual revenue
collection. In general, this may be more politically acceptable, in part because many people regard
improved administration as a matter of fairness and equity.
National level tax revenue and related scenarios
The most promising approaches to increasing tax and non-tax revenue would involve improved
administration of the more basic taxes. The World Bank estimates that Kenya’s “tax gap” – the
difference between what the revenue authorities could collect and what they do collect – is in the
order of 15 per cent.21 A first significant improvement from a tax administration perspective could be
gained by broadening the tax base for income tax collection. The 2014 World Bank PER estimated
that collected revenues from this tax amounts to about half of all revenues, but this is collected from
only 0.34 per cent of registered businesses. Therefore, efforts to improve tax administration - for
example, a stronger focus on compliance for medium-sized taxpayers - could potentially enhance
revenues. This may imply a need for a reorganisation and enlargement of the Revenue Authority to
establish specific units to ensure wider taxpayer registration and assessment, which may require a
substantial increase in required staff numbers (and so increased expenditure).
Among the more basic taxes, many observers focus on the potential for improving value-added tax
(VAT) revenue. As in many developing economies that collect VAT, while the tax has proven
relatively efficient in terms of collection cost, administrative inefficiencies, exemptions, and the large
size of the informal economy - currently estimated at about 70 per cent of overall output - have
undercut revenue generation. According to the World Bank’s 2014 PER, the Kenya Revenue
Authority estimates the VAT collection gap to be more than 20 per cent. Current efforts of the
Kenyan government to enhance VAT and excise collection, including through the introduction of a
new excise law focusing on improving collection on goods for export are already demonstrating
positive results.
Scenario 1 suggests that a realistic improvement in the VAT tax administration could bring about a
significant reduction in the fiscal-space gap. The assumptions of Scenario 1 are the same as those
of the base scenario, except that in Scenario 1 the collection efficiency of domestic and import VAT
would gradually increase by 20 per cent over the projection period. This would improve the average
value of tax revenue as a percentage of GDP over the projection period to 18.2 per cent of GDP,
compared with 17.7 per cent in the base scenario. The increase of about 0.5 per cent in the
average tax revenue/GDP ratio would bring the FY2020/21 total government debt-GDP ratio to
21 The tax gap analysis that the World Bank is currently carrying out with National Treasury could give more insight into
Kenya’s tax potential.
30
68.9 per cent, compared with 71.6 per cent in Scenario 0, a reduction of about 2.7 percentage
points. The fiscal gap, measured by the net internal debt flow, would average 4.4 per cent of GDP
over the projection period, compared with 5.0 per cent in Scenario 0, a reduction of about 0.6
percentage points.
Box A: Improvements from better VAT tax administration
Results Scenario 0 Scenario 1 Variation
Average tax revenue (% of GDP), FY2016/17-FY2020/21 17.7 18.2 +0.5
Average priority expenditure (% of GDP), FY2016/17-FY2020/21 7.3 7.3 =
Average priority expenditure per child (US$ at 2016 prices and
exchange rate), FY2016/17-FY2020/21
US$263.88 US$263.88 =
Net internal debt flow (% of GDP), FY2016/17-FY2020/21 5.0 4.4 -0.6
Total government debt (% of GDP), FY2020/21 71.6 68.9 -2.7
Scenario 2 tries out a higher growth rate of the education and health staff. In the base scenario, the
education staff grows at a rate equal to the growth rate of the child population and the health staff
grows at a rate equal to the overall population growth rate. In Scenario 2 the education and health
staff grow at rates equal to three times the base-scenario growth rates. This would lead, of course,
to an increase in the fiscal-space gap, all other things being equal. The net internal debt flow would
average 5.3 per cent of GDP over the projection period, compared with 5.0 per cent in Scenario 0,
an increase of about 0.3 percentage points. The total government debt-GDP ratio would conclude
FY2020/21 at 72.8 per cent of GDP, compared with 71.6 per cent in Scenario 0.
Box B: Increase growth of health and education staff
Results Scenario 0 Scenario 2 Variation
Average tax revenue (% of GDP), FY2016/17-FY2020/21 17.7 17.6 =
Average priority expenditure (% of GDP), FY2016/17-FY2020/21 7.3 7.5 +0.2
Average priority expenditure per child (US$ at 2016 prices and
exchange rate), FY2016/17-FY2020/21
263.88 272.66 +8.78
Net internal debt flow (% of GDP), FY2016/17-FY2020/21 5.0 5.3 +0.3
Total government debt (% of GDP), FY2020/21 71.6 72.8 +1.2
Scenario 3 simply combines Scenarios 1 and 2, so that a measure of improved tax administration
would help “fund” increases in education and health staffing levels. The net internal debt flow would
average 4.6 per cent of GDP over the projection period, compared with 5.0 per cent in Scenario 0,
a decrease of about 0.4 percentage points. The total government debt-GDP ratio would conclude
FY2020/21 at 70.1 per cent of GDP, compared with 71.6 per cent in Scenario 0. With the specific
numbers chosen for the exercise, the additional revenue deriving from improved administration
would suffice to fund a significant increase in real priority expenditure per child and contribute to
overall deficit reduction.
Box C: Improvements in VAT and increase in growth of health and education staff
Results Scenario 0 Scenario 3 Variation
Average tax revenue (% of GDP), FY2016/17-FY2020/21 17.7 18.2 +0.5
Average priority expenditure (% of GDP), FY2016/17-FY2020/21 7.3 7.5 +0.2
Average priority expenditure per child (US$ at 2016 prices and
exchange rate), FY2016/17-FY2020/21
263.88 272.66 +8.78
Net internal debt flow (% of GDP, FY2016/17-FY2020/21 5.0 4.6 -0.4
Total government debt (% of GDP), FY2020/21 71.6 70.1 -0.5
31
In general, the search for a significant and stable source of funding for enhanced but stable
expenditure in priority sectors is bound to focus on relatively large, national-level revenue flows. In
effect, priority expenditure has a continuing stake in solid, irreversible improvement in the
administration of large, modern taxes such as the VAT and the personal and income taxes.
Thus, Scenario 4 considers an improvement of the administration of the income tax on companies.
This scenario’s assumptions revert to the base scenario, with the single exception that a substantial
effort is made to improve the company-tax administration (possibly including intensified
enforcement, removal of exemptions, and so on). The specific assumption is that the elasticity of
company tax with respect to nominal GDP jumps to 2 in FY2016/17 and gradually declines to 1
over the projection period. Under Scenario 4, the net internal debt flow would average 4.8 per cent
of GDP over the projection period, compared with 5.0 per cent in Scenario 0, a decrease of about
0.2 percentage points. The total government debt-GDP ratio would conclude FY2020/21 at 71.0 per
cent of GDP, compared with 71.6 per cent in Scenario 0, an improvement of 6.1 percentage points.
Given the small relatively size of company income tax revenue flow, the change would produce only
a modest increase to in the tax revenue/GDP ratio over the projection period.
Box D: Improvements from company income tax administration
Results Scenario 0 Scenario 4 Variation
Average tax revenue (% of GDP), FY2016/17-FY2020/21 17.7 17.8 +0.1
Average priority expenditure (% of GDP), FY2016/17-FY2020/21 7.3 7.3 =
Average priority expenditure per child (US$ at 2016 prices and
exchange rate), FY2016/17-FY2020/21
263.88 263.88 =
Net internal debt flow (% of GDP), FY2016/17-FY2020/21 5.0 4.8 -0.2
Total government debt (% of GDP), FY2020/21 71.6 71.0 -0.6
Enhancing county tax collection and related scenarios
Kenya’s Constitution guarantees counties access to several “own” revenue sources. First, as per
Art. 209, they can charge property tax and entertainment tax. Second, counties levy various service
fees, such as market fees, parking, etc. Third, counties can enact local legislation that could enable
them to mobilise further own-source revenues.
It is important to note that in Kenya, as elsewhere, devolution has been a strategy for improved
revenue mobilisation and development at sub-national level.22 Sub-national governments may be
better positioned to identify and prioritise needs of local communities, and thus have the
comparative advantage of delivering public service. 23 Further, tax evasion is likely to be minimised
where tax payments by citizens is closely linked to development agenda at local level.24 Thus,
potentially, counties should be able to maximise own source income generation. In the interviews
conducted for this study, several respondents described county revenue potential as a ‘hidden
goldmine’, as county governments have not yet taken advantage of powers they possess to raise
and collect taxes.
However, recent analyses and current county experience suggests that tax collection at the country
level raises a broad range of issues. First, at present, the most important source of own revenue for
counties is the property tax. The World Bank PER found that income from this tax varies largely per
county, with a range between 1 and 583 Shillings per capita for FY2009/10. The current report of
22 C. Dick-Sagoe, Survey of literature of fiscal decentralization as a sustainable local development tool in Ghana, Journal of
sustainable development in Africa, 14(3) 2012, 228-251. 23 F.C. Enemuo, ‘Problems and Prospects of Local Governance’ (Chapter 7, pp. 181–204), in G. Hyden, D. Olowu & H.
Ogendo (eds) African Perspectives of Governance (Trenton/Asmara: Africa World Press), 2002. 24 K. Westergaard and M.M. Alam, Local government in Bangladesh: Past experiences and yet another try, World
Development 23(4) 1995, 679-690.
32
the Office of the Controller of the Budget indicates that this variation is persisting. Moreover, the
importance of property taxes as a share of locally generated revenues appears to diminish, with
some counties, such as Embu, reporting that it constituted only 5.1 per cent of total own revenues
for FY2015/16, and others, such as Machakos, Kakamega and Nakuru reporting that property taxes
amounted to 40-55 per cent of total own revenue. One possible explanation for this variation is the
absence of up-to-date valuation of property based on an updated register that would allow for a
correct estimation of tax due.
A second issue characterising county tax collection is the reality that actual revenues fall
consistently behind set targets. For FY2015/16, in total counties managed to collect 69.3 per cent of
the annual target. While this is seen as a modest improvement as compared to the 67.2 per cent
collected in the previous year, there is a large amount of variation among counties, with some
falling as much as 80 per cent short of their target. The most probable explanation for these results
is overestimation of potential own-source revenue, as suggested by the World Bank PER. This
could be a consequence of either limited revenue forecasting skills, or of pressure to fit unrealistic
funding demands to budget proposals. This is evident when considering that county governments in
their FY2013/14 budgets proposed to collect four times the amount of revenue local authorities
collected prior to the devolution process.
For present purposes, a plausible scenario for county revenue is that some increase in fiscal space
could be attained through a combination of gains in improved county revenue administration - in
particular forecasting and collection; as well as possible introduction of additional local taxes or re-
prioritisation of current rates of local taxes and service fees. In the absence of detailed data for
specific tax rates and fees, the related quantitative scenario simply assumes that higher county-
level tax collection could be represented by assuming a higher elasticity of overall county-tax
revenue with respect to GDP than the elasticity used in the base scenario.25 A higher elasticity
simply means that each percentage point of the GDP growth rate induces a higher percentage
increase in overall county-tax revenue.
Accordingly, Scenario 5 considers the consequences of improved county tax collection by taking
this “reductive” approach. In the base scenario, county tax collection would grow with an elasticity
of 2 with respect to nominal GDP, while in Scenario 5, county tax collection would grow with an
elasticity of 3 with respect to nominal GDP. Under Scenario 5, the net internal debt flow would
average 3.5 per cent of GDP over the projection period, compared with 5.0 per cent in Scenario 0,
a decrease of about 1.5 percentage points. The total government debt-GDP ratio would conclude
FY2020/21 at 65.0 per cent of GDP, compared with 71.6 per cent in Scenario 0, an improvement of
6.6 percentage points.
Scenario 6 is another “combined” scenario, which considers the combined consequences of
improved county-tax collection and a gradually increased flow of non-recurrent county health
expenditure, from just barely more than 0 per cent of GDP to 3 per cent of GDP in 2021 (compared
with 2 per cent in the base scenario). This specific combination, would produce a modest
deterioration in the fiscal space. The increased county-tax collection would partially fund the
increase in the county-level capital expenditure. With the figures assumed, under Scenario 6 the
net internal debt flow would average 3.5 per cent of GDP over the projection period, compared with
5.0 per cent in Scenario 0, a decrease of about 1.5 percentage points. The total government debt-
25 A more in-depth study could examine county taxes county by county. Obviously, Kenya’s 47 counties have a wide range of
characteristics and circumstances, ranging from densely populated urban areas with large local service needs to sparsely
populated rural areas with different kinds of agricultural production.
33
GDP ratio would conclude FY2020/21 at 73.9 per cent of GDP, compared with 71.6 per cent in
Scenario 0, an increase of 2.3 percentage points.
Box E: Improved county tax collection and higher non-recurrent county health expenditure
Results Scenario 0 Scenario 5 Variation
base
scenario
Scenario 6 Variation
base
scenario
Variation
Scenario
5/6
Average tax revenue
(% of GDP),
FY2016/17-
FY2020/21
17.7 19.0
+2.3 17.8 0.1 -1.2
Average priority
expenditure (% of
GDP), FY2016/17-
FY2020/21
7.3 7.3 = 7.8 0.5 0.5
Average priority
expenditure per child
(US$ at 2016 prices
and exchange rate),
FY2016/17-
FY2020/21
263.88 263.88 = 286.2 +22.3 +22.3
Net internal debt flow
(% of GDP),
FY2016/17-
FY2020/21
5.0 3.5 -1.5 5.5 +0.5 +2.0
Total government
debt (% of GDP),
FY2020/21
71.6 65.0 -6.6 73.9 +2.3 +8.9
There are, of course, many other possibilities for revenue enhancement besides those mentioned
thus far. For example, there may be some scope for increasing non-tax revenue by improving the
performance of state-owned enterprises. Kenya has about 300 state-owned enterprises, many of
which have been underperforming in both service delivery and profitability. The potential for
improving the fiscal space is likely to be limited, however. Enterprises that managed to achieve
higher profit flows are likely to prioritise reinvesting them, although there may be some scope to
increase dividend income to the government. A current assessment of options to introduce
parastatal reforms carried out by the Presidential Taskforce on Parastatal Reforms has noted
various areas of inefficiency notes, ranging from corporate governance to lack of overarching roles.
One potential future source of fiscal-space enhancement is oil revenue. Oil deposits have been
discovered in recent years, and there has been some speculation that they could eventually provide
a significant source of additional income. However, further studies have suggested that oil
extraction cannot be profitable in the short to medium term. For now, it appears that unit costs of
extraction and transport are likely to exceed unit revenue at present world price levels. In addition,
there is growing pessimism regarding development costs. A further concern is that if present pricing
and costing policies remain in place, the sector would operate inefficiently and less profitably than it
otherwise might have done.26 In all, oil revenue is not likely to enhance the fiscal space significantly
in the medium term.
26 Don Hubert, Mapping risks to future government petroleum revenues in Kenya, Oxfam Novib, March 2016,
https://www.oxfam.org/sites/www.oxfam.org/files/file_attachments/rr-mapping-risks-petroleum-revenues-kenya-060516-
en.pdf.
34
4.2.2 Improving budget execution on priority expenditures
A policy choice the government is now actively considering is to take steps to improve budget
execution. Like many other African economies, budget execution has been relatively low, not only
for development but even for recurrent expenditure, and in particular for education and health
expenditure. Development expenditure in Africa (and, for that matter, throughout the world) is
always difficult to carry out on schedule, for many obvious reasons, and this translates into low
execution rates. Low execution rates for recurrent expenditure seem more difficult to explain. One
important reason, of course, is that education and health are sectors requiring skilled personnel,
who may not turn out to be unavailable. Where budget execution is low, the explanation sometimes
given is that the country in question has deficient “absorption capacity,” meaning that the country
lacks appropriate people to be hired as programmed and “absorb” the funds.
Scenarios 7-9 consider the quantitative consequences of improved execution rates for the fiscal
space. Scenario 7 reverts to the assumptions of Scenario 0, with the single exception that budget
execution rates rise from an estimated 90 per cent in FY2015/16 to 100 per cent over the projection
years for recurrent expenditure in health and education. This improvement is assumed to take place
entirely through the number of people on staff, not through higher pay than originally budgeted.
Scenario 8 reverts again to the assumptions of Scenario 0, with the single exception that the
execution rate of non-recurrent expenditure rises from an estimated 50 per cent in FY2015/16 to 65
per cent over the projection. Scenario 9 combines Scenarios 1 and Scenario 7, with a gradual
improvement in VAT collection efficiency helping to finance the improved recurrent budget
execution.
Box F: Improvements in the budget execution rate
Results Scenario
0
Scenario
7
Variation
base
scenario
Scenario
8
Variation
base
scenario
Scenario
9
Variation
base
scenario
Average tax
revenue/GDP,
FY2016/17-
FY2020/21
17.7 17.7 = 17.7 = 18.2 +0.5
Average priority
expenditure/GDP,
FY2016/17-
FY2020/21
7.3 7.7 +0.4 7.3 = 7.68 +0.43
Average priority
expenditure per child
(US$ at 2016 prices
and exchange rate),
FY2016/17-
FY2020/21
263.88 279.28 15.40 265.65 +1.76 279.28 15.40
Net internal debt
flow/GDP,
FY2016/17-
FY2020/21
5.0 5.5 +0.5 5.1 = 4.9 -0.1
Total government
debt/GDP, FY2020/21
71.7 73.7 +2.0 71.8 +0.2 71.0 -0.7
35
Evaluation of the scenario results indicates that, at least for the specific numbers chosen, higher
execution results would have quite limited consequences for the fiscal gap. Under Scenario 7
(higher execution of recurrent priority expenditure) the net internal debt flow would average 5.5 per
cent of GDP over the projection period, compared with 5.0 per cent in Scenario 0, an increase of
about 0.5 percentage points. The total government debt-GDP ratio would conclude FY2020/21 at
73.7 per cent of GDP, compared with 71.7 per cent in Scenario 0, a deterioration of 2.0 percentage
points. Under Scenario 8 (higher execution of non-recurrent priority expenditure) the net internal
debt flow would average 5.1 per cent of GDP over the projection period, compared with 5.0 per cent
in Scenario 0, an increase of about 0.1 percentage points. The total government debt-GDP ratio
would conclude FY2020/21 at 71.8 per cent of GDP, compared with 71.7 per cent in Scenario 0, a
deterioration of 0.2 percentage points. Finally, under Scenario 9 (improved VAT administration and
higher execution of recurrent priority expenditure) the net internal debt flow would average 4.9 per
cent of GDP over the projection period, compared with 5 per cent in Scenario 0, a modest decrease
of about 0.1 percentage points. The total government debt-GDP ratio would conclude FY2020/21 at
71.0 per cent of GDP, compared with 71.7 per cent in Scenario 0, a modest improvement of 0.7
percentage points.
4.2.3 Increasing external grants for budget support and projects
In recent years, for a variety of reasons27 most of Kenya’s donors have phased out budget-support
grants. Officials of aid agencies have suggested that these are unlikely to resume, as there is
diminished interest in grant funding on both donor and government side. Donors have also reduced
project grants, and, similarly, have no serious plans to revive these in the coming years. Some
donors have been providing substantial grants outside the budget, and some of these have funded
significant projects in education and health.
All the same, Kenya still has some important external-grants programs flowing to priority-sector
programs. A reduction in grant flows could lead to some combination of reduced expenditure or an
increased fiscal gap. As an illustrative exercise, Scenario 10 considers the consequences of a
reduction in the external-grants flow. The specific assumption is that the external-grants flow for
national government projects generally declines from an estimated 0.44 per cent of GDP in
FY2015/16 to 0.35 per cent of GDP, and remains at that value over the remainder of the projection
period. Under this scenario, the net internal debt flow would average 5.1 per cent of GDP over the
projection period, compared with 5.0 per cent in Scenario 0, a modest increase of about 0.1
percentage points. The total government debt-GDP ratio would conclude FY2020/21 at 72.1 per
cent of GDP, compared with 71.7 per cent in Scenario 0, a modest deterioration of 0.4 percentage
points.
Box G: External grants to the national government 20 per cent lower than in the base scenario
Results Scenario 0 Scenario 10 Variation
Average tax revenue (% of GDP), FY2016/17-FY2020/21 17.7 17.7 =
Average priority expenditure (% of GDP), FY2016/17-
FY2020/21
7.3 7.3 =
Average priority expenditure per child (US$ at 2016 prices
and exchange rate), FY2016/17-FY2020/21
263.88 263.9 =
Net internal debt flow (% of GDP), FY2016/17-FY2020/21 5.0 5.1 +0.1
Total government debt (% of GDP), FY2020/21 71.7 72.1 +0.4
27 These reasons include home-country political imperatives, the difficulty of working with complex and demanding
conditionality, and growing disillusion with the government-to-government grant modality.
36
Both international donors and recipient countries have increasingly found that external grants
carried out through the fiscal accounts have several drawbacks. One is that donor countries have
found that such grants have come under political attack. Another is that conditionality has
sometimes made programs and projects difficult for donors, managers and governments to
administer. One consequence has been that many donors and governments prefer that operations
involving grants operate outside the fiscal framework. This has contributed to the notable decline in
external grants carried out through African fiscal accounts in recent years.
It is important to remember in this context that external grants are characteristically provided with
substantial counterpart requirements. If the authorities decide to terminate the program in question,
the expenditure flow that would be terminated could be significantly more than the grant flow. (That
is, if an external grant program of US$ 1 million per year concludes, and the counterpart is, say, 50
per cent, the overall program that could be terminated would amount to US$ 2 million).
4.2.4 Enhanced GDP growth
The projection exercise could be used straightforwardly to evaluate the consequences of a higher
real-GDP growth rate than what the base-scenario assumes. Scenario 11 reverts to the Scenario 0
assumptions, but differs in a single way: the real-GDP growth rate rises gradually from 5.8 per cent
in FY2015/16 to 7.0 per cent in FY2020/21, instead of 6.0 per cent in the base scenario. With this
assumption, the average FY2016/17-FY2020/21 net internal debt flow would be 4.8 per cent of
GDP (compared with 5.0 per cent of a smaller GDP in the base scenario), and the total (external
and internal) government debt stock would conclude FY2020/21 at 69.2 per cent of GDP
(compared with 71.7 per cent of a smaller GDP in the base scenario). Per-child real priority
expenditure at FY2015/16 prices and exchange rate would average US$266.80 over FY2016/17-
Fy2020/21, 1.1 per cent higher than in the base scenario. This would come about because, since
non-recurrent priority expenditure is assumed to be the same percentage of GDP as in the base
scenario, the higher real GDP would drive it higher in real terms than in the base scenario.
Box H: Higher real GDP growth
Results Scenario 0 Scenario 11 Variation
Average tax revenue (% of GDP), FY2016/17-
FY2020/21
17.7 17.7 =
Average priority expenditure (% of GDP),
FY2016/17-FY2020/21
7.3 7.2 =
Average priority expenditure per child (US$ at 2016
prices and exchange rate), FY2016/17-FY2020/21
263.88 266.8 +2.9
Net internal debt flow (% of GDP), FY2016/17-
FY2020/21
5.0 4.8 -0.2
Total government debt (% of GDP), FY2020/21 71.7 69.2 -2.4
There are, of course, several other economic variables that are exogenous to the fiscal system, and
the projection exercise can be used to evaluate them by setting up alternative scenarios. In
addition, there are some other possibilities that would appear, in principle, to be options for
enhancing the fiscal space, but in fact appear not to be viable in Kenya’s specific reality.
4.3 Less appropriate options to enhance fiscal space
Formally, an examination of the components of the fiscal space suggests that if reductions in non-
priority expenditure and in debt service could be achieved, they could augment the fiscal space. In
37
addition, it might seem possible to augment the fiscal space by securing external loans. In general
terms, however, unlike (for example) a steady improvement in tax administration, these would
probably not be approaches that UNICEF should advocate as means to improve the fiscal space on
a stable, sustained basis.
4.3.1 Reducing non-priority expenditure
For any economy, and Kenya in particular, the objective of limiting non-priority expenditure presents
a complex set of practical issues as a general approach for bringing about sustained enhancement
of Kenya’s fiscal space. It is instructive to compare with the approach of improving tax
administration. Unlike the approach of reducing non-priority expenditure, improving tax
administration is generally politically acceptable; it is usually regarded as technical; and it can be
sustained as multiannual efforts, often with foreign technical support. By contrast, reduction of non-
priority expenditure is likely to be politically controversial, and may be difficult to carry out in
sustained multiannual efforts. While it would be too much to say that improving tax administration is
likely to happen steadily and that reducing non-priority expenditure is likely to be continuously
difficult, it is probable that UNICEF would find the government more inclined to favour improved tax
administration than reducing non-priority expenditure.
There are several additional considerations. One is that a large proportion of non-priority
expenditure is, in fact, essential for children’s welfare. One obvious example is expenditure on
water and sanitation, which is part of non-priority expenditure under the definition used here.
Another is that non-recurrent non-priority expenditure includes infrastructure investment, which is
essential to sustain the economy’s growth. The economy’s growth is essential, in turn, to sustain
the growth of tax revenue, which is essential to maintain the fiscal space.
4.3.2 Reducing external-debt service through agreements with creditors
Kenya’s public sector has accumulated external debt from various sources, including multilateral
and bilateral entities. World Bank figures show that Kenya’s total stock of public and publicly
guaranteed debt stood at US$12.6 billion at the end of 2014, about 21 per cent of GDP. Debt
service for this debt category amounted to US$281 million that year, about 0.5 per cent of GDP.
Since then, to be sure, Kenya has taken on a relatively large amount of debt from China, and
carried out international bond issues totalling about US$400 million. This led to a significant
increase in the debt-GDP ratio: external debt may have reached 30 per cent of GDP at the end of
FY2015/16. Nevertheless, debt sustainability analyses suggest that Kenya remains some way from
crossing benchmark “danger lines” particularly since debt service will not become significant until
the 2020 decade.
Reduction of external debt service has virtually no potential as a means of augmenting the fiscal
space for two straightforward reasons. First, Kenya’s external debt service is small as a percentage
of GDP. Second, since the mid-2000s, with the conclusion of the cycle of debt reduction that began
with the Heavily Indebted Poor Countries programme in the late 1990s, the international financial
community has generally been unwilling to consider debt reduction.
4.3.3 Increasing external-debt disbursements
In general, macroeconomic policy specialists concur that it is inadvisable to use commercial
external debt to fund education, health, or social-protection expenditure. The reasoning is
straightforward: eventual returns to education and health expenditure are realised over decades,
but debt service on commercial external debt is generally due within a decade. Concessional debt,
38
with multi-decade terms and near-zero interest rate, is more realistic for such purposes. Kenya,
however, has progressed sufficiently that it has graduated from being able to access such loans. In
compensation, of course, graduation makes Kenya eligible for larger World Bank and other loans
that can be applied to large infrastructure projects.
In some ways, this view of the potential role of external debt in the fiscal space may be too narrow.
If, for example, the government means to carry out a particular project with or without external
finance, it would enhance the fiscal space if it could secure an external loan to finance it. Funds that
would otherwise have had to be used for the project’s funding would now be made available,
potentially, for priority expenditure. The basic point is that any external loan disbursement would, in
principle, enhance the fiscal space. On the other hand, external financing would increase the
national debt significantly, and would commit Kenya to a high debt-service profile in the coming
decade, and a higher external debt-GDP ratio. Kenya’s own Medium Term Debt Strategy (2015)
proposes that Kenya stay well within an overall ratio of 50 per cent of GDP for the gross public debt
in net present value terms.
4.3.4 Increasing net internal borrowing flows
In the analytical structure of the projection exercise, net internal borrowing is calculated residually.
In effect, it is the consequence of all the programming assumptions taken together. Evaluation of its
feasibility therefore amounts to evaluation of the feasibility of all the programming assumptions
taken together. In principle, if it is inadvisable to fund priority expenditure with external debt, it is all
the more inadvisable to use internal debt, which usually carries a higher interest rate and shorter
maturities.
Kenya’s net internal financing flow averaged about 4.1 per cent of GDP over the FY2008/09-
FY2015/16 period. Given the economy’s (nominal) GDP growth, this caused Kenya’s internal debt
to rise over those years from about 23 to about 30 per cent of GDP. To prevent internal debt from
rising further, policy-makers are likely to take steps across the full fiscal-space range to reduce the
internal-debt flow in coming years. For this reason alone, it is unlikely that they would so much as
consider issuing internal debt as a means to increase the fiscal space.
39
5 Conclusion
This report’s fundamental recommendation is that, in support of its advocacy on behalf of
expenditure beneficial for children, UNICEF should continually formulate quantitative projections,
and make use of these in its dialogue with the Kenyan government and other stakeholders. These
projections should not only cover future expenditure needs in education, health and other sectors
relevant for children, but should also encompass the main components of the “fiscal space” that
provides the funding for such expenditure. Quantitative projections of this kind should enable
UNICEF to engage in more effective dialogue.
To help implement this fundamental recommendation, this chapter recommends and describes a
methodological approach to formulating fiscal-space projections. The methodology centres on the
government’s fiscal accounts identity. It applies a “scenario’ of programming assumptions to the
historical fiscal data base to formulate multiannual projections of the main fiscal accounts. For each
projection year, its basic procedure is to use the programming assumptions to calculate the flows of
revenue, priority expenditure, non-priority expenditure, external-debt disbursements, and debt
service, and then use the fiscal identity to calculate the government’s net internal debt flow
residually. The net internal debt flow calculated in this way serves as an indicator of the “fiscal gap”
for that year.
If this flow runs at a higher percentage of GDP than internal financial markets could absorb, or/and
if it implies that the government’s debt would rise very rapidly, the assumptions would presumably
be unfeasible, and would have to be revised to increase the fiscal space/reduce the fiscal gap.
Sensitivity analysis can be used to evaluate alternative policy approaches to maintaining an
adequate and stable growth rate for the fiscal space underlying the “priority-expenditure” flow.
A fiscal-space “framework” structured in the way this report describes can be used to help
determine the most likely policy approaches to ensure that the fiscal space grows to sustain a
stable, reliable funding base for priority expenditure. The analysis described in this report is
intended to be essentially illustrative, to show how the methodology it recommends can be used to
address the relevant policy issues. Nevertheless, certain tentative conclusions regarding the
substantive issues do emerge, including the following:
1. While the economic and political context offers little likelihood that tax revenue could be
increased by raising rates or introducing new taxes, there is considerable potential for improving
tax revenue through improved administration. Improved tax administration is likely to be
politically acceptable, especially if it is perceived as favouring fairness and equity;
2. Although the model cannot examine aspects of cost-efficiency, the projections made under
assumptions of improved absorption rates for recurrent and development expenditure in health
and education indicate that the effects on the fiscal gap will be small. At the same time, the
effects on associated outcomes in health and education through better absorption are likely to
be substantial;
3. The devolution process now under way in Kenya may offer some possibilities to increase the
fiscal space. In coming years, however, the magnitudes of the county fiscal flows will remain
small relative to the size of those of the national government. While the counties will take on
significant additional expenditure responsibilities for health, they are less likely to do so for
education. It appears that it will take some years for the devolution process to take on a stable
structure, and so, for coming years, its contribution to the fiscal space is likely to remain limited;
40
4. External grants carried out through the fiscal accounts, which have been diminishing for some
years, are likely to be a diminishing and even disappearing source of fiscal space for education
and health. External grants are likely to maintain some importance outside the fiscal accounts;
5. In general, non-concessional external debt should not be used to fund education and health
expenditure. The basic reason is that the yields from education and health expenditure come
only in the long term, beyond the terms typical of non-concessional external debt. For similar
reasons, internal term debt should not be used to fund education and health expenditure;
6. It may seem that there is some potential for enhancing the fiscal space by reducing, or
improving efficiency, in non-priority expenditure. It is not likely, however, that this can be as
reliable and stable approach to shoring up the fiscal space as the effort to improve tax
administration. In particular, it is important to remember that non-priority expenditure includes
infrastructure development, and this is crucial for sustaining real growth – which is crucial, in
turn, for sustaining revenue growth.
41
Annex 1 List of references
Dick-Sagoe, C., Survey of literature of fiscal decentralization as a sustainable local development
tool in Ghana, Journal of sustainable development in Africa, 14(3) 2012, 228-251.
Enemuo, F.C., ‘Problems and Prospects of Local Governance’ (Chapter 7, pp. 181–204), in G.
Hyden, D. Olowu & H. Ogendo (eds) African Perspectives of Governance (Trenton/Asmara: Africa
World Press), 2002.
Hubert, D., Mapping risks to future government petroleum revenues in Kenya, Oxfam Novib, March
2016, https://www.oxfam.org/sites/www.oxfam.org/files/file_attachments/rr-mapping-risks-
petroleum-revenues-kenya-060516-en.pdf.
IMF, Debt sustainability analysis update, 1 March 2016,
https://www.imf.org/external/pubs/ft/dsa/pdf/2016/dsacr1685.pdf.
IMF, Debt sustainability analysis update, 23 December 2016,
https://www.imf.org/external/pubs/ft/dsa/pdf/2017/dsacr1725.pdf.
IMF, Kenya: First Review Under the Twenty-Four Month Stand-By Arrangement and the
Arrangement Under the Standby Credit Facility and Requests for Waivers of Applicability,
Rephasing of Disbursements, and Modification of Performance Criterion-Press Release; Staff
Report; and Statement by the Executive Director for Kenya, 2 February 2017,
http://www.imf.org/en/Publications/CR/Issues/2017/02/02/Kenya-First-Review-Under-the-Twenty-
Four-Month-Stand-By-Arrangement-and-the-Arrangement-44607.
Kinuthia, J. and J. Lakin, Kenya: Analysis of the 2016/17 National Budget Estimates, June 2016,
http://www.internationalbudget.org/wp-content/uploads/ibp-kenya-analysis-of-2016-17-national-
budget-estimates-6-2016.pdf.
Mutua, J., R. Muya and D. Otieno, Child Budget Analysis in Kenya: National Government and Six
County Governments, Institute of Economic Affairs (IEA), May 2015.
Ngugi, B., Next budget to focus more on education, health sectors, Daily Nation, 2 February 2016,
http://www.nation.co.ke/business/Next-budget-to-focus-more-on-education-and-health-sectors/996-
3057980-4028tn/index.html.
OPM, Analysis of Kenya’s expenditure in education, future sector cost scenarios and benefits of
curriculum reform, 2016.
Sanghi, A. and D. Johnson, Deal or no deal: Strictly business for China in Kenya? World Bank
Policy Research Working Paper, March 2016,
http://documents.worldbank.org/curated/en/801581468195561492/pdf/WPS7614.pdf.
Office of the Controller of Budget, Annual National Government Budget Implementation Review
Report FY15/16.
Republic of Kenya, 2016/2017 Programme Based Budget of the National Government of Kenya for
the Year ending 30th June, 2017.
42
Republic of Kenya, 2016/2017 Programme Based Budget of the National Government of Kenya for
the Year ending 30th June, 2017.
SOLIDAR, Kenya: Social Protection Monitoring, Country Study, April 2016.
UNICEF, Kenya launches a Single Registry to strengthen social protection, 14 September 2016,
https://www.unicef.org/kenya/reallives_18743.html.
Westergaard, K. and M.M. Alam, Local government in Bangladesh: Past experiences and yet
another try, World Development 23(4) 1995, 679-690.
Williamson, T. and A. Mulaki, Devolution of Kenya’s Health System: the role of HPP, Brief, Health
Policy Project, RTI International, January 2015,
http://www.healthpolicyproject.com/pubs/719_KenyaDevolutionBrief.pdf.
World Bank, Decision Time: Spend More or Spend Smart? Kenya Public Expenditure Review
(PER), Volume 1, December 2014.
43
Annex 2 Fiscal Space projections
This Annex describes the details of the base-scenario projection exercise discussed in the main
report, and then describes the results of a sensitivity analysis. The base-scenario programming
assumptions are intended to be relatively simplified, to make the calculations relatively easy to
carry out and to understand. The following general explanatory points are noted:
1. The assumptions are “programming” assumptions. They are not intended, and should not be
understood, as forecasts, but rather as plausible possibilities for planning purposes. In
particular, the growth rates of government expenditure are intended as plausible policy
settings;
2. In general, the aim for the base scenario is to set programming assumptions that are “neutral.”
For example, Kenya`s merchandise export volumes are assumed to grow at the same rates as
the world trade volume, so Kenyan exports maintain the same share of the world trade volume.
The volume of Kenya’s merchandise imports is assumed to grow at the same rates as real
GDP, so merchandise imports would tend to maintain the percentage of GDP. For recurrent
expenditure, the assumption that staff sizes will grow at the same rate as the population would
be neutral in a similar sense. So is the assumption that government wage rates would grow at
the same rate as per-capita nominal GDP;
3. For the base scenario, the elasticities that help determine the government’s revenue
performance are taken to be just higher than one for the initial projection year, but then to
decline gradually toward one over the projection years;28
4. It is straightforward to set programming assumptions that adjust gradually over the projection
period, using (“geometric”) adjustment formulas. This is useful for several different assumption
lines. For example, are large proportion of the assumptions are set as growth rates. These can
be assumed to rise or diminish gradually from their initial projection values toward their final
projection values. Another way to use a gradual adjustment would be for the elasticity of a
given revenue line with respect to nominal GDP to take on an initial value somewhat different
from one, but then gradually adjust toward a long-term value of one.
For the base scenario, the programming assumptions are described in Table A.1. on the page
following:
Table A.1. Base-scenario programming assumptions
NOTES ON PROGRAMMING ASSUMPTIONS (SCENARIO 0):
(A) World economic conditions (1-3):
(1) The growth rate of the world trade volume rises gradually from its estimated 2016 value of 4.3 per cent to a
2021 value of 6 per cent.
(2) The growth rate of the U.S.-dollar world price level rises gradually from its estimated 2016 value of 1 per
cent to a 2021 value of 2 per cent.
(3) The London Interbank Offer Rate rises gradually from its 2016 value of 0.34 per cent to a 2021 value of
1.5 per cent.
(B) Basic Kenyan macroeconomic variables (4-10):
(4) The growth rate of real GDP rises gradually from 5.8 per cent in FY2015/16 to an FY2020/21 value of 6 per
cent.
(5) The GDP deflator grows at the same rate as the year-average consumer price index.
28 In general, it is inadvisable to apply econometric point estimates based on historical data for these values, for at least two
reasons. The first is that future elasticities are likely to differ from historical elasticities. The second is that, say, if the
elasticity of a given revenue line with respect to nominal GDP is assumed to exceed (be less than) one, the projected
revenue flow would rise (diminish) indefinitely as a percentage of GDP.
44
NOTES ON PROGRAMMING ASSUMPTIONS (SCENARIO 0):
(6) The December-December growth rate of the consumer price index (CPI) declines gradually from 6 per cent
in FY2016/17 to 3 per cent in FY2020/21.
(7) The December-December growth rate of the U.S. dollar exchange rate grows at a rate (approximately) equal
to the differential of the Kenyan and the world U.S.-dollar inflation rates.
(8) The overall population growth rate declines gradually from 1.3 per cent in 2017 to 1.1 per cent in 2021.
(9) The growth rate of the population under fifteen years of age declines gradually from 1 per cent in 2017 to
1 per cent in 2021.
(10) The headcount poverty incidence declines gradually from 50 per cent in 2017 to 45 per cent in 2021.
(C) Exports and imports of goods and non-factor services (11-17):
(11) The export volume grows at the same rate as the world trade volume.
(12) Export prices grow at the same rate as the world U.S.-dollar price level.
(13) The import volume grows at the same rate as real GDP.
(14) Import prices grow at the same rate as the world U.S.-dollar price level.
(15) Non-factor service exports grow at a rate equal to the combined growth rates of world trade volume and the
world US$ price level.
(16) Non-factor service imports excluding insurance and freight charges for merchandise imports grow at a rate
equal to the combined growth rates of world trade volume and the world US$ price level.
(17) Insurance and freight charges for decline gradually from 12 per cent of the value of merchandise imports in
2017 to 11 per cent in 2021.
(D) National-expenditure accounts (18-20):
(18) Consumption expenditure by government entities outside the central government rises gradually from 11.1
per cent of GDP in FY2015/16 to 14 per cent of GDP in FY2020/21.
(19) Gross fixed capital formation remains at 19.8 per cent of GDP.
(20) The net increase in inventory stocks remains at 0.5 per cent over the projection period.
(E) Tax and non-tax revenue (21-33):
(21) the elasticity of personal income-tax revenue with respect to nominal GDP declines from 1.1 in FY2016/17
to 1 in FY2020/21.
(22) the elasticity of company income-tax revenue with respect to nominal GDP declines from 1.1 in FY2016/17
to 1 in FY2020/21.
(23) the elasticity of other income-tax revenue with respect to nominal GDP declines from 1.1 in FY2016/17 to 1
in FY2020/21.
(24) the elasticity of customs revenue with respect to the value of merchandise imports declines from 1.1 in
FY2016/17 to 1 in FY2020/21.
(25) the elasticity of excise revenue with respect to nominal GDP declines from 1.1 in FY2016/17 to 1 in
FY2020/21.
(26) the elasticity of export-duty revenue with respect to the value of merchandise exports declines from 1 in
FY2016/17 to 1 in FY2020/21.
(27) the elasticity of county tax revenue with respect to nominal GDP averages 2 over the projection years.
(28) internal value-added tax rate remains unchanged at 16 per cent.
(29) internal value-added tax collection efficiency remains unchanged from its FY2015/16 value.
(30) import-based value-added tax rate remains at 16 per cent.
(31) import-based value-added tax collection efficiency remains unchanged from its FY2015/16 value.
(--) For the base scenario, the following revenue elasticities are taken to equal 1:
(32) central-government non-tax revenue with respect to nominal GDP.
(33) central-government non-tax revenue with respect to nominal GDP.
(E) External grants to the government (34-37):
(34) Central-government external grants for current expenditure would remain at 0 per cent of GDP.
(35) County-government external grants for current expenditure would remain at 0 per cent of GDP.
(36) Central-government external grants for capital expenditure (projects) would remain at 0.4 per cent of GDP.
45
NOTES ON PROGRAMMING ASSUMPTIONS (SCENARIO 0):
(37) County-government external grants for capital expenditure (projects) would remain at 0 per cent of GDP.
(F) Government expenditure in the priority and non-priority categories (38-67):
(F.1) For non-interest recurrent expenditure:
(F.1.a) In the education sector:
(38) the budget execution rate remains unchanged at 90 per cent.
(39) the budgeted staff grows at the same rate as the number of children.
(40) staff salaries grow at a rate equal to the growth rate of per-capita nominal GDP.
(41) expenditure on current goods and services grows at a rate equal to the combined growth rates of the year-
average CPI and the sectoral staff size.
(42) expenditure on non-staff recurrent expenditure excluding current goods and services grows at a rate equal
to the combined growth rates of the year-average CPI and the population growth rate.
(43) county recurrent expenditure grows at a rate equal to the combined growth rates of the year-average CPI
and the population.
(F.1.b) In the health sector:
(44) the budget execution rate remains unchanged at 90 per cent.
(45) the budgeted staff grows at the same rate as the population.
(46) staff salaries grow at a rate equal to the growth rate of per-capita nominal GDP.
(47) expenditure on current goods and services grows at a rate equal to the combined growth rates of the year-
average CPI and the sectoral staff size.
(48) expenditure on non-staff recurrent expenditure excluding current goods and services grows at a rate equal
to the combined growth rates of the year-average CPI and the population growth rate.
(49) county recurrent expenditure grows at a rate equal to the combined growth rates of the year-average CPI
and the child population.
(F.1.c) In the social-protection sector:
(50) Central-government social-protection expenditure grows at a rate given by the combined growth rate of the
year-average CPI and of the population under the poverty line.
(51) County-government social-protection expenditure is assumed at present to be zero. It would grow at a rate
given by the combined growth rate of the year-average CPI and of the population under the poverty line.
(F.1.d) In the non-priority expenditure sectors:
(52) the budget execution rate remains unchanged at 100 per cent.
(53) the budgeted staff grows at the same rate as the population.
(54) staff salaries grow at a rate equal to the growth rate of per-capita nominal GDP.
(55) expenditure on current goods and services grows at a rate equal to the combined growth rates of the year-
average CPI and the sectoral staff size.
(56) expenditure on non-staff recurrent expenditure excluding current goods and services grows at a rate equal
to the combined growth rates of the year-average CPI and the population growth rate.
(57) county recurrent expenditure grows at a rate equal to the combined growth rates of the year-average CPI
and the child population.
(F.2) For non-recurrent expenditure, over the projection years:
(58) Education non-recurrent central-government expenditure budget-execution rate remains at 50 per cent
from FY2015/16 to FY2020/21.
(59) Budgeted education non-recurrent central-government expenditure falls gradually from an FY2015/16 value
of 0.4 per cent of GDP to an FY2020/21 value of 0.3 per cent of GDP.
(60) Education non-recurrent county-government expenditure rises gradually from an FY2015/16 value of 0 per
cent of GDP to an FY2020/21 value of 0.5 per cent of GDP.
(61) Health non-recurrent central-government expenditure budget-execution rate remains at 50 per cent from
FY2015/16 to FY2020/21.
(62) Budgeted health non-recurrent central-government expenditure falls gradually from an FY2015/16 value of
0.5 per cent of GDP to an FY2020/21 value of 0.4 per cent of GDP.
46
NOTES ON PROGRAMMING ASSUMPTIONS (SCENARIO 0):
(63) Health non-recurrent county-government expenditure rises gradually from an FY2015/16 value of 0.01 per
cent of GDP to an FY2020/21 value of 2 per cent of GDP.
(64) Social-protection non-recurrent central-government expenditure budget-execution rate remains at 0.2 per
cent from FY2015/16 to FY2020/21.
(65) Non-priority non-recurrent central-government expenditure budget-execution rate remains at 50 per cent
from FY2015/16 to FY2020/21.
(66) Budgeted non-recurrent non-priority central-government expenditure remains at 13.8 per cent of GDP over
the projection period.
(67) Non-recurrent non-priority county-government expenditure rises gradually from an FY2015/16 value of
0.1 per cent of GDP to an FY2020/21 value of 1 per cent of GDP.
(G) For external and internal debt (68-71):
(68) average interest rates on the previous year’s year-end external debt stock increase (decrease) with LIBOR.
(69) average interest rates on the previous year’s year-end internal debt stock decline gradually from 12.2 per
cent in FY2015/16 to 7.3 per cent in FY2020/21.
(70) external-debt repayments in each projection year amount to 5 per cent of the preceding year’s year-end
external-debt stock.
(71) external-debt disbursements in each projection year amount to 65 per cent of total non-recurrent
expenditure.
Table A.2. immediately following lists the quantitative values of these assumptions, and shows the
base-scenario projection results.29
Table A.2. Projection Results for Scenario 0 (base scenario)
Projection results for Scenario 0 (per cent of
GDP)
FY2015/2016 FY2016/2017-
FY2020/2021
FY2020/21
(A) Total priority non-interest expenditure 6.2 7.3 8.0
Total education expenditure 4.9 5.0 5.0
Total health expenditure 0.8 1.9 2.6
Total social-protection expenditure 0.4 0.4 0.3
Priority recurrent expenditure: 5.5 5.1 4.9
Recurrent education expenditure: 4.8 4.5 4.4
Central-government recurrent education
expenditure:
4.6 4.4 4.2
Expenditure on education staff 3.2 3.2 3.2
Non-staff recurrent education expenditure: 1.4 1.2 1.1
Recurrent education expenditure on goods and
services
0.5 0.4 0.4
Other non-staff recurrent education expenditure 0.9 0.8 0.7
County-government recurrent education
expenditure
0.2 0.2 0.1
Recurrent health expenditure: 0.6 0.5 0.4
Central-government recurrent health
expenditure:
0.4 0.3 0.3
Expenditure on health staff 0.3 0.2 0.2
Non-staff recurrent health expenditure: 0.1 0.1 0.1
Recurrent health expenditure on goods and
services
0.0 0.0 0.0
29 Table A.2. shows only the assumption values. Consult Error! Reference source not found.. to understand the reasoning
underlying any specific assumption.
47
Projection results for Scenario 0 (per cent of
GDP)
FY2015/2016 FY2016/2017-
FY2020/2021
FY2020/21
Other non-staff recurrent health expenditure 0.1 0.1 0.1
County-government recurrent health
expenditure
0.2 0.1 0.1
Social-protection non-staff current
expenditure:
0.2 0.2 0.1
Central-government social-protection non-staff
current expenditure
0.2 0.2 0.1
County-government social-protection non-staff
current expenditure
0.0 0.0 0.0
Priority non-recurrent expenditure: 0.7 2.1 3.1
Non-recurrent education expenditure: 0.2 0.5 0.6
Central-government non-recurrent education
expenditure
0.2 0.2 0.1
County-government non-recurrent education
expenditure
0.0 0.3 0.5
Non-recurrent health expenditure: 0.3 1.4 2.2
Central-government non-recurrent health
expenditure
0.3 0.2 0.2
County-government non-recurrent health
expenditure
0.0 1.2 2.0
Non-recurrent social-protection expenditure 0.2 0.2 0.2
(B) Tax and non-tax revenue (excl. external
grants) (+):
19.7 20.1 20.2
Tax revenue: 17.3 17.7 17.8
Central-government tax revenue: 17.0 17.3 17.4
Income tax: 8.8 9.0 9.0
Personal income tax 1.3 1.4 1.4
Company tax: 7.1 7.2 7.2
Other income tax: 0.4 0.5 0.5
Value-added tax: 4.7 4.7 4.7
Value-added tax on internal transactions 3.7 3.7 3.7
Value-added tax on imports 1.0 1.0 1.0
Customs and excise duties: 3.5 3.6 3.6
Customs duties 1.3 1.3 1.3
Excises 2.2 2.3 2.3
Export duties 0.0 0.0 0.0
County-government tax revenue 0.3 0.4 0.4
Non-tax revenue (excl. external grants) (+): 2.4 2.4 2.4
Central-government non-tax revenue 2.4 2.4 2.4
County-government non-tax revenue 0.0 0.0 0.0
Non-tax revenue (excl. external grants) (+): 2.4 2.4 2.4
Central-government non-tax revenue 2.4 2.4 2.4
County-government non-tax revenue 0.0 0.0 0.0
(C) External grants (+): 0.5 0.5 0.5
External grants for current expenditure: 0.0 0.0 0.0
Central-government external grants for current
expenditure
0.0 0.0 0.0
County-government external grants for current 0.0 0.0 0.0
48
Projection results for Scenario 0 (per cent of
GDP)
FY2015/2016 FY2016/2017-
FY2020/2021
FY2020/21
expenditure
External grants for capital expenditure
(projects):
0.5 0.5 0.5
Central-government external grants for capital
expenditure (projects)
0.4 0.4 0.4
County-government external grants for capital
expenditure (projects)
0.0 0.0 0.0
(D) Total non-priority non-interest expenditure
(-):
-18.9 -18.2 -17.7
Non-priority recurrent expenditure: -11.9 -10.6 -9.8
Central-government non-priority recurrent
expenditure:
-12.3 -10.9 -10.1
Non-priority expenditure on staff -1.5 -1.5 -1.5
Non-staff recurrent non-priority expenditure: -10.8 -9.5 -8.6
Recurrent non-priority expenditure on goods and
services
-0.1 -0.1 -0.1
Other non-staff recurrent non-priority expenditure -10.7 -9.3 -8.5
County-government non-priority recurrent
expenditure
0.3 0.3 0.3
Non-priority non-recurrent expenditure: -7.0 -7.5 -7.9
Central-government non-priority non-recurrent
expenditure
-6.9 -6.9 -6.9
County-government non-priority non-recurrent
expenditure
-0.1 -0.6 -1.0
(E) External-debt disbursements (+): 4.9 4.9 5.1
External-debt disbursements (+) (US$ millions): 2,970.8 3,629.2 4,399.6
(F) External debt service (-): -1.1 -2.3 -2.6
External interest expenditure (-) -0.5 -0.8 -1.0
External interest expenditure (-) (US$ million) -297.2 -628.1 -880.9
External debt repayments (-) -0.6 -1.5 -1.6
External debt repayments (-) (US$ million) -341.9 -1,119.4 -1,367.3
(G) Net internal financial flows (incl. internal
interest) (+):
1.2 2.3 2.5
Net internal-debt flow (+): 3.3 5.0 4.9
Internal-debt disbursements (+)
Internal debt repayments (-)
Internal interest expenditure (-) -2.8 -2.7 -2.4
Discrepancy (+) 0.7 0.0 0.0
Revenue and grants 20.1 20.6 20.7
Expenditure: -28.4 -29.0 -29.1
Recurrent expenditure: -20.7 -19.3 -18.2
Non-interest recurrent expenditure -17.5 -15.8 -14.7
Interest -3.3 -3.5 -3.4
Non-recurrent expenditure: -7.7 -9.6 -11.0
Discrepancy 0.7 0.0 0.0
Surplus (deficit): -7.6 -8.4 -8.4
Primary surplus (deficit) -4.3 -4.9 -5.0
Interest -3.3 -3.5 -3.4
49
Projection results for Scenario 0 (per cent of
GDP)
FY2015/2016 FY2016/2017-
FY2020/2021
FY2020/21
Financing: 7.6 8.4 8.4
Net external financing 4.3 3.4 3.5
Net internal financing 3.3 5.0 4.9
External and internal debt 58.3 66.5 71.6
Net debt: 58.3 66.5 71.6
External debt 29.0 32.0 33.7
External (US$ millions) 17,829.0 24,898.2 30,377.7
Internal: 29.2 34.5 38.0
Internal debt 29.2 34.5 38.0
Internal deposits (-) 0.0 0.0 0.0
MACROECONOMIC AGGREGATES:
Gross domestic product (US$ million) 60,493.1 $73,817.4 85,708.9
Gross domestic product at 2016 prices and
exchange rate (US$ million)
60,493.1 $72,076.4 80,656.6
Gross domestic product (national currency -
millions)
6,210,518.9 8,719,273.6 10,503,804.8
GDP deflator 103.1 120.9 130.8
Consumer prices (year-average) 155.0 181.7 196.6
Consumer prices (December) 161.5 187.2 201.2
Exchange rate (year-average) 102.7 117.6 122.6
Exchange rate (December) 101.1 112.1 116.4
Population (millions) 46.1 47.8 48.9
Population under fifteen (millions) 19.3 19.9 20.3
Headcount poverty incidence 50.0% 47.5% 45.0%
Net exports of goods and non-factor services
(US$ million):
-$11,439.7 -$14,472.9 -$16,699.9
Exports of goods and non-factor services (US$
million)
$11,465.4 $13,969.5 $16,081.2
Merchandise exports (US$ million) $6,568.3 $8,002.9 $9,212.6
Non-factor services receipts(US$ million) $4,897.1 $5,966.6 $6,868.6
Imports of goods and non-factor services(US$
million)
-$22,905.0 -$28,442.3 -$32,781.1
Merchandise imports: (US$ million) -$19,352.1 -$24,140.1 -$27,932.2
Non-factor services payments: (US$ million) -$3,553.0 -$4,302.2 -$4,848.9
Insurance and freight payments for merchandise
imports(US$ million)
-$2,322.2 -$2,767.0 -$3,072.5
Other non-factor services payments(US$ million) -$1,230.7 -$1,535.2 -$1,776.4
Per cent of GDP:
Gross domestic product 100.0 100.0 100.0
Total consumption: 98.6 98.4 98.3
Non-government consumption 81.8 80.4 79.0
Government consumption: 16.7 18.0 19.3
Central-government consumption 5.6 5.4 5.3
Consumption of other governments 11.1 12.6 14.0
Total investment: 19.5 20.3 20.3
Gross fixed capital formation 19.8 19.8 19.8
Net increase in inventory stocks -0.3 0.5 0.5
Net exports of goods and non-factor services: -18.1 -18.7 -18.6
50
Projection results for Scenario 0 (per cent of
GDP)
FY2015/2016 FY2016/2017-
FY2020/2021
FY2020/21
Exports of goods and non-factor services 18.1 18.1 17.9
Imports of goods and non-factor services (-) -36.2 -36.8 -36.5
Per-capita non-government consumption at
US$ 2016 prices and exchange rate
1,075.1 1,211.3 1,303.3
Growth rate 7.1% 3.9% 3.7%
Table A.3. Kenya: Projected priority expenditure (U.S. dollars per child and prices and exchange rate of
FY2015/16), FY2017-2021 (base scenario)
US$ per child at prices and exchange rate of 2016 FY2015/20
16
FY2016/2017-
FY2020/2021
FY2020/
21
(A) Total priority non-interest expenditure 194.68 263.88 317.63
Total education expenditure 155.03 180.76 200.16
Total health expenditure 26.36 69.79 103.89
Total social-protection expenditure 13.29 13.33 13.58
Priority recurrent expenditure: 173.25 185.79 195.63
Recurrent education expenditure: 148.91 163.65 174.58
Central-government recurrent education expenditure: 143.19 157.93 168.86
Expenditure on education staff 100.23 114.97 125.90
Non-staff recurrent education expenditure: 42.96 42.96 42.96
Recurrent education expenditure on goods and services 15.03 15.03 15.03
Other non-staff recurrent education expenditure 27.92 27.92 27.92
County-government recurrent education expenditure 5.73 5.73 5.73
Recurrent health expenditure: 17.77 16.57 16.00
Central-government recurrent health expenditure: 12.69 11.49 10.92
Expenditure on health staff 8.88 7.66 7.07
Non-staff recurrent health expenditure: 3.81 3.83 3.85
Recurrent health expenditure on goods and services 0.89 0.89 0.90
Other non-staff recurrent health expenditure 2.92 2.94 2.95
County-government recurrent health expenditure 5.08 5.08 5.08
Social-protection non-staff current expenditure: 6.57 5.57 5.05
Central-government social-protection non-staff current
expenditure
6.56 5.56 5.05
County-government social-protection non-staff current
expenditure
0.01 0.01 0.01
Priority non-recurrent expenditure: 21.43 78.09 122.00
Non-recurrent education expenditure: 6.12 17.10 25.58
Central-government non-recurrent education expenditure 6.06 5.88 5.70
County-government non-recurrent education expenditure 0.06 11.23 19.88
Non-recurrent health expenditure: 8.59 53.22 87.89
Central-government non-recurrent health expenditure 8.16 8.31 8.36
County-government non-recurrent health expenditure 0.43 44.91 79.53
Non-recurrent social-protection expenditure 6.72 7.77 8.53
51
Table A.4. Kenya: Scenarios for fiscal-space analysis and summary scenario results
Scenario
0
Scenario
1
Scenario
2
Scenario
3
Scenario
4
Scenario
5
Scenario
6
Scenario
7
Scenario
8
Scenario
9
Scenario
10
Scenario
11
Real GDP
growth rate
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
6 per cent.
rises
gradually
from
5.8 per
cent in
FY2016/1
7 to an
FY2020/2
1 value of
7 per cent.
Elasticity of
company-tax
revenue with
respect to
nominal GDP
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 2 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1,1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
declines
from 1.1 in
FY2016/1
7 to 1 in
FY2020/2
1.
Elasticity of
county tax
collection with
respect to
nominal GDP
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
3 over the
projection
years.
remains at
3 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
remains at
2 over the
projection
years.
Domestic VAT
collection
efficiency
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
22.99 per
cent to an
FY2015/1
6 value of
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
22.99 per
cent to an
FY2015/1
6 value of
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
22.99 per
cent to an
FY2015/1
6 value of
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
52
Scenario
0
Scenario
1
Scenario
2
Scenario
3
Scenario
4
Scenario
5
Scenario
6
Scenario
7
Scenario
8
Scenario
9
Scenario
10
Scenario
11
27.59 per
cent
27.59 per
cent
27.59 per
cent
Import VAT
collection
efficiency
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
19.11 per
cent to an
FY2015/1
6 value of
22.93 per
cent
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
19.11 per
cent to an
FY2015/1
6 value of
22.93 per
cent
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
rises
gradually
from its
FY2015/1
6 value of
19.11 per
cent to an
FY2015/1
6 value of
22.93 per
cent
remains
unchange
d from its
FY2015/1
6 value.
remains
unchange
d from its
FY2015/1
6 value.
External grants
to the central-
government for
capital
expenditure
(projects)/GDP
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
remain at
0.44 per
cent of
GDP.
decline
from 0.44
per cent of
GDP in
2016 to
0.44 per
cent of
GDP in
2017 and
remain at
that level
through
2021.
decline
from 0.44
per cent of
GDP in
2016 to
0.44 per
cent of
GDP in
2017 and
remain at
that level
through
2021.
Education staff
-
execution/budg
et
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
increases
from 90
per cent in
2016 to
100 per
remains
unchange
d at 90
per cent.
increases
from 90
per cent in
2016 to
100 per
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
53
Scenario
0
Scenario
1
Scenario
2
Scenario
3
Scenario
4
Scenario
5
Scenario
6
Scenario
7
Scenario
8
Scenario
9
Scenario
10
Scenario
11
cent in
2017 and
remains at
that rate
through
2021.
cent in
2017 and
remains at
that rate
through
2021.
Elasticity of
education staff
size with
respect to child
population
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows in
each
projection
year at a
rate equal
to 3 times
the growth
rate of the
number of
children.
grows in
each
projection
year at a
rate equal
to 3 times
the growth
rate of the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
grows at
the same
rate as the
number of
children.
Health staff -
execution/budg
et
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
increases
from 90
per cent in
2016 to
100 per
cent in
2017 and
remains at
that rate
through
2021.
remains
unchange
d at 90
per cent.
increases
from 90
per cent in
2016 to
100 per
cent in
2017 and
remains at
that rate
through
2021.
] remains
unchange
d at 90
per cent.
remains
unchange
d at 90
per cent.
Elasticity of
health staff size
with respect to
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows in
each
projection
year at a
grows in
each
projection
year at a
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
grows at
the same
rate as the
population
54
Scenario
0
Scenario
1
Scenario
2
Scenario
3
Scenario
4
Scenario
5
Scenario
6
Scenario
7
Scenario
8
Scenario
9
Scenario
10
Scenario
11
. . rate equal
to 3 times
the
population
growth
rate.
rate equal
to 3 times
the
population
growth
rate.
. . . . . . . .
Non-recurrent
education
expenditure -
execution/budg
et
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
increases
from 50
per cent in
2016 to 65
per cent in
2017 and
remains at
that rate
through
2021.
at 50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
Non-recurrent
health
expenditure -
execution/budg
et
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
increases
from 50
per cent in
2016 to 65
per cent in
2017 and
remains at
that rate
through
2021.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
remains at
50 per
cent from
FY2016/1
7 to
FY2020/2
1.
County-
government
non-recurrent
health
expenditure/GD
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
rises
gradually
from an
FY2015/1
6 value of
55
Scenario
0
Scenario
1
Scenario
2
Scenario
3
Scenario
4
Scenario
5
Scenario
6
Scenario
7
Scenario
8
Scenario
9
Scenario
10
Scenario
11
P 0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP.
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
3 per cent
of GDP.
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP
0.01 per
cent of
GDP to an
FY2020/2
1 value of
2 per cent
of GDP