Evidence-Based Revenue Forecasting FY 2021-22
The Evidence-Based Revenue Forecasting FY 2021-22 is part of the federal budget for FY 2021-22. This page reproduces the text of its 15 PDF pages, extracted automatically from the official PDF published by the Finance Division, Government of Pakistan.
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Page 1
Evidence-Based Revenue Forecasting FY 2021-221
(FBR Taxes)
June 2021
Strategic Planning Reforms & Statistics Wing
1 Revenue Forecasting Report has been prepared in consultation with team of experts from Fiscal Policy
Center, Pakistan Institute Development Economics (PIDE), IslamabadPage 2
List of Acronyms CD Customs Duty CFY Current Fiscal Year EBRF Evidence-Based Revenue Forecasting FBR Federal Board of Revenue FED Federal Excise Duty FY Fiscal Year GDP Gross Domestic Product LSM Large Scale Manufacturing PFY Previous Fiscal Year ST(D) Sales Tax (Domestic) ST(M) Sales Tax (Imports)
Page 3
Contents
1. FBR Collection Profile…………………………..……………………………….4
1.1 Five Year Growth Trend/Tax-GDP ratio…………………………..4
1.2 CFY Collection ………………………………………………….……5
2. Evidence-Based Revenue Forecasting (EBRF) FY 2021-22………………6
2.1 Methodology……………………………………………………..……6
2.2 Head-wise Revenue Forecasts……………………………………10
3. Concluding Remarks.…………………………………………………..………12
Annex-I………………….……………………………………………….….…13
Annex-II……………………….……………………………………………....14
Annex-III…………………………….…………………………………….…..15Page 4
1. FBR Collection Profile
Major part of government tax revenues is collected by FBR. A substantial increase in
the tax collections has been witnessed during last two decades. FBR tax collection
was just around Rs.392 billion in 2000-01 which has jumped to around Rs.4 trillion in
2019-20. The average growth till FY 2017-18 remained 14.1%, however, due to
Covid-19 pandemic the yearly growth has plummeted, thus affecting slightly the
average annual growth for the period 2001-2020 as well (13.9%).
1.1 Five Years FBR Collection Trend
The last five years’ collection trend is shown in the following table. The 5 years
average growth was 9.3%, however, by excluding the last two years, average growth
for normal years i.e. FY 2013-14 to FY 2017-18 stands at 14.6% (Table 1).
Table 1: FBR Collection Trend
5 Years
Tax Avg.
2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20
Heads Growth
(%) *
DT 877,255 1,033,720 1,217,474 1,344,226 1,536,583 1,445,508 1,523,445 15.7
ST 996382 1087790 1,302,371 1,328,965 1,485,306 1,459,213 1,596,877 12.2
FED 138084 162248 188,055 197,911 213,493 238,186 250,474 12.1
CD 242810 306220 404,572 496,772 608,373 685,575 626,612 21.0
Total 2,254,531 2,589,978 3,112,472 3,367,874 3,843,755 3,828,482 3,997,408 14.6
(*) for the Years 2013-14 to 2017-18
Tax-GDP Ratio
Similarly, in the tax-GDP ratio, similar trend has been noticed and it kept on rising till
FY 2017-18 and reached 11.2 (Graph 1), but later on this healthy trend couldn’t
continue during FY 2018-19 and FY 2019-20, which is mainly attributed to Covid-19
pandemic related economic challenges.Page 5
Graph 1: FBR: Tax-GDP Ratio
12.0 11.1
10.7 10.6
10.1
10.0 9.4 9.58 9.0
8.0
6.0
4.0
2.0
0.0
2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20
1.2 CFY Collection: July-March 2020-21
After a slow growth in previous two years now the collection is picking up, which is
evident from table 2. This performance is very encouraging as compared to previous
couple of years. The nine months target has been achieved to the extent 103.4%.
Table 2: CFY Collection: July-March 2020-21
Rs. Million
Tax Heads 2020-21 2019-20 Growth (%)
DT 1,246,379 1,142,286 9.1
ST 1,415,770 1,250,222 13.2
FED 191,686 186,472 2.8
CD 541,049 481,478 12.4
TOTAL 3,394,885 3,060,458 10.9Page 6
With the recovery of economy the revenue collection is also improving, and with
further improvements in coming months hope the tax collection shall also increase,
thus enabling FBR to achieve its revenue FY 2021-22 target.
2. Evidence-Based Revenue Forecasting (EBRF) FY 2021-22
FBR collects Direct Taxes (DT), Sales Tax (Domestic & Imports), Federal Excise
Duty (FED) and Customs Duties (CD). In this study tax-wise buoyancy estimates
have been used to forecast the FBR head-wise revenues for FY 2021-22. The tax
buoyancy is an indicator to measure efficiency and responsiveness of revenue
mobilization in response to growth in the GDP or national income. A buoyant
tax means the tax revenues increase more than proportionately in response to a rise
in national income/GDP/base.
2.1 Methodology
The SPRS Wing before budget, projects the head-wise revenue estimates based on
buoyancy estimates2 from previous years on rolling basis. Tax-wise buoyancy
estimates are calculated by using historical collection and respective bases data.
The current tax-wise buoyancy estimates are estimated from data for the years
1999-2000 to 2019-20 in respect of economic indicators i.e. GDP, Non-agri GDP,
LSM and Imports.3
The respective proxy bases of head-wise FBR taxes are as under:
Direct Taxes (DT) Non-agri GDP
Sales Tax Domestic (STD) Large Scale Manufacturing (LSM)
Sales Tax Imports (STM) Import Value
Customs Duties (CD) Dutiable Import Value
Federal Excise Duty (FED) LSM
2 Buoyancy is relationship between changes in actual revenues and changes in proxy tax base from
National Accounts data.
3 Annex-I and Annex IIPage 7
% Change in Actual
Revenues
Buoyancy estimates are derived as = % Change in
Respective Base
Since these tax bases have a dynamic relationship with GDP, in the second step we
have calculated the buoyancies of these tax bases with GDP =.
% Change in
Respective Base
% Change in GDP
Finally these two are multiplied to arrive at respective tax to GDP buoyancies=
% Change in % Change in
Actual Revenues Respective Base X
% Change in % Change in GDP
Respective Base
Using these buoyancy estimates autonomous growth for each tax is estimated by
using the projections provided by Finance Division for each proxy base.4 It provides
for the GDP Growth and inflation forecast for upcoming year. GDP value used for
this projection of growth is Gross Value Addition of Sectors at Constant Factor
Costs. Using the inflation forecasts these GDP growth estimates are converted into
GDP growth estimates at Current Factor Cost. Further, GDP-Gross value addition at
Current Factor Cost is used for measuring the Buoyancy estimates to be used for
revenue forecasts.
In respect of Direct Taxes (DT) Non-Agri GDP has been taken as its proxy base. The
buoyancy of direct taxes has been estimated in two steps: in the first step Direct Tax
to Non-Agri GDP and in second step Non-Agri-GDP to GDP (Gross Value Addition-
Current Factor Cost) is estimated. Then two buoyancy estimates have been
multiplied to estimate the Direct Taxes to GDP Buoyancy estimates.
% Change in DirectDirect taxes to Non-Agri GDP Buoyancy (B1) =
Taxes
% Change in Non-Agri
GDP
4 Finance Division provides the macroeconomic framework for the next fiscal year along with rolling
estimates for next two years in their Medium Term Budget Strategy Paper (2021-22 to 2023-24).Page 8
Non-Agri GDP to GDP Buoyancy (B2) = % Change in Non-Agri
GDP
% Change in GDP
Direct taxes to GDP Buoyancy = B1 * B2
Similarly for Customs (CD) the proxy base is dutiable imports, whereas the
projections as provided by Finance Division are for the total imports. Therefore, the
buoyancy has been estimated in two steps: first Customs to dutiable imports and in
second step Dutiable Imports to total Imports and then these two have been
multiplied to get the CD buoyancy estimates.
For Federal Excise (FED) and Sales Tax (Domestic) the base is Large Scale
Manufacturing (LSM) and for Sales Tax (Imports) the base is imports. Therefore, for
these taxes the buoyancy values are directly estimated from proxy bases. Following
table reflects the respective buoyancies which are estimated using simple log-log
regression method in excel sheet by using log values of actual data for taxes.5
Table 3: Buoyancy Results
Direct Tax (DT)
DT to Non-Agri GDP Non-Agri-GDP to GDP DT to GDP
1.1 0.99 1.13
Sale Tax-Domestic (STD) 1.11
Sales Tax-Imports (STM) 0.92
Customs (CD)
Customs to
Custom-Dutiable Imports Dutiable Imports to Imports Imports
0.95 0.95 0.90
FED 0.77
5 Source: FBR Annual Reports and Economic Survey of PakistanPage 9
Calculating Autonomous Growth
In the second step autonomous growth has been estimated by multiplying buoyancy
estimates (Table 3) to projected growths of respective bases (Table 4):6
Table 4: Growth Assumptions for FY 2021-22
Macroeconomic Indicators Projected Growths (%)7
GDP (Nominal) 13.22
LSM (Nominal) 14.70
Imports 12.00
Inflation 8.20
GDP (Real) 5.02
LSM (Real) 6.50
Table 5 provides an autonomous growth parameters for each tax head. These are
based on the buoyancy estimates from the last 20 years actual revenue collection
data and the macroeconomic proxy bases provided by Pakistan Bureau of
Statistics/Annual Economic Surveys and the growth projections published in Budget
Strategy Paper / Economic Adviser’s Wing, Finance Division.
Table 5: Autonomous Growth
[Base Growth * Buoyancy] Autonomous Growth (%)
DT (GDP non-agri * DT Buoyancy) 14.89
ST(D) (LSM * STD Buoyancy) 16.31
STM (Imports * STM Buoyancy) 11.03
CD (Imports * CD Buoyancy) 10.85
FED (LSM * FED Buoyancy) 11.30
6 Autonomous growth depends on macroeconomic indicators and assumption of tax structure being
able to capture revenue from these as per past performance. A higher growth in base will lead
towards higher independent growth in respective taxes and thus higher projected collection.
7 Source Medium Term Budget Strategy Paper 2021-22 to 2023-24 / Economic Adviser’s Wing,
Finance DivisionPage 10
These autonomous growths will be used to project the autonomous growth estimates of respective revenue heads. To be sure of the results robustness a small exercise was also done by using the reduced and increased nominal growths by 10%. The resulting change was insignificant. 2.2 Head-wise Revenue Projections FY 2021-22 The autonomous growth (Table 5) has been applied on base year’s expected collection (i.e. 2020-21) for each respective head to project an increase of Rs. 636 billion. This addition has been added in the expected collection of FY 2020-21 thus, the revenue forecast for FY 2021-22 without additional Policy/Admn measures has been obtained to the tune of Rs. 5,336 billion. The required growth over the expected collection of FY 2020-21 i.e. Rs. 4,700 billion would be 13.5% in FY 2021-22. However, with the addition of Policy/Admn measures the target for FY 2021-22 would be Rs. 5,829 billion, which is near to IMF suggestion i.e. requiring a growth of about 24.0%.
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Table 6: Revenue Projections for FY 2021-22
(Rs. Billion)
Base Growth Assumptions Buoyancy Estimates Autonomous growth
Sectors % %
DT (GDPN *
GDP (Nominal) 13.22 DT 1.13 14.89 DTBuoy)
ST(D) (LSMN *
LSM(Nominal) 14.70 ST D 1.11 16.31 STDBuoy)
STM (Imports *
Total Imports 12.00 STM 0.92 11.03 STMBuoy)
CD (Imports *
Inflation 8.20 Customs 0.90 10.85 CDBuoy)
FED (LSMN *
GDP (Real) 5.02 FED 0.77 11.30 FEDBuoy)
LSM (Real) 6.50
DT ST(D) ST(I) CD FED Total
Expected Base
1,789 934 1,002 700 275 4,700
Figures 2020-21
Projection (2021-22)
with Autonomous 266 152 111 76 31 636
Growth
FBR Projections 2,055 1,086 1,113 776 306 5,336
without measures FY
ST 2,199 Req.2021-22 13.5
(total) Growth
(*) This excludes Policy/Admn Measures and consists of projection due to autonomous growthPage 12
Concluding Remarks It has been found that the overall FBR taxes are buoyant (1.04 overall buoyancy) and there is a potential for increase in tax revenues provided that macroeconomic indicators are doing well. It is evident from last 20 years data that FBR revenues increased substantially with around 14% average growth. The head-wise break-up reveals that the direct taxes are most buoyant with I.13 buoyancy value, followed by sales tax (domestic) with 1.11 buoyancy estimates. On the other hand, sales tax (imports), customs and FED have relatively lesser buoyancies. In this regard, addressing the issues of narrow base, unnecessary exemptions and valuation problems at import stage can be instrumental for making these tax heads more buoyant, thus enabling the revenue organization to fetch more tax revenues. The revenue forecast for FY 2021-22 by applying the buoyancy estimates and projected respective macroeconomic indicators would be Rs.5,336 billion without Policy/Admn measures. After adding Policy/Admn measures the target would be Rs.5,829 billion. However the revenue collection and achieving of target would largely depend on the performance of the economy against the targets.
Page 13
Annex-I
Net Tax collection 2000-01 to 2019-20 (Rs. Million)
S.No FY Direct Taxes ST Imports ST Dom FED Customs Total
1 2000-01 124,585 88,554 65,011 49,080 65,047 392,277
2 2001-02 142,505 92,779 73,782 47,186 47,818 404,070
3 2002-03 151,898 105,605 89,534 44,754 68,836 460,627
4 2003-04 165,079 125,875 93,292 45,552 91,045 520,843
5 2004-05 183,372 144,845 93,692 53,104 115,374 590,387
6 2005-06 224,988 171,445 123,353 55,272 138,384 713,442
7 2006-07 333,737 175,909 133,487 71,804 132,299 847,236
8 2007-08 387,861 196,034 181,396 92,137 150,663 1,008,091
9 2008-09 443,548 203,715 248,029 117,455 148,403 1,161,150
10 2009-10 525,977 247,246 269,102 124,784 160,273 1,327,382
11 2010-11 602,451 308,648 324,709 137,353 184,853 1,558,014
12 2011-12 738,424 430,399 374,500 122,464 216,906 1,882,693
13 2012-13 743,409 429,831 412,697 120,964 239,459 1,946,360
14 2013-14 877,255 495,330 501,052 138,084 242,811 2,254,532
15 2014-15 1,033,720 553,028 534,762 162,248 306,220 2,589,978
16 2015-16 1,217,474 678,313 624,058 188,055 404,572 3,112,472
17 2016-17 1,344,226 702,565 626,400 197,911 496,772 3,367,874
18 2017-18 1,536,583 824,219 661,087 213,493 608,373 3,843,755
19 2018-19 1,445,508 810,357 648,856 238,186 685,575 3,828,482
20 2019-20 1,523,064 876,333 720,471 250,470 626,378 3,997,408Page 14
Annex-II
Tax Bases Data (Rs. Million)
GDP (Gross
Value Dutiable
S.No FY Addition) GDP-non agri LSM Imports Imports
1 2000-01 3,923,244 2,977,943 410,879 627,000 386,597
2 2001-02 4,146,167 3,177,876 424,089 634,630 404,641
3 2002-03 4,534,218 3,474,902 481,374 714,372 436,316
4 2003-04 5,250,527 4,085,776 621,899 897,825 629,159
5 2004-05 6,122,568 4,808,334 814,657 1,223,079 869,815
6 2005-06 7,715,777 5,701,305 1,003,062 1,711,158 1,052,837
7 2006-07 8,735,766 6,549,859 1,149,573 1,851,136 1,010,603
8 2007-08 10,355,255 7,961,728 1,363,068 2,512,072 1,283,696
9 2008-09 12,542,265 9,543,644 1,427,213 2,723,570 1,337,629
10 2009-10 14,248,547 12,787,274 1,644,117 2,910,975 1,333,709
11 2010-11 17,647,553 13,054,833 2,144,831 3,455,286 1,521,329
12 2011-12 19,361,511 14,608,436 2,362,410 4,009,093 1,600,186
13 2012-13 21,496,680 16,161,704 2,519,037 4,349,880 1,652,823
14 2013-14 24,028,897 18,052,680 2,824,463 4,634,974 1,778,444
15 2014-15 26,089,690 19,553,568 2,853,222 4,719,399 2,703,371
16 2015-16 27,402,295 20,652,329 2,801,169 4,721,978 3,467,318
17 2016-17 29,977,559 22,659,094 3,044,603 5,583,637 4,067,138
18 2017-18 32,383,021 24,471,242 3,331,363 6,749,678 4,662,323
19 2018-19 35,783,281 27,413,644 3,722,943 7,499,468 5,054,709
20 2019-20 38,878,480 29,409,085 3,712,779 7,057,323 4,455,140Page 15
Annex-III Log Values
Tax collection Tax bases
GDP-
GDP non Total Dutiable
S.No FY DT STM STD FED CD TOTAL (GVA) agr LSM Imports imports
1 2000-01 11.7 11.4 11.1 10.8 11.1 12.9 15.2 14.9 12.9 13.3 12.9
2 2001-02 11.9 11.4 11.2 10.8 10.8 12.9 15.2 15.0 13.0 13.4 12.9
3 2002-03 11.9 11.6 11.4 10.7 11.1 13.0 15.3 15.1 13.1 13.5 13.0
4 2003-04 12.0 11.7 11.4 10.7 11.4 13.2 15.5 15.2 13.3 13.7 13.4
5 2004-05 12.1 11.9 11.4 10.9 11.7 13.3 15.6 15.4 13.6 14.0 13.7
6 2005-06 12.3 12.1 11.7 10.9 11.8 13.5 15.9 15.6 13.8 14.4 13.9
7 2006-07 12.7 12.1 11.8 11.2 11.8 13.6 16.0 15.7 14.0 14.4 13.8
8 2007-08 12.9 12.2 12.1 11.4 11.9 13.8 16.2 15.9 14.1 14.7 14.1
9 2008-09 13.0 12.2 12.4 11.7 11.9 14.0 16.3 16.1 14.2 14.8 14.1
10 2009-10 13.2 12.4 12.5 11.7 12.0 14.1 16.5 16.4 14.3 14.9 14.1
11 2010-11 13.3 12.6 12.7 11.8 12.1 14.3 16.7 16.4 14.6 15.1 14.2
12 2011-12 13.5 13.0 12.8 11.7 12.3 14.4 16.8 16.5 14.7 15.2 14.3
13 2012-13 13.5 13.0 12.9 11.7 12.4 14.5 16.9 16.6 14.7 15.3 14.3
14 2013-14 13.7 13.1 13.1 11.8 12.4 14.6 17.0 16.7 14.9 15.3 14.4
15 2014-15 13.8 13.2 13.2 12.0 12.6 14.8 17.1 16.8 14.9 15.4 14.8
16 2015-16 14.0 13.4 13.3 12.1 12.9 15.0 17.1 16.8 14.8 15.4 15.1
17 2016-17 14.1 13.5 13.3 12.2 13.1 15.0 17.2 16.9 14.9 15.5 15.2
18 2017-18 14.2 13.6 13.4 12.3 13.3 15.2 17.3 17.0 15.0 15.7 15.4
19 2018-19 14.2 13.6 13.4 12.4 13.4 15.2 17.4 17.1 15.1 15.8 15.4
20 2019-20 14.2 13.7 13.5 12.4 13.3 15.2 17.5 17.2 15.1 15.8 15.3
Buoyancy Estimates based on 20 years data
DT STM STD FED CD TOTAL
1.13 0.92 1.11 0.77 0.90 1.04