NATIONAL ACCOUNTS STATISTICS Quarterly Annual National Accounts In

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NATIONAL ACCOUNTS STATISTICS Quarterly & Annual National Accounts In Rwanda RWILIZA Jean Chrysostome National

NATIONAL ACCOUNTS STATISTICS Quarterly & Annual National Accounts In Rwanda RWILIZA Jean Chrysostome National Bank of Rwanda 17 September 2020 1

Outline q q q Introduction Compilation methodologies Main data sources Data gaps Improvement 17

Outline q q q Introduction Compilation methodologies Main data sources Data gaps Improvement 17 September 2020 2

Introduction 17 September 2020 3

Introduction 17 September 2020 3

Introduction q q q GDP by economic activity, i. e. GDP(P), are compiled on

Introduction q q q GDP by economic activity, i. e. GDP(P), are compiled on a quarterly and annually at both current & constant 2006 prices basis; The estimates of GDP are compiled in accordance with the principles and concepts of the SNA 93; Quarterly GDP estimates are published via NISR website since October 2011; q First estimate 3 months while revised 9 months q Annual estimates are obtained by summing up the relevant quarterly estimates. 17 September 2020 4

Methodology 17 September 2020 5

Methodology 17 September 2020 5

Production approach n n The current methodology depends on establishing a “benchmark” every five

Production approach n n The current methodology depends on establishing a “benchmark” every five years. The quarterly GDP(P) estimates are based on extrapolating 2006 benchmarks using two types of indicators: n n n value indices (for current price estimates) and quantity indices (for constant price estimates). Benchmark estimates are available for every kind of activity of Total output, IC, and GVA. 17 September 2020 6

Production approach (cont) Value indices: There are 2 methods of producing value indices: n

Production approach (cont) Value indices: There are 2 methods of producing value indices: n First, when figures for the turnover are available directly, these can be converted into a value index. Ø n These turnover data are available for the formal sector and equivalent figures for producers of government services. Second, where turnover figures are not available directly, a value index can be obtained by multiplying a quantity index by an appropriate price index. Ø This is what we do for Agriculture and the rest of informal sector. 17 September 2020 7

Production approach (cont) Quantity indices: There are several methods of deriving a quantity index:

Production approach (cont) Quantity indices: There are several methods of deriving a quantity index: q If a value index exists, it can be divided by an appropriate price index. q If quantity data are available, they can be converted directly into an index number. Ø If neither values nor reliable quantities are available, proxy indicators of quantity may have to be used. In some cases the quantity indices are based on the population growth rate. 17 September 2020 8

Production approach (cont) Annual estimates: n Annual estimates are derived by summing the quarterly

Production approach (cont) Annual estimates: n Annual estimates are derived by summing the quarterly estimates. n The main sources for the indicators are: banking data, BOP, Crop assessments, Government finance data, Population projections, Trade data (Import export), Price data (CPI & PPI)and tax data (VAT). 17 September 2020 9

GDP at market prices n Once the estimates of GVA by activity have been

GDP at market prices n Once the estimates of GVA by activity have been made, two adjustments are required in order to convert total GVA at basic prices into GDP at market prices, both current and constant. The first is for Financial Intermediation Services n Indirectly Measured : FISIM (formerly known as imputed bank service charges) The second is taxes (less subsidies) on products. n 17 September 2020 10

Expenditure approach n n n GDP by expenditure share, i. e. GDP(E) is NOT

Expenditure approach n n n GDP by expenditure share, i. e. GDP(E) is NOT independently compiled. Therefore, hard to verify GDP(P). The difference between the total GDP(P) and the sum of other items of expenditure (Government final consumption expenditure, GFCF, and netexport) is reported as private consumption. Separate estimates for household final consumption expenditure, consumption of nonprofit institutions serving households, and changes in inventories are not compiled. 17 September 2020 11

Mode of production n n Formal sector has been defined as businesses registered for

Mode of production n n Formal sector has been defined as businesses registered for VAT excluding agriculture (agro-industries such as tea and coffee processing are included) For largest enterprises, banks and insurance companies, these data are supplemented by the detailed annual (for banks, quarterly) financial accounts. Informal activity covers marketed production by all other private producers not registered for VAT Apart from crop production (use of “crop assessment data”)estimates are produced by extrapolating the benchmark using proxy indicator. 17 September 2020 12

Mode of production (cont) n n Non-monetary production covers goods (mostly crops) and housing

Mode of production (cont) n n Non-monetary production covers goods (mostly crops) and housing services that are consumed by the producer (auto-consumption). These proportions are assumed to be constant between benchmarks. The Government and NGO mode of production is assumed to be activity carried out in three branches of activity, namely public administration, education and health. 17 September 2020 13

Main data & sources at the rebasing period Data Sources EICV 2 NISR Trade

Main data & sources at the rebasing period Data Sources EICV 2 NISR Trade data: Imports CIF, import duty and VAT, RRA (Customs) Export FOB BOP: detailed services (Goods for comparison) BNR Existing gross output estimates by mode of production NISR National Accounts VAT: Monthly turnover RRA GFS: Government expenditure details MINECOFIN Enterprise survey data NISR Agriculture survey (2008) provisional results NISR Crop assessments (2006 -2008) MINAGRI Agriculture prices for 2006 by market 17 September 2020 National Institute of Statistics of Rwanda MINAGRI 14

Data sources for regular estimates Mode of production (cont) DATA FOR: Type SOURCES Agriculture

Data sources for regular estimates Mode of production (cont) DATA FOR: Type SOURCES Agriculture Crop production MINAGRI(mostly n Non-monetary production covers goods crops NAEB crops) and. Export housing services that are consumed by the Others RAB etc producer (auto-consumption). These proportions are Formal sector to. VAT income tax turnoverbenchmarks. RRA assumed be & constant between Profit & loss accounts of firms BNR & NISR n The Government and NGOofmode production is Quantity & turnover firms of NISR (PPI survey) assumed to be activity carried out in three branches RDB, RTDA, RURA of service activity, Government namely public administration, education Public expenditure MINECOFIN BOPand health. Prices 17 September 2020 BNR Trade data RRA Farm gate prices CPI &PPI MIS-MINAGRI NISR 15

Gaps The main gaps include: n Better estimates of agricultural production n through joint

Gaps The main gaps include: n Better estimates of agricultural production n through joint collaboration between NISR and MINAGRI n this process has started n Quarrying n Quarterly estimates of road constr. Quarterly BOP (especially services) n Quarterly insurance data n Timely school enrolment data n 17 September 2020 16

Improvement n The NISR is committed to improving the GDP estimates and to expanding

Improvement n The NISR is committed to improving the GDP estimates and to expanding the range of NAS aggregates: Current improvement: n n Replacing use of population indicators with more representative indicators; from 19% to 7. 4% Increasing use of existing NISR survey data (e. g. Pop. Census 2002, EICV 2, NAS 2008). 17 September 2020 17

Plans for Improvement (2012 to 2014) Increasing access to, and/or use of, existing administrative

Plans for Improvement (2012 to 2014) Increasing access to, and/or use of, existing administrative source data (e. g. Income tax, RAB, RURA, RTDA, Ministries); Finalizing results of EICV 3 ; Conducting benchmark agriculture, RGPHC, IBES (enterprise and NGO surveys); Developing detailed benchmarks based on Input-Output Tables (IOT) and Supply/Use Tables (SUT); Rebase of GDP to 2011 base year; Expanding and improving annual and sub-annual data collections (e. g. for Agriculture, PPI); and Redeveloping the NAS compilation methodology and worksheets (Crop WIP, construction model etc) 17 September 2020 18

Many thanks 17 September 2020 19

Many thanks 17 September 2020 19