Statistical Methods, Standards and Guidelines 66

the field and were not seen at both stages of editing or committed at the data entry stage, and if any error found are fixed.

Analysis and Report Writing This is an important stage of processing the survey results. This is done by NBS and other organizations or individuals with competence in specific areas such as poverty analysis, consumer price index and national accounts. Both national and international consultants are usually recruited to support local staff in the analysis.

Dissemination and Utilization of Results A National dissemination seminar is conducted after completion of report writing. The seminar involves key stakeholders to the survey.

4.7.3 Reference to applicable standard classifications The HBS follow the International reference classifications such as International Standard for Industrial Classification (ISIC), Tanzania Standard Classification of Occupations (TASCO) and Classification of Individual Consumption by Purpose (COICOP).

4.8
CONSUMER PRICE INDEX (CPI) Consumer Price Index (CPI) measures changes over time in the general level of prices of goods and services that households purchase for the purpose of final consumption. For this reason, CPI has increasingly become a key macro-economic indicator for monitoring price movements and how these movement impact on policy decisions.

4.8.1 Objectives and uses of CPI The purpose of a price index includes the following:- (i) To measure changes in the purchasing power of monetary incomes; (ii) To measure changes in living standards; and (iii) To measure price inflation experienced by households.

CPI has been used in various fields such as: - (i) To assist government economists in conducting general economic policy, especially monetary policy: and

Statistical Methods, Standards and Guidelines 67

(ii) It is widely used in indexation arrangements in both the private and public sectors. These include indexing pension and superannuation payments, taxes and charges, some governmental bonds, and business contracts.

4.8.2 It’s Methodology (i) The application uses the Modified Laspeyre’s Approach to compute CPI statistics based on monthly price quotations (or monthly average price quotations) and annual expenditure information using a combination of manual and computer tabulation procedures.
) p p ( * ) p p ( * w

I i 0, i 1, -t i 1, -t it, i 0, n 1

i 0 t ∑ →

which can be re-written as: LTPR

STPR

w

I i 0, 1 -t i 1, -t t i 0, n 1

i 0 t → → →∑

where W0,i is base period weight for item i, STPRt→t-1,i is the short-term price relative of item i for current period (= pt,i /pt-1,i) and LTPRt-1→0,i is the long-term price relative of item i for previous period (= pt-1,i /p0,i).

(ii) CPI is calculated using the equivalent of a recursive procedure, in which previous period’s base-weighted long-term price relatives, pt-1, q0 are updated by the current period’s price relatives.

(iii) The geometric mean method is used in computing the price level at aggregate level in view of its multiple advantages.

(iv) The program adopts the Matching Price Observation method in imputing the areas’ average prices, in which the price averages are calculated on the basis of “matched observations”. Whenever a particular price observation is missing from either the previous month or the current month, the corresponding price observations will be dropped from the other period. This is to ensure consistent sample of price quotations in each period.

Statistical Methods, Standards and Guidelines 68

(v) The program calculates missing variety prices based on Short Term Price Relative (STPR) (actual or imputed) and previous period price, and stores them in the database with a flag. These calculated price data can be retrieved into spreadsheets for the next period imputation process.

4.9
INTERNATIONAL COMPARISON PROGRAM (ICP) The International Comparison Programs is a global project, managed centrally by the World Bank, with an organized hierarchy of regional management structure. The responsibility of managing its African component ICP-Africa lies with the African Development Bank (AfDB). The main objective of the ICP is to compare the economic aggregate and the volumes of gross domestic product (GDP) between the countries.

The targeted population is the set of all goods and services that are consumed by household from outlets during the benchmark year, covering the whole country (including rural and urban areas), except expenditure of housing rent on residential (building), education and health services which are subsidized in most of the countries.

The ICP price project is integrated with the existing system of price collection for the CPI except to some items which are not available in CPI but are needed in ICP according to the agreement of country members.

The ICP price collections are carried out in urban and rural areas (weekly market) of the sampled centres. Stratification allocation and purpose are the methods used to select the region for ICP price collection activity. In Tanzania, there are seven zones including Zanzibar which constitute Unguja and Pemba.

The country members capture and validate ICP price collection using the same method as used in CPI but further analysis is done by African Development Bank (AFDB).

4.9.1 Objectives and uses of ICP As a global program, the ICP will produce Purchasing Power Parity (PPP) estimates, with the objective of facilitating cross-country comparison of GDP and its components, such as expenditures on food items, health, education and capital goods.

Statistical Methods, Standards and Guidelines 69

Under the Poverty Reduction related Objectives, the ICP are to provide a reliable information base for national, regional and global policy making and for monitoring of progress.

The ICP data is widely used by international and regional agencies:
(i) To establish international poverty threshold and to monitor progress towards achieving the SDGs poverty reduction target of the World Bank; (ii) To construct the Human Development Index of the UNDP;
(iii) To compare health expenditure per capita of the World Health Organization; (iv) To assess per capita expenditures in education for UNESCO; (v) To monitor the welfare of children for UNICEF; and (vi) To compare the relative sizes of economies and to estimate weighted averages of regional growth rates of IMF/ADB.

4.9.2 It’s Methodology The country members capture and validate ICP price collection using the same method as used in CPI but further analysis is done by African Development Bank (AfDB).

4.10 HARMONISED CONSUMER PRICE INDEX (HCPI) The Harmonised Consumer Price Index (HCPI) Compilation Model is an Excel add-in based Visual Basic for Application (VBA) program developed for providing technical assistance to fund member countries of SADC for consumer price statistics compilation. The package is a prototype model that could also be used for teaching, training, and research purposes. It can likewise serve as a framework from which price collection formats and product classification systems can be integrated to fit country-specific practices.

Its main function is to compile the HCPI for multiple areas at multiple levels of product items to obtain aggregate national level price statistics.

4.10.1 Objectives and uses of HCPI The purpose of the harmonized consumer price indices is to estimate the development in the countries' consumer prices on a comparable basis.

Statistical Methods, Standards and Guidelines 70

HCPI’s main use is for monetary policy, and is used as one of the convergence criteria to assess compliance of member states to economic unions and to monitor progress towards integration.

4.10.2 Methodology of compiling HCPI. (i) The modified Laspeyres formula is used to compute HCPI statistics based on monthly price quotations (or monthly average price quotations) and annual expenditure information using a combination of manual and computer tabulation procedures.
It/0 = ∑ i pi tqb i / ∑ i pi 0qb i which can be written

                   It/0 = ∑

i wi . Ii t / Ii 0
where
wi
is the weight used for product i, It/0
is the price index for product i between the price reference period 0 and period t; pi t
is the price of product i in period t;

pi 0
is the price of the same product i in period 0; qb i
is the base-period quantity of product i expressed as a proportion of the expenditure on product i to total expenditures covered in the HCPI.

(ii) HCPI is calculated using the equivalent of a recursive procedure, in which previous period’s base-weighted long-term price relatives, pt-1, q0 are updated by the current period’s price relatives.

(iii) The geometric mean method is used in computing the price level at aggregate level in view of its multiple advantages.

Statistical Methods, Standards and Guidelines 71

dropped from the other period. This is to ensure consistent sample of price quotations in each period.

4.11 INTEGRATED LABOUR FORCE SURVEY. Integrated Labour Force Survey (ILFS) is the survey conducted by National Bureau of Statistics with the aim of providing a benchmark data of both qualitative and quantitative on some characteristics of the labour force. The survey is conducted after every five-years.

4.11.1 Objectives and uses of the ILFS The broad objective of the Integrated Labour Force Survey is to obtain comprehensive data on the current status of National Labour Market prevailing in Tanzania. The specific objectives of the survey includes obtaining information on Labour Force Participation Rates (LFPR); employment to population ratios; employed population; unemployed population; hours of work; employment in the informal economy; inactivity rates; education attainment and illiteracy; number of child labourers; income from employment and time use in economic and non-economic activities.

Uses of ILFS The survey provides indicators, which are very important in monitoring and assessing economic growth of the country. This information can also be used to assess the impact of various policies on social and economic activities of the people and consequently identify the disadvantaged groups of the population which will be used by policy makers to design relevant policy that address the situation.

4.11.2 Methodology of data production

Frame of the Sample The ILFS, just like other surveys uses the sampling frame derived from Population and Housing Census (PHC).

Statistical Methods, Standards and Guidelines 72

Design of the Sample The sample selection methodology for the ILFS is based on a stratified three-stage sample design.

The first stage involves systematic sampling of EAs within each stratum with Probability Proportion to Size (PPS) from the ordered list of EAs in the sampling frame. An optimal number of EAs is selected at the first stage distributed by both urban and rural areas. The second stage involves systematic sampling procedure for selecting households from each selected EA. At this stage an optimal number of households is selected from each sampled EA.

The third stage involves selection of respondents for Time Use Module. During data collection, interviewer developes a household register for persons aged 5 years or above in accordance to their sex and age. One household member is selected from the register using KISH grid approach and the time use questionnaire is therefore administered to the selected member of the household in each selected household.

Sample Size Determination The selections of EAs follow the systematic sampling procedure within each stratum with Probability Proportion to Size (PPS), likewise the selection of households also follow the systematic sampling procedure, while the selection of individuals within household the KISH grid approach is usually employed.

Estimation Procedure In order for the sample estimates to be representative of the population, it is necessary to multiply the data by a sampling weight, or expansion factor. Principally the basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage). The sampling probabilities at each stage of selection are usually maintained in an Excel spreadsheet with information from the sampling frame for each sampled EA so that the overall probability and corresponding weight is easily calculated.

The basic sampling weight, or expansion factor, is calculated as the inverse of the probability of selection. The weight can be expressed as follows: Where: , m M n M M

hi hi h hi h hi × × × '

Page 11 of 20