FISIM estimation and allocation to industries and final users
Cameroon: Financial Intermediation Services Indirectly Measured (FISIM)
I. Issues under consideration
In general, only a small part of intermediation services is charged explicitly, as commissions, by financial institutions (banks) to their customers. Financial institutions charge implicitly (i.e. indirectly) a large part of these services to their customers by lending at higher interest rates to their borrowers and borrowing at lower interest rates from their depositors. Therefore FISIM is the indirect measure of the value of the production of services that financial intermediaries (banks) do not explicitly charge to their customers.
For the year 2005, the National Institute of Statistics of Cameroon has decided to put in place a benchmark year for national accounts. One of the main objectives of that benchmark year was to implement the 2008 SNA. So, for the treatment of FISIM, Cameroon is currently following the recommendations of the 2008 SNA version. Before that, Cameroon was following the 1993 SNA version, but the consumption of FISIM was not allocated between users.
Following the 1993 SNA, the 2008 SNA suggests the use of the reference rate method to deal with the issue of calculating and allocating the FISIM. While the 1993 SNA left the possibility to countries to continue to follow the 1968 SNA convention whereby the whole of FISIM is allocated to intermediate consumption of a notional industry, this possibility has been removed in the 2008 SNA. FISIM should be allocated between the different users, and the allocated amounts treated either as intermediate consumption or as final consumption or exports.
By application of the reference rate method, the 2008 SNA calculates the output of FISIM as difference between the rate paid to banks by borrowers and the reference rate plus the difference between the reference rate and the rate actually paid to depositors. Thus FISIM is calculated according to the formula (rL - rr) L + (rr - rD) D, where rr is the reference rate, rL is interest rates on loans and rD is interest rates on deposits, L is the total amount of loans and D is the total amount of deposits. The reference rate of interest is a risk-free interest rate and does not include any financial intermediation services. The 2008 SNA suggests that the interbank rates are suitable proxies for the reference rate.
II. Data requirements, availability, gaps and meeting challenges to fill data gaps
For the calculation of FISIM, data on the total amount of loans granted to borrowers and the total amount of deposits made by lenders are needed for the accounting period; also needed are data on the interests paid to banks by borrowers and interests received by depositors from banks; debtor interest rates (interest rates on loans), creditor interest rates (interest rates on deposits) and inter-bank borrowing and lending rate need also to be known. These data need to be available by sector or industries if possible. All these data are normally available from the central banks and commercial banks statistics.
In Cameroon, the mains data sources for the calculation of FISIM are:
· The central bank (BEAC[1]) monetary situation. This data source is a summary of the data contained in the balance sheets of financial institutions (banks, central bank and other financial institutions). It gives information on the financial assets owned and the liabilities owed by financial institutions towards the other institutional units. A concordance table is set up to pass from banks’ statements to national accounts’ financial assets (loans and deposits) and identify the debtor or creditor sector for each asset.
· The statistical and fiscal statements of banks and credit cooperatives. This data source helps to calculate property incomes received by banks and credit cooperatives, the interests that they pay and also the commissions that they receive or pay.
· The balance of payments (BoP). This data source gives information on interests paid on loans and commercial credits at credit (resources for the national economy) and at debit (uses) and by institutional units. This information permits the calculation of imports and exports of FISIM.
· The statement of the financial operations of the State. This data source gives the amount of interests paid by the central State on the domestic debt and the external debt.
· The statistical and fiscal statements of non-financial corporations and the administrative or management accounts of public administrations. This data source gives information on the structure of interests paid or received by industries. This structure is used to breakdown the intermediate consumption of FISIM by industry.
· Other publications of the central bank, in search of interest rates. These documents provide floor creditor interest rates, ceiling debtor interest rates and inter-bank borrowing and lending rate.
III. Compilation practices
III.1. Calculation of FISIM and allocation to final users
To calculate the FISIM, the steps behind are followed:
1) Identification of financial assets and liabilities that correspond to loans and deposits, by institutional sector: when there is no information on stocks of loans and deposits, data on interests paid or received are used to estimate the stock of loans and deposits by using average interest rates by sector.
2) Determination of interest rates by institutional sectors: to calculate FISIM we need to know the interests rates that banks charge to their borrowers (debtor rate) and the one that they pay to their lenders (creditor rate). Given the lack of information on the rates that banks actually apply to their customers by sector, we decided to use the floor creditor interest rate and the ceiling debtor interest rate.
3) Calculation of actual interests paid on loans and deposits detained by resident banks: actual interests paid to or received from banks are calculated for each sector, using the amounts in step 1 and the rates in step 2.
4) Calculation of FISIM for resident banks: the reference interest rate is used to calculate reference interest (i.e. SNA interest according to 2008 SNA) on loans and on deposits. We use the inter-bank borrowing and lending rate, as reference rate, for this calculation. FISIM of resident banks is obtained by sector using the formula: (actual interests on loans – reference interests on loans) + (reference interests on deposits – actual interests on deposits).
5) Calculation of importations of FISIM: importations of FISIM are calculated from two elements of the BoP: incomes of investments of public administrations and incomes of investments of others sectors. The latter are supposed to be only units of the non-financial corporation’s sector. A method of calculation similar to the above (steps 1 to 4) is implemented to calculate importations of FISIM.
6) Synthesis of information on interests and FISIM: the national production of FISIM and the importations of FISIM are put together to build up the commodity flow table of FISIM for the global economy.
III.2. Allocation of FISIM by kind of activity
The breakdown of intermediate consumption of FISIM by kind of activity is done in two ways:
o For the market industries, the structure of the interest paid by firms from the statistics and tax returns (DSF) is used;
o The structure of the production is used for non-market activities.
IV. Way forward
The present technical note presents what has been done in the 2005 benchmark year national accounts compilation. It was just the first step forward. To come over data challenge we have faced, more investigation has to be done to get average actual interest rates that banks practice for their different customers (corporations, government and households), through a survey for example. Also, the 2008 SNA recommends that FISIM should be calculated on mortgages, and treated as intermediate consumption of households for their construction of dwellings. The current methodology does not estimate that component. Hence all consumption of FISIM by households is only final consumption. This issue has to be addressed as well in future development of the methodology for Cameroon.
Reference:
1. Pégoué Achille (2011). Traitement des intérêts et du SIFIM dans la base 2005 du Cameroun. Institut National de la Statistique. Cameroun.
2. Direction de la Statistique et de la Comptabilité nationale du Cameroun (2001). Méthodologie d’élaboration des comptes nationaux selon le SCN1993.
3. United Nations (1993). System of National Accounts (1993 S NA).
4. United Nations (2008). System of National Accounts (2008SNA).
Econometric approach to calculate imputer rents of owner occupied dwelling services
Ø Issues under consideration
According to the national accounts, the construction or purchase of housing by a household is considered as an investment. For owners and similar (free housing), they are supposed to pay rent (called imputed rent) for the property they occupy. Thus, they produce dwelling services they consume.
Ø Data requirements
The necessary data are household budget survey including a section on housing and habitat characteristics: region, residence (urban, rural), type of dwelling, number of rooms, main floor material, main wall material, main roof material, main source of lighting, type privies (WC with flush, fitted toilets, unimproved toilets,…), mode of evacuation of household waste, gender, highest qualification and marital status of household head, …
A question allows owners and assimilated to assess the amount of rent they have to pay if they had let the house they occupy. This approach raises a number of questions: owners and similar are sufficiently informed to give the right information? We think that they will tend to give the amount of which they would rent their house, not that the law of supply and demand would impose.
Ø Compilation practices
Thus, econometric modeling, based on dwelling and household characteristics to assess the amount of rent, is more appropriate. Then, we proceed with the imputation of households living free rent.
Econometric model to estimate is a model selection: Heckman model. Theoretically, it is estimated two equations:
i) Main equation:
ii) Selecting equation:
with:
We assume that the endogenous variable (the logarithm of the annual rent) is actually observed if the household pays rent (selecting equation).
The inverse Mills ratio resulting from this regression, which is actually a probit model, is injected into the main equation
Imputation
The values estimated by the model have three scenarios in terms of owner and free housing households:
· Some households are on the supply curve, and give the amount they would receive if they had to put their house rent;
· Others lie on the demand curve, and underestimate therefore the actual value of their dwellings (giving the amount they would pay if they were renting).
· The last category consists of those who are at the intersection of supply and demand curve.
The results obtained are as follows:
Table 1: Average of the key variables by tenure status
Tenure status / Declared annual rent / Estimed annual rent by the model / Annual rent with imputation of the owners and relatedowner with land title / Mean / 361,1568 / 291,5274 / 291,5274
N / 321209 / 321652 / 321652
Std. Deviation / 692,0024 / 468,5245 / 468,5245
owner without land title / Mean / 109,1305 / 97,2364 / 97,2364
N / 1644088 / 1645112 / 1645112
Std. Deviation / 153,2876 / 103,4022 / 103,4022
lease / Mean / 183,9946 / 187,7613 / 183,9946
N / 739809 / 739809 / 739809
Std. Deviation / 401,9304 / 297,7206 / 401,9304
rental sale / Mean / 457,8296 / 735,0616 / 457,8296
N / 4158 / 4158 / 4158
Std. Deviation / 379,1171 / 911,2270 / 379,1171
Housed by the employer / Mean / 171,5482 / 190,0020 / 190,0020
N / 100967 / 101587 / 101587
Std. Deviation / 499,0805 / 460,3411 / 460,3411
Housed by a friend/ parent / Mean / 94,6291 / 95,7644 / 95,7644
N / 288560 / 288665 / 288665
Std. Deviation / 149,1384 / 97,6168 / 97,6168
other / Mean / 103,7695 / 94,5743 / 94,5743
N / 19753 / 19753 / 19753
Std. Deviation / 145,5651 / 88,0969 / 88,0969
Total / Mean / 153,9591 / 142,4384 / 141,1761
N / 3118544 / 3120736 / 3120736
Std. Deviation / 341,5447 / 250,6423 / 280,6720
N= number of households, Std. Deviation = standard deviation
Data sources for compiling supply and use table (SUT)
Construction of SUT requires information from various sources on the following components of supply and use, disaggregated by products. In Cameroon, the following sources of data are used for each component of SUT.
Ø Supply table
Item / Sector / Sources of dataDomestic output by industries / Formal sector / - Statistics and tax returns (DSF) (financial and non-financial corporation)
- Government budget documents/ government finance statistics (revenue and expenditure)
- Finance statistics of social security Fund
- Finance statistics of local administration and public administrative companies
- Administrative statistics on agriculture, livestock, forestry, fishing and crude oil.
- General business census 2009: it include information on NPISHs
Informal sector / Survey on employment and the informal sector (2005, 2010)
Imports / Goods / Merchandise trade from customs authorities
Services / Balance of payment statistics
Trade margins/Transport costs / Formal sector / Statistics and tax reporting of companies: provides the trade margins and the transport cost of the formal companies
Informal sector / - Survey on employment and the informal sector (2005, 2010): provides the trade margin by product
- Prices survey on food products: provides the trade margin and transport cost by product
Taxes/subsidies on products / - Government budget documents, the General Tax Code and the Finance Law for taxes;
- Stabilization Fund of oil prices for fuel subsidies.
Ø Use table
Item / Sector / Sources of dataIntermediate consumption by industries / Formal sector / - Statistics and tax returns (DSF) (financial and non-financial corporation)
- Government budget documents/ government finance statistics (revenue and expenditure)
- Finance statistics of social security Fund
- Finance statistics of local administration and public administrative companies
- Administrative statistics on agriculture, livestock, forestry, fishing and crude oil.
- General business census 2009: it include information on NPISHs
Informal sector / Survey on employment and the informal sector (2005, 2010)
Exports / Goods / Merchandise trade from customs authorities
Services / Balance of payment statistics
Household final consumption expenditure / Household income-expenditure surveys 2007
Final Consumption expenditure of NPISHs / General business census 2009: it include information on NPISHs
Government final consumption expenditure / Government budget documents/ government finance statistics (revenue and expenditure)
- Finance statistics of social security Fund
- Finance statistics of local administration and public administrative companies
Gross fixed capital formation / Formal sector / - Statistics and tax returns (DSF) (financial and non-financial corporation)
- Government budget documents/ government finance statistics (revenue and expenditure)
- Finance statistics of social security Fund
- Finance statistics of local administration and public administrative companies
- Administrative statistics on agriculture and livestock
Informal sector / Survey on employment and the informal sector (2005, 2010)
Change in inventories / Statistics and tax returns (DSF) (only non-financial corporation)
Ø Value Added components