Quarterly Estimation of Agricultural Value Added Issues covered….. • Agriculture as a special case for national accounts compilers • data sources for QVA • imputation of work-in-progress for long production cycles • seasonal adjustment • comparison of time series • reference to OECD member country practices Agriculture as a special case • Source data are not ideal – policy users are priority – annual data are priority - agricultural statisticians consider quarterly data for some commodities to be meaningless – high degree of informal activity • But large amount of quantity and price data • Homogeneous commodities • Extreme seasonality in some activities • Production cycles stretch over several quarters for some goods - both seasonal and smooth examples • Output and seasonality can be unpredictable due to weather conditions Quarterly data sources Many countries can use double indicator and double deflation methods - output quantity and price data often available quarterly at a detailed level - but IC may be derived using I:O ratios (O:VA) • starting with output in constant prices • apply IO ratio to give IC in constant prices • difference = VA in constant prices • reflate (revalue) both output and IC with their own prices/indices to give current price output and IC • difference = VA in current prices From constant to current prices Quantity revaluation often used for output Combination of quantity revaluation and deflation/reflation using price indices for IC Data fairly homogeneous at most detailed level - i.e. no significant - - changes in mix of sub-products - changes in quality over time (minimised by updating base year frequently) Data sources - output In OECD countries, output often measured indirectly, i.e. use rather than supply Farms not surveyed quarterly …...but, enterprises using the products are surveyed So, commodity flow methods are used: - surveys give use (IC) - adjusted with any FC - plus exports less imports - plus changes in inventories (if possible) Data sources - intermediate consumption Although supply data for feed, seed and fertiliser may be quarterly, may not be used for IC ….maybe not be available by activity? IO ratios often used, based on previous benchmark data (farm surveys/censuses) …..but IO ratios fail when exogenous effects such as weather, disease, etc. affect IO UK example Farm surveys : annual censuses twice yearly crop production survey, quarterly cereal stocks survey, monthly survey of grain fed to livestock, monthly survey of the production and marketing of hatching chicks and eggs. UK - Use surveys Enterprise acti vi ty Data collected Frequency Dairies Milk purchased, Monthly Output of dairy products Slaughterhouses Nos. of cattle, sheep, pigs, poultry slaughtered and Weekly, monthly and average weights quarterly Egg packers Nos. of eggs graded and packed and average prices paid Monthly to producers Bacon and ham producers Weight of bacon and ham cured Monthly Millers Cereals used, flour produced Monthly Brewers and distillers Use of wheat and barley Monthly UK - Estimating output from inputs Agricultural economists and statisticians closely monitor stocks and flows of feedstuffs….to use in modelling output Surveys of sales and stocks, combined with exports/imports data Enterprise activity Data collected Frequency Feed manufacturers Feedstuffs‟ production, stocks, raw materials. Value and volume of Monthly feed sold to farmers Poultry farmers Production of poultry feed for own use Monthly UK - Estimating IC Although figures on supply of seed, feed and fertilisers are available monthly, they are not used directly for IC (no activity breakdown?) IC is derived using IO ratios but this is under review (effects of disease….?) Australia - Data sources Output wheat and barley - marketing boards livestock - slaughterers wool - trade association IC IO ratios not used due to weather conditions seed - area sown x rate feed - quarterly supply marketing costs - base year value extrapolated by constant price output Types of agricultural output • Continuous, with short production cycles – milk, eggs, chicks, poultrymeat • Single-use plants and livestock - they produce output once only, after a long production cycle – arable crops, livestock fattened for slaughter – (poultrymeat is single-use but a short production cycle) • Cultivated assets – dairy cattle, breeding livestock, draught animals, bees, vines, fruit trees – production of these assets covers rearing them to productive maturity and usually takes > 3 months Production of cultivated assets • When assets are produced for eventual own use, output of unfinished goods is recorded as own-account GFCF • When produced under contract, the sale has been agreed and is considered to be taking place continuously - recorded as sales of unfinished goods for producer and GFCF for purchaser • When assets are produced with the intention of eventually selling them, but the purchaser is not identified, output of unfinished goods = work-in-progress. There is no GFCF associated with this transaction Dairy cattle…... • If a dairy farmer breeds his own replacement milking cows, the production of the calf and then rearing her to maturity is recorded as own-account GFCF i.e. simultaneously output and GFCF • If he buys year-old heifers from a breeder at a market, he records the purchase as GFCF and subsequent rearing to maturity as own-account GFCF (as above). The breeder records the birth and first year of rearing as work-in-progress • If the breeder produced and reared calves under contract to the farmer, then the breeder would record all production as sales, and in parallel, the farmer records GFCF i.e. in all cases, output should be recorded in each quarter on a continuing basis. This avoids negative value added in earlier quarters Long production cycles SNA93 accounting rules state that flows recorded on accrual basis: • when economic value is created, transformed or extinguished, or when claims and obligations arise, are transformed or cancelled. i.e. production should be recorded at the time it takes place, and valued at the prices of that time. So, the production of unfinished products is recorded as work-in-progress. Principle is - in line with business accounting, - better reflects economic reality, - and avoids recording of holding gains. But does it make sense for agriculture? Long production cycles SNA93 (10.107) states….. “In the case of single-use plants or livestock, any such crops or livestock that have not yet been harvested or slaughtered at the end of the accounting period constitute work-in-progress, as follows: (a) When accounts are compiled quarterly, the value of the finished output of an annual crop - i.e. the value of the grain or other crop actually harvested - may be distributed over the quarters in which production has taken place in proportion to the costs incurred each quarter. The value of the output produced in the quarter in which the crop is harvested is then equal to the value of the harvested crop less the value of the additions to work-in-progress produced in the previous quarters;” Example - arable crops….. • At the beginning of the production cycle, output is forecast, in volume/constant price terms e.g. area planted x expected yield x base year average price • .an allocation of costs across quarters is determined, e.g. Q1=0.20 Q2=0.25 Q3=0.30 Q4=0.25 • .the constant price (volume) forecast is allocated across quarters using the costs profile; • .the forecast output (WIP) in each quarter is revalued to the current price of that quarter; • .all quarters are revised after the harvest. NB harvest value (current prices) will not equal value of WIP due to holding gains Eurostat alternative method (Handbook 3.35 +) • Impute output (WIP) as equal to costs in the pre-sale quarters • In the sale quarter, record balance of output (beware of holding gains) • No revisions made to earlier quarters, but output, and values added in last quarter could be strange, and very different from year to year - last quarter being used as “residual” • Also, the pattern of output, and value added, across quarters depends on how costs are defined Eurostat - effect on value added of different cost estimation methods If “full” valuation used for costs: output = intermediate consumption + compensation of employees + taxes on production + operating surplus/mixed income + consumption of fixed capital then, for all quarters: value added = compensation of employees + taxes on production + operating surplus/mixed income + consumption of fixed capital But if costs (and thus output) are estimated as: output = intermediate consumption + compensation of employees then, for pre-sale all quarters: value added = compensation of employees and for the sales quarter: value added = compensation of employees (for the sale quarter) + taxes on production (for whole year) + operating surplus/mixed income (for whole year) + consumption of fixed capital (for whole year) SNA68 recommended allocating all output to sale quarter Problems with imputing WIP SNA93 method: - reasonable QVA profile? (non-negative, smoothed) - but big revisions possible Eurostat alternative: - no revisions - but possible exaggerated harvest peak - negative output possible if harvest fails? IMF concerns…. Although accrual approach is paramount….SNA93 (6.100) : “There may be circumstances in which the uncertainties attached to the estimation of the value of WIP in advance of the harvest are so great that no useful analytical or policy purpose is served by compiling such estimates”. Uncertainty about output has stopped many countries implementing SNA93 Implementation of prices in non-market quarters may be very difficult Imputing WIP does not reflect economic reality in the case of agriculture - farmers do not behave as if income will be forthcoming? Allocation in practice (interpolation, imputation…) • The ways in which countries treat the issue of single-use crops and livestock with a long production cycle (whether to interpolate, or not) vary considerably: – Crop production is assigned to the quarters in which harvest occurs – Austria, Germany, Norway – Crop production is assigned to the third quarter – Denmark, Finland, Netherlands (sugar beet in the fourth quarter) – A quarter of total output is assigned to each quarter – Sweden – Intermediate consumption for crops is distributed over quarters in fixed proportions – Denmark, Norway. Summary of allocation methods • Output equal to harvest/sales (no WIP) SNA68 – possible negative VA - no revisions – large peaks • Output allocated equally to all Qs – no peaks - revisions – steps between years – no relation to economic reality? • Output allocated with costs profile SNA93 – seasonal pattern but smaller amplitude - revisions • Output allocated equal to costs, except harvest Q Eurostat – possible large peaks - no revisions – possible negative output? Agricultural QVA - Selected OECD Countries Constant prices referenced to 1995=100 300,0 250,0 200,0 150,0 100,0 50,0 0,0 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Australia France Germany Korea New Zealand Turkey Agricultural QVA - Nordic/Scandanavian Region Constant prices referenced to 1995=100 180,0 160,0 140,0 120,0 100,0 80,0 60,0 40,0 20,0 0,0 Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1 Q4 Q3 1990 1993 1996 1999 Netherlands Norway Sweden Denmark Finland Agricultural QVA - Selected CCs Constant prices referenced to 1995=100 300,0 250,0 200,0 150,0 100,0 50,0 0,0 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 1994 1995 1996 1997 1998 1999 2000 2001 Poland Czech Rep. Slovak Rep. T urkey Agricultural QVA - Baltic countries Constant prices referenced to 1995=100 250 200 150 100 50 0 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 1992 1993 1994 1995 1996 1997 1998 1999 2000 Estonia Latvia Lithuania 300,0 250,0 200,0 150,0 100,0 50,0 0,0 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Poland Czech Rep. Slovak Rep. T urkey Estonia Latvia Lithuania Seasonal adjustment • Zero or negative values cause problems • Multiplicative models not possible • Additive models may not be appropriate for series • Australian solution = to use pseudo-additive model • Previously had „adjusted‟ by allocating VA equally across Qs („annual spreading‟) • Only allows growth at annual joins (Q2-3 in Australia) Discussion points... Do participants : • Survey farms quarterly, for output and IC? • Use IO ratios? • Survey processors for use data (commodity flow)? • Survey suppliers for IC data? • Impute WIP (allocate output) for long production cycles? • Have problems with seasonal adjustment of agricultural QVA?
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