the_complete_and_consistent_data_base_coco_for_the_national_scale
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the_complete_and_consistent_data_base_coco_for_the_national_scale [2020/02/13 07:55] – [COCO2: Data Preparation] matsz | the_complete_and_consistent_data_base_coco_for_the_national_scale [2020/02/13 09:26] – [COCO2: Estimation procedure] matsz | ||
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This procedure has developed as a path dependent compromise between computation time and presumed quality. It starts with an estimation of land use in combination with agricultural land balance, including the land transition between LU classes. This determines the utilisable agricultural area (UAA) and non-agricultural land use. Step 2 distributes crop areas within the fixed UAA from step 1 and estimates crop production and yields. Step 3 only tackles the complete animal sector data (activities, | This procedure has developed as a path dependent compromise between computation time and presumed quality. It starts with an estimation of land use in combination with agricultural land balance, including the land transition between LU classes. This determines the utilisable agricultural area (UAA) and non-agricultural land use. Step 2 distributes crop areas within the fixed UAA from step 1 and estimates crop production and yields. Step 3 only tackles the complete animal sector data (activities, | ||
- | **Figure 3. Overview on main estimations in for the consolidation of national data in Europe (in coco1.gms)** | + | **Figure 3: Overview on main estimations in for the consolidation of national data in Europe (in coco1.gms)** |
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An overview is given in the following figure. | An overview is given in the following figure. | ||
- | **Figure 4. Overview on main elements in the finalisation step for the consolidation of national data in Europe (in coco2.gms)** | + | **Figure 4: Overview on main elements in the finalisation step for the consolidation of national data in Europe (in coco2.gms)** |
{{:: | {{:: | ||
+ | |||
+ | In spite of only limited subtasks tackled in coco2.gms, the multitude of different data inputs is comparable to that in COCO1. | ||
+ | |||
+ | **Include file // | ||
+ | |||
+ | Various input files are collected with some adjustments to match to CAPRI definitions and with some gap filling. As the consumer prices follow from a top down expenditure allocation problem, the input data range from macroeconomic information to very detailed prices of food items. | ||
+ | |||
+ | * Consolidated data from COCO1 | ||
+ | * Macroeconomic information from Eurostat and UNSTATS: Exchange rates, population, GDP deflator, private consumption of households in current prices. | ||
+ | * Price index information: | ||
+ | * Expenditure by product groups (from Eurostat and national sources) | ||
+ | * Auxiliary data for special cases (Prices for some milk products in selected countries, fish meal information etc) | ||
+ | * Country Sheets of the Western Balkan and Turkey: Exchange rate, inhabitants, | ||
+ | * Disaggregate absolute consumer prices for selected narrowly defined food items (ILO and Eurostat) | ||
+ | |||
+ | Where available, producer prices for milk products were already included from Eurostat statistics (Agricultural prices and price indices) in COCO1. Completeness was not achieved in COCO1, however, because processed dairy products are not part of the EAA. Here we complete some gaps using price information for some Member States and (partly assumed) relationships among dairy product prices and their fat and protein contents. | ||
+ | Data on total consumer expenditures as well as expentitures by food groups are included from various sources as described in Chapter 2.2.2.5, partly extended using general price index information. | ||
+ | |||
+ | Consumer price index weights and price indices for food aggregates (2005=100) are coming from Eurostat tables on HICP. Supplementary information for Albania, Bosnia and Croatia comes from national agencies. The price index weights are used to extend older series on food expenditure by product groups (say “meat”) which have been discontinued (see below under file coco2_shares.gms). | ||
+ | |||
+ | Finally we use very narrowly defined absolute consumer prices (e.g. for spaghetti) and price indices. The earlier years (before 2008) had been provided by ILO which has discontinued this activity. For a subset of those Eurostat offers matching information as “detailed average prices (table prc_dapYY) that has been used to extend the ILO series. These prices are mapped to CAPRI regions, products and units (// | ||
+ | |||
+ | Price indices for food and non-alcoholic beverages from HICP as well as the general food price index are used to complete the disaggregate ILO prices for single typical food items. | ||
+ | |||
+ | Finally another HPD estimator is used to adjust the dissagregate prices to be (somewhat) in line with Eurostat information on relative food price levels across Europe. | ||
+ | |||
+ | **Include file // | ||
+ | |||
+ | Expenditure shares are defined and completed top-down using simple OLS estimates against related statistical expenditure information or, as a last fall back option, based on a trend. | ||
+ | |||
+ | The food expenditure share completions start with data from COICOP level 3 giving results on food and non-alcoholic beverages. Further disaggregation relies on historical Eurostat data (HIST), on the above mentioned index weights from HICP and partly national data (Germany and Spain). | ||
+ | |||
+ | A conveninent expenditure group is potatoes as these expenditure shares may be extrapolated based on COCO1 human consumption multiplied by producer price as regressors for OLS. | ||
+ | |||
+ | ====COCO2: Estimation procedure==== | ||
+ | |||
+ | **Include file // | ||
+ | |||
+ | The approach to determine consumer prices is to distribute food expenditure on groups with consumption quantities given from COCO1 results such that endogenous consumer prices link endogenous expenditure with exogenous quantities. Deviations of estimated expenditure and consumer prices from their supports is penalised in an entropy framework. Estimation is done year by year, starting with the most recent year where hard data are usually available to a greater extent than for the oldest years in the database. Including consumer price changes (always relative to the previously solved year) serves to stabilise the results to some extent such that the objective does not only have supports for the consumer prices, but also for their changes. The entropy problem is solved by maximizing: | ||
+ | |||
+ | \begin{align} | ||
+ | \begin{split} | ||
+ | max_t &- \sum_{m, | ||
+ | & | ||
+ | & | ||
+ | & | ||
+ | & | ||
+ | & | ||
+ | & | ||
+ | |||
+ | \end{split} | ||
+ | \end{align} | ||
+ | |||
+ | where //m// represents the region, //j// the food item with consumer price, FOPOS the food group, //t// stands for the current estimation year, t_1 for the year estimated before and k for the number of support points (=3). | ||
+ | |||
+ | Parameters are | ||
+ | | \(HCOM_{m, | ||
+ | | \(UVAD_{m, | ||
+ | |\(CPS_{m, | ||
+ | |\(DCPS_{m, | ||
+ | |\(EXS_{m, | ||
+ | |\(TOFACS_{m, | ||
+ | |\(PQ_k\) |A priori probabilities for support points| | ||
+ | |\(TOFO_{m, | ||
+ | |\(PE_{m, | ||
+ | |\(PED_{m, | ||
+ | |\(CP_{m, | ||
+ | |\(DCP_{m, | ||
+ | |\(PEX_{m, | ||
+ | |\(PFAC_{m, | ||
+ | |\(EX_{mFOPOS}\) |Group expenditures| | ||
+ | |\(TOFAC_m\) |Food expenditure slack| | ||
+ | |||
+ | Constraints are as follows: | ||
+ | Summing up probabilities for support points | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{k\forall_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{k\forall_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{k\forall_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{k\forall_{m}(TOFAC.LO_m\ge TOFAC.UP_m)} PFAC_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Define consumer price changes from support points | ||
+ | |||
+ | \begin{equation} | ||
+ | DCP_{m,j} = \sum_{k\forall_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Of course consumer prices changes are also related to the last simulation result (which is for T+1 due to backward looping) | ||
+ | |||
+ | \begin{equation} | ||
+ | DCP_{m,j} =UVAD_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Define consumer prices from support points and probabilities | ||
+ | |||
+ | \begin{equation} | ||
+ | CP_{m,j} = \sum_{k\forall_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Define group expenditure from support points and probabilities | ||
+ | |||
+ | \begin{equation} | ||
+ | EX_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Define total expenditure slack from support points and probabilities | ||
+ | |||
+ | \begin{equation} | ||
+ | TOFAC_m=\sum_{k\forall_{m}(TOFAC.LO_m\ge TOFAC.UP_m)} PFAC_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Exhaustion of food expenditure may be relaxed with a slack factor different from one. However, this “last resort” to achieve feasibility in the expenditure allocation problem is limited to years and countries with precarious data and subject to strong penalties. | ||
+ | |||
+ | \begin{equation} | ||
+ | \sum_{FOPOS} EX_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | Consistency of group expenditure | ||
+ | |||
+ | \begin{equation} | ||
+ | EX_{m, | ||
+ | \end{equation} | ||
+ | |||
+ | For most countries the exhaustion of total expenditure is the only evident hard constraint (and even this is relaxed in problem cases). However, as the penalties for group expenditure are set high, and furthermore as the range of expenditure supports defines additional implicit hard constraints, | ||
+ | |||
+ | **Include file // | ||
+ | |||
+ | The initialisation, | ||
+ | |||
+ | * The initialisation tries to ensure positive consumer margins by the assignments of expected values and by specifying bounds on estimated consumer prices. The reference point for these margins is an average of EU and national prices that reflects the importance of domestic sales vs. imports. | ||
+ | * Bounds and spread of supports around expected consumer prices are set high for items without ILO style prices (say “table olives” TABO) or where the fit of available price information is questionable (e.g. cabbage prices for “OVEG”). | ||
+ | * A checking parameter (“p_checks”) permits to check the iniitalisation in case of infeasibilites. The most frequent case observed in the last years is that lower bounds on oils expenditure become binding, suggesting the need for some systematic mismatch of price and expenditure information for this group. | ||
+ | |||
+ | ====COCO2: Final completions==== |
the_complete_and_consistent_data_base_coco_for_the_national_scale.txt · Last modified: 2022/11/07 10:23 by 127.0.0.1