Chained unit value indexes of Galicia, the Basque Country and the Murcia Region. Methodological document.

Transcription

1 Chained unit value indexes of Galicia, the Basque Country and the Murcia Region. Methodological document. 1. Introduction Commercial foreign trade is an indicator of the increasingly greater openness of developed economies, as can be seen from the monthly information on Foreign Trade Statistics provided by the Spanish Tax Office. Between 2000 and 2008, Spain s total imports grew by nearly 70% while exports were up by over 50% during the same period. If we look at the foreign trade of the Autonomous Communities of Galicia, the Basque Country and the Murcia region, this growth was still higher, as the aggregate of the three Autonomous Communities doubled imports and a 70% growth in exports was recorded. As a result of the great growth in imports, the foreign trade balance which was practically null in 2000, came to nearly six thousand million euros in 2008, which accounted for 3.8% of the GDP of the three autonomous communities. Special mention should be made of the significant growth in the imports of the Murcia Region, which was up by 155% over the eight years in question, followed by the Basque Country that nearly doubled its total imports, while Galicia registered growth slightly over the national level, at 74%. With respect to exports, the Autonomous Community that registered greatest growth was Galicia with nearly 90% and it is the only of the economic territories included in the study where the growth of the exports was higher than that of the imports. In the Basque Country, exports were up by nearly 70%, while their growth in the Murcia Region was slightly over 40%. Nonetheless, the weight of the foreign trade of the three autonomous communities is uneven. The value of the total goods traded abroad in 2008 in the Murcia Region accounted for 3.2% of the national total, which stood at 6.6% in Galicia and 8.5% in the Basque Country. This uneven weight of the foreign trade of the three autonomous communities is related with the also uneven weight of its economies, and it is therefore clearer to relate it with the Gross Domestic Product (GDP) by calculating the opening-up rate. The three opening-up rates had similar values, and stood at 53% in the Murcia Region, 55% in Galicia and 58% in the Basque Country in For the Spanish economy as a whole, in the same year, the opening-up rate is 43%, which indicates that these three economies are more open to other countries than the national average. Foreign Trade Statistics has the Single Administrative Document (S.A.D) and the INTRASTAT system used for collecting statistics on the trade in goods between countries of the European

2 Union as source of information. It allows us to establish the commercial flows of the companies of different countries, including in the case of Spain, information on the Autonomous Community which is the origin or destination of each commercial flow. It is therefore information based on records, which provide highly relevant information about the statistical value and the amount traded in each operation, which converts these records into an important source of information on the prices of those operations at a low cost, as it means that surveys do not have to be conducted with export and import companies. The indexes that are prepared based on this information are the foreign trade Unit Value Indexes (IVU) and provide an approach to the real price indexes of the operations to import and export goods. It is an approach to the prices of foreign trade operations, as the prices to which they refer are not perfectly differentiated individual goods, but rather more or less uniform sets of classes of goods. The main characteristics of the IVUs are: a) They can be used to approximate the trend of the import and export prices b) They are used as deflators for foreign trade in constant euros. c) They are used to construct important indicators such as the real trade ratio or competitiveness indexes. The Ministry for the Economy and the Treasury has obtained the IVUs for the Spanish economy since 1968, while at Autonomous Community level, special mention should be made of the indicators obtained by the Galician Statistics Office (IGE) since 2000 and the Andalusian Statistics Office (IEA) since The IGE has performed a change of base of its IVUs in 2007 and used the opportunity to adapt the methodology used to the reality of changing trade with new products constantly entering and leaving. Furthermore, the calculation formulas recommended by Eurostat are applied in the new 2005 base, together with the chained indexes based on the Fisher formula. These formulas are applicable to the IVUs as the latter are calculated based on records that contain all the goods traded, while other price indexes (IPC, IPRI), which must be based on a sample of goods, which would be very expensive to modify every year. In 2008, the Murcia Regional Statistics Centre (CREM) and the Basque Statistics Office (EUSTAT) considered the need to obtain an indicator of the prices of the foreign trade operations in their respective autonomous communities. The fact that these indicators had already been estimated in an Autonomous Community and the suitability of its methodology led both entities to choose the methodology that was already being applied by the IGE. They received the support and help of the technicians in charge of the same operations in Galicia. This meant that price 2

3 indicators of foreign trade operations in three perfectly comparable autonomous communities could be obtained at a low cost and they are therefore discussed jointly in this publication. 2. Main methodological aspects The chained unit value indexes (IVU) are based on the annual selection of uniform product groups known as elementary classes from which unit values are obtained (as an approach to the prices). Year-on-year comparisons are performed using the unit values of these elementary classes and they are then chained to obtained indexes. Schematically, the indexes are calculated using the following process: 2.1 Processing the base statistical information. 2.2 Defining the elementary classes. 2.3 Calculating the unit values of the elementary classes. 2.4 Selecting elementary classes. 2.5 Calculating the simple indexes of the elementary classes. 2.6 Designing the aggregation mechanism to build composite indexes. 2.7 Calculating the aggregate IVUs by usage groups. 2.8 Processing the non-selected elementary classes. 2.9 Debugging. This document sets out the main methodological aspects of the IVUs obtained by the IGE, EUSTAT and CREM and the specific characteristics of each one of them. For further details used and specifically, all the mathematical formulas of the indexes, classifications and correspondences used, please consult the methodologies available from the three statistical entities. 2.1 Processing the base statistical information. As has already been indicated, the base statistical information comes from the administrative records of the Customs and Special Levies Department of the Spanish Tax Office, which every month collects the foreign trade operations of goods that occur in Spain, indicating the Autonomous Community that is the origin or destination of those international flows. The data are directly downloaded from the Spanish Tax Office s website. In order to calculate the unit value indexes, the information of interest is: the flow (export or imports), the origin or destination country, the product (classified by Combined Nomenclature (NC) 3

4 or the Integrated Tariff of the European Communities (TARIC) codes, the value of the operation, the weight, the number of traded units of the goods and the province of origin or destination. The province of origin/destination" of the Customs Department data is used to allocate the province, except when this field appears without a value, in which the province is allocated according to the "fiscal domicile province of the exporter/importer" variable. Those products whose prices are not in line with the general trend, such as jewels or works of art, were excluded from the base information. Vessels and aircraft were also eliminated as their presence is not guaranteed every month and as their potential high value greatly distort the series. The excluded products are the following groups of the CUCI classification: 667, 792, 793, 811, 896, 897, 899, 911, 931, 961, 971. In the IVUs of the Basque Country, in addition to the aforementioned products, trains, which are in group 791 of the CUCI, are not included when calculating the indexes, to avoid any distortion that that may cause to the series. When designing the IVUs of the Murcia Region, the oil imports needed to processed in a special way. In 2000, the imports of this Autonomous Community doubled, due to the oil imports for the oil pipeline that was opened between the Cartagena and Puertollano refineries that year. In order to avoid the impact of these imports, which are allocated to the Murcia Region in the Foreign Trade statistics but which according to the European Accounts System, SEC95 (3.133) must be considered as import of the Autonomous Community of Castilla-la Macha, corrector coefficient have been applied since that year to the imports of products included in the CUCI Defining the elementary classes. The elementary classes are made up of product groups for which the unit values are calculated at the greatest level of desegregation. On the one hand, it is desirable to have the most desegregated classes to ensure their uniformity, but on the other hand, the variety of situations, the reduced sample size which we face when analysing a smaller autonomous community (when not directly the lack of observations) and the possible existence of errors, encourages the consideration of wider classes. The elementary classes are defined using the intersection of the five following characteristics: 1. Flow: A difference is made between imports and exports. 2. Geographical zone: 4

5 Given that the foreign trade data must be divided due to the geographical desegregation, the following desegregation is carried out: 1. Euro zone countries (EMU Area) 2. European Union countries that do not belong to the EMU Area (EU Area) 3. OECD countries that do not belong to the EU area (OECD Area) 4. Other countries (RM Area). The IVUs of Galicia and the Basque Country consider these four geographical zones to define their elementary classes, while the smaller size of the Murcia Region meant that it was advisable to consider only three zones, by considering the EU countries overall and without distinguishing whether or not they belong to the euro zone. The IVUs of Galicia took into account the 25 countries making up the EU on the 1st January 2005, while the 27 countries that currently make up this economic area were considered in the Murcia Region and the Basque Country. Nonetheless, the small weight, 0.4% of the total, of the commercial trade between Galicia and Rumania and Bulgaria means that the EU IVUs of the three autonomous communities may be compared without significant errors. 3. CUCI Classification: The elementary classes are defined using the CUCI groups (International Trade Unified Classification). The CUCI regroups the TARIC classification (which was originally used to classify the data) in categories according to the materials used, the preparation stage and the final use. This classification is used to three digits. 4. Usage Group (UG): This is a classification criterion based on the requirements of the Economic Accounts Systems (SEC) and prepared by the General Sub-Directorate of Macroeconomic Analysis (SGAM) of the Ministry of the Economy and the Treasury and the Spanish Statistics Institute (INE). This classification is used to four digits, which takes a total of 28 different groups, to define the elementary classes. 5. Unit type: It was decided to consider the unit type in which the operation is measured as an additional criteria to define the elementary class. Therefore, if two products are measured in different units, they will belong to two different elementary classes, even though they are assigned to the same GU and to the same CUCI. 5

6 Therefore, the initial elementary classes are obtained using all the intersections that can occur between the trade flow, geographical zone, GU to four digits, CUCI groups and unit types, even though it must be taken into account, for example, that not all the unit types can occur in all CUCI groups when determining the real number of possible classes. The CU and CUCI variables are obtained using the correspondence between these classifications and the TARIC, which is the product classification used in foreign trade. 2.3 Calculating the unit values of the elementary classes. The unit value of an elementary class in a specific month is calculated as the weighted average of the prices of the operations belonging to that class. The weighting reflects the relative importance of the amount trade in each operation with respect to the total operations in said month. The main drawback of using unit values is the composition effect, which may appear when the relative structure of the trade is modified within the group where the unit value is calculated. In these cases, the unit value may vary as the structure of the articles include in an elementary class was altered, even though the prices of said articles are not modified. 2.4 Selecting the elementary classes. The base statistics information does not guarantee that a representative unit value can be calculated for the total operations carried out for all the elementary classes observed. Therefore, once the unit values of all the elementary classes are obtained, a method to select elementary classes needs to be designed so that we can effectively estimate unit values in a reliable manner, and a procedure to process the elementary classes that were not selected. As far as the problems that prevent the reliable estimation of unit values and which condition the processing to be given to all the classes are concerned, we can group them into two: 1) The problem of the sample size: It refers to the need to have a minimum number of monthly observations of the elementary class to be able to calculate the relevant IVU in a regular manner. Given that the IVUs are calculated for three autonomous communities of different sizes, it is obvious that the minimum observation threshold must be adapted to each case in particular. The minimum sample size in the case of Galicia is 162 observation per the year, there are 155 observations in the Basque Country and a minimum threshold of 100 annual observations has been set for the Murcia Region. In all cases, there is also the requirement that there are observations twelve months a year. 6

7 Further, a second selection considers those classes that, even though they do not comply with the aforementioned size criteria, have a high weight in the trade of the flow, origin and GU to one digit to which they belong and they also have observations every month of the year. 2) The problem of the uniformity of the classes: Given the definition of the elementary classes, all the products with the same units that belong to the same GU to four digits and the same CUCI group are integrated in a single elementary class and are processed as equivalent goods when calculating the unit value of the class. In the majority of the cases, these products are, in fact, very similar, and the advantages associated to this common treatment overcome the drawbacks of the aggregation. However, it will not be so in some cases, which could lead to elementary classes that are too heterogeneous, so that the estimated unit values will not be very representative of the prices of the operations effectively carried out. The uniformity of the classes cannot be directly measured according to the physical or technical characteristics of the products that integrate the class, or for the dispersion of the prices that integrate the operations; it is considered that there is a problem that must be processed when the estimator of the unit value is unstable, with unstable estimator being taken to be one that has a high variation coefficient. When obtaining the IVUs, it has been considered that the class is sufficiently stable if the variation coefficient is under 35%. This restriction would leave out of the selection those classes with a heterogeneous composition, where the estimation of the unit value is not very robust, and which has a high trade volume. Thus, instead of estimating the unit values as weighted averages of the prices of all the operations performed, a robust estimate procedure based on L-estimators is used. r 1 +r 2 trimmed means are used, where each individual price is weighted by the relative amount (weight or number of units) of each record with respect to the total effective observations. The r 1 +r 2 trimmed means are obtained by eliminating the [nr 1 ] operations with the lowest prices and the [nr 2 ] operations with the highest prices from the total n observations of each class. The procedure used to decide the trimming type is as follows: the variation coefficient is calculated for each selected class. If this is lower or equal to 35%, the class becomes part of the selected ones. And if the variation coefficient is over 35%, the following are calculated: a) The variation coefficients of the following trimmed means, 0+0, 0+5, 5+0, 5+5, 0+10, 10+0, 5+10, 10+5, 0+15, 15+0, 10+10, 5+15, 15+5, 10+15, 15+10, 15+15, where the first digit represents the trimming of the lowest prices and the second digit the highest. b) The intraclass coverage of the same trimmed means, which is defined as the quotient between the total value of the operations effectively used to estimate to unit value and the total value of the initially available operations. 7

8 The trimming that satisfies that the variation coefficient is under 35% provided that the intraclass coverage is over 50%. The following table shows the number of selected elementary classes in the IVUs of the three autonomous communities between 2000 and It can be seen how the growth in commercial trade results in a larger number of operations and therefore in being able to have a greater number of elementary classes that comply with the conditions set to be selected. In Galicia, the number of selected classes rose from 416 to 744, which was an increase of 80%. The IVU of the Basque Country are the one that select the largest number of elementary classes, in keeping with the greater volume of its foreign trade, rising from 746 classes in 2000 to 1002 in 2008, 35% up. In the Murcia Region, a total of 376 classes were selected in 2000, which were 50% higher in number (559) in Table 1. Number of elementary classes selected annually to calculate the IVUs Year Elementary Classes Galicia Basque Country Murcia Region It seems obvious that the annual selection of classes may notably improve the quality of the estimated IVUs in relation to other indexes that keep the same selection of classes of the base year, particularly in periods where there is a significant increase of the economic phenomenon studied. Table 2 shows the distribution of the statistical value of the total foreign trade and of the elementary classes selected for each flow by GU to one digit. It is evidently desirable that both distributions are reasonably similar. 8

9 Table 2. Distribution of the statistical value of foreign trade and of the elementary classes selected by flow and usage group, average for Distribution by flow and usage groups (%) Foreign trade Selected classes Exports Imports Exports Imports Galicia Basque Country Murcia Region Consumer goods 54,1 26,1 49,8 37,5 Capital goods 13,3 6,0 5,1 9,6 Intermediary goods 32,6 68,0 45,0 52,9 Consumer goods 16,9 10,8 24,3 29,4 Capital goods 15,8 6,3 16,1 13,8 Intermediary goods 67,3 82,9 59,6 56,8 Consumer goods 68,8 14,5 73,9 13,9 Capital goods 4,7 5,5 3,4 5,1 Intermediary goods 26,5 80,0 22,6 81,0 The foreign trade of the three autonomous communities not only show differences in terms of the volume of their operations and the evolution in the period considered, as indicated in the introduction to this document, but the above tables also show a different distribution of these operations by product groups according to their use. Special mention should be made of the different structure of its exports. It is important to stress the lower relative economic weights of the international flows of capital goods in the foreign trade of the three autonomous communities and therefore if we also consider only the elementary classes that we have selected. Table 3 shows the different indicators of the elementary classes selected in the IVU. Table 3. Characteristics elementary classes selected by flow and usage group. Simple average for Characteristics of the selected elementary classes No annual observations Intraclass coverage Variation coefficient Exports Imports Exports Imports Exports Imports Galicia Basque Country Murcia Region Consumer goods ,9 97,9 11,5 15,4 Capital goods ,8 94,7 17,8 23,0 Intermediary goods ,2 95,7 17,4 19,4 Consumer goods ,8 96,9 13,9 17,5 Capital goods ,5 94,1 17,5 22,1 Intermediary goods ,9 95,6 16,7 19,9 Consumer goods ,5 97,3 3,1 4,8 Capital goods ,6 93,4 20,2 20,6 Intermediary goods ,5 95,8 10,3 9,7 9

10 The number of observations of the selected elementary classes is very different depending on the type of good in question. There are less observations for capital goods which greatly hinders the selection of classes of these goods when only considering the size criterion. The intraclass coverage provides an idea of the trimming to which the selected elementary classes have to be submitted to estimate their unit value, with the values are over 90% in all the cases. Finally, the variation coefficient is an indicator of the dispersion of the prices of the observations that enter into calculating the unit values of each elementary class. The maximum values of the variation coefficients are over 20% in the classes corresponding to capital goods flow. In general, the elementary values corresponding to consumer goods trade have a very high number of observations, high intraclass coverage and a lower variation coefficient. These are therefore the IVUs that a priori produce greater confidence. The imports of capital goods represent the opposite case, with a lower number of annual observations and a high variation coefficient. These are the IVUs that may present greater problems of stability and coverage, but which correspond with flows of less economic importance. 2.5 Calculating the simple indexes of the elementary classes. The simple indexes are the lowest level components used to obtain indexes and where there is no weighting. They are elementary class indexes. Elementary class indexes are calculated by applying the standard Paasche and Laspeyres formulas, which enable the Fisher indexes to be obtained, which are the ones that are published. These formulas can be consulted in the methodologies available by any of the statistics entities of the three autonomous communities. 2.6 Designing the aggregation mechanism to construct composite indexes. The Statistical Office of the European Communities (EUROSTAT) in SEC 95 (10.63) indicates that: The most appropriate way to measure the year-on-year price variations is by means of a Fisher price index. The price variations for longer periods will be obtained by chaining the year-onyear price movements. Furthermore, the import and export price index manual prepared by the following entities: International Labour Office (ILO), International Monetary Fund (IMF), Organization for Economic Co-operation and Development (OECD), Statistical Office of the European Communities (EUROSTAT), UN Economic Commission for Europe (UNECE) and the World Bank, recommends the use of exact or superlative indexes as aggregation forms, specifically the Fisher, Walsh and 10

11 Törnqvist-Theil indexes. As far as the use of chained indexes are concerned, it recommends chaining if the prices and quantities of the adjoining periods are more similar than the prices and quantities of more distant periods. Taking the above recommendations into account, together with the high volatility of the value and of the traded products The use of Fisher indexes implies that the index aggregation formula is the geometric mean of the Paasche and Laspeyres indexes. Both types of indexes are therefore first calculated with the relevant aggregation formulas of the simple indexes and their weightings. The main advantage of the chained indexes is to keep an updated assessment structure, thus avoiding the problems of ageing and the replacement biases that a fixed base is likely to generate. On the other hand, this methodology has the drawback of the generalised loss of transversal additivity and in a lower time average. The drawbacks arising from non-updating of the base period emerge from the introduction or elimination of products, technical changes or of preferences, etc, which lead to elementary classes appearing or disappearing or which change their internal composition (composition effect) with the resulting unit value change without it being the result of a change in the prices of the individual products. It can also occur that the seasonal dynamics present in the base period, and which influences the calculation of the unit value in this period, is modified over time which would also deteriorate the comparability. The way of solving the problem arising from these factors consists in performing comparisons between periods that are as near as possible (for example, one period) by means of links. The index below between two periods 0 and t will be the product of the links of each of the intermediate periods (1,2,... t.1, t). This type of index lacks a base period in the strictest sense. It has a period in which it is arbitrarily 100. This period is known as the "benchmark". The application of the concept of the chained index to high frequency economic series (monthly or quarterly) raises two significant problems: 1. The ranges introduced by the seasonal components (approximately periodic) and irregular, which may distort and complicate, particularly the comparison between two adjacent period. 2. It is of interest that the high and low frequency estimates are quantitatively consistent, that is, that the low frequency data may be derived from the high ones. With respect to the first point, the base price and elementary classes may be seasonal and it was therefore considered to deseasonalise them by means of using an annual benchmark. With respect to the second point, the use of monthly (quarterly) chaining in monthly (quarterly) indexes, that is, the linking of indexes by comparing current prices with those of the previous month 11

12 (quarter) may lead to systematic or derived deviations away from its annual equivalent. This derivative is greater the more intense and stable the seasonal guideline is, or, if your prefer, the more different the annual subseries of the monthly (quarterly) index are with respect to the annual series obtained by their time aggregation. Taking the above into account, it was decided to use chaining with respect to the previous year (annual chaining). There are different annual chaining methods, by using the annual information (annual overlapping) to select classes and calculate the base prices or by using a sub-period of the previous year as can be the last month (monthly overlapping). The use of this second possibility is based on the rupture that occurs when the first month of a year is compared with respect to the last month of the previous year is less in this case. The use of the annual overlapping has the advantage of having the same structure as its annual equivalent, therefore the monthly links are temporarily consistent with the annual ones, fewer discontinuities occur in the monthly overlapping but the time consistency is lost and additional seasonal and irregular variation sources may be introduced. These considerations mean that the selected classes and the base prices are considered to take the structure of the immediately previous year as the benchmark and thus guarantee the time consistency. Therefore, the unit value indexes of Galicia, the Basque Country and the Murcia Region are calculated as chained Fisher indexes with annual overlapping. 2.7 Calculating the aggregate IVUs by usage groups. Each the elementary classes are selected that enter into the IVU calculation, the links of each elementary class are calculated and are aggregated to calculate the links per usage group to four digits, flow and origin. Using these links, the grouping process is repeated to obtain the following aggregates until the links for each flow are achieved. It should be considered that the information of all the classes, whether selected or non-selected, is used in the weightings used in the aggregation method. The chained indexes are then calculated by multiplying the links of all the intermediate period, so that if we begin the calculation in year 0, the index in year 1 coincides with its link, the index in year 2 is obtained by the product of the year 1 link and the relevant monthly link of year 2. For the remaining years, the chained annual index of the previous year is multiplied by the monthly link that always takes the previous year as the base. Finally, the indexes are passed to the year 2005=100 benchmark. 12

13 2.8 Processing the non-selected classes. Unlike what occurs in other price indexes of the economy (industrial, consumer prices or prices received by the farmers, for example), all the elementary classes that make up foreign trade are involved in calculating the aggregate IVUs. This implies that it is necessary to assign an IVU to those classes where there is not suitable information available in the customs records. In any event, a fundamental requirement of the system is that every elementary class has its IVU, either calculated using its own commercial operations or allocated based on other IVUs. The allocation procedure is as follows, both for Laspeyres and for Paasche indexes: Once the links are calculated according to the above section for the different aggregation levels of the usage groups where the starting points was the links of the selected elementary classes (with information), a descending allocation process in the aggregation level in the performed (from the highest degree of aggregation to the lesser degree), for example, if any flow x zone cross does not have information to calculate the link, the link of the relevant flow is allocated and so on successively, by using the allocated links where necessary in each step until the elementary class is reached. This allocation system guarantees that if the process of obtaining aggregate links is replicated using elementary classes with information and the allocated, the links remain unaltered. 2.9 Debugging. One of the main drawbacks of the IVUs is their high volatility, as they reproduce the irregularity of the customs statistics, which are their raw material, the frequent errors committed in the recording when they fill in the fields of weights and units in their customs returns also result in extreme unit values. Furthermore, the composition effect is another standard source of atypical values. Therefore, these atypical values need to be debugged to be eliminated their effect on the final indexes as far as possible. The debugging process that was performed was the following: given that a uniformity criterion is required for the elementary classes by using all the annual information, which sets as atypical values those records that make the variation coefficient of the class is superior to 35% and subsequently, the selected type of trimming is used with the annual information to carry out the monthly trimming, it may occur that an observation is atypical taking into account the annual information but not from the monthly point of view. Therefore, those records that are eliminated and which are not considered atypical when the monthly procedure was performed were excluded when calculating the unit values, provided that the intraclass coverage does not fall by 50%. After this primary debugging, the procedure consisted in obtaining for each aggregate (beginning by the greatest to the lowest degree of aggregation and restricting the process to the level of two 13

14 GU digits) a measure of the variability (typical deviation) of the links for the whole period and analyse and study the months where these links are outside the interval (1+2, 1-2 )), with being the typical deviation. The classes that are included when calculating the links that take values outside the defined interval are analysed each month. It is determined which of them are responsible for the data considered to be atypical and the extreme observations are eliminated until said link takes a value considered to be acceptable. 3. Disseminating the IVUs Once IVUs of each autonomous community to the maximum level of desegregation are calculated, it is decided which ones can be published. As a general rule, the indexes that are published are the only ones that really are reliable in terms of their representation and coverage. Obviously, the more they are desegregated, the greater the representation problems are of the unit value indexes and the greater their volatility, as there is a high irregular component. In the three autonomous communities, the IVUs are published by flow and by flow and usage group to one digit: intermediary, capital and consumer goods, also considering the origin/destination of the flows. In the case of Galicia and the Basque Country, the indexes are published for the four geographical zones used when defining the elementary classes: EMU, EU, OECD and the rest of the world. The smaller size of the Murcia Region has meant that it was decided not to be publish the OECD and the rest of the world indexes separately to avoid publishing indexes based on very few and therefore not reliable series. Only two geographical zones are therefore considered: EU and the rest of the world. Therefore, only the EU indexes are comparable by geographical origin/destination, with the aforementioned clarification that the EU-27 in the Basque Country and the Murcia Region and the EU-25 are considered in the Galician indexes. The indexes by usage group to two digits are published, by considering the consumer goods (nonfood and food consumer goods) and intermediary goods (intermediary goods of agriculture, livestock, forestry and fisheries, energy and industrial) The low number of month records of capital goods flows means that their IVUs are excessively volatile and not very relevant for the economic analysis, and they are therefore not published to two digits. The usage group indexes to two digits are not desegregated geographically. Table 4 provides the coverage of the IVUs of the three autonomous communities for the usage groups to two digits, defined as the percentage of the total value of the operations of the elementary classes selected out of the total value of the aggregate. 14

15 It has to be taken into account that the coverage is calculated excluding the goods of the CUCI that have been initially eliminated and in the case of the Murcia Region, always considering the imports of the CUCI 333 weighted by its corrector coefficient. Table 4. Final coverage of the IVUs calculated by usage group. Simple average for IVU Coverage by flow and usage groups Exports Imports Total 95,5 94,8 Consumer Goods Food 95,2 97,1 Non-Food 95,6 93,0 Galicia Capital Goods Total 89,5 54,5 Total 84,5 82,8 Intermediary Goods Agriculture 29,1 35,3 Energy 72,2 77,7 Industrial 85,7 86,4 Total 92,0 89,1 Consumer Goods Food 89,2 93,0 Basque Country Non-Food 82,5 87,1 Capital Goods Total 73,4 66,2 Intermediary Goods Total 91,6 88,5 Agriculture 14,9 46,9 Energy 81,8 93,1 Industrial 92,2 87,3 Total 91,6 78,8 Consumer Goods Food 98,7 96,6 Murcia Region Non-Food 57,6 61,7 Capital Goods Total 75,3 76,1 Intermediary Goods Total 84,1 85,1 Agriculture 52,9 54,3 Energy 93,2 92,7 Industrial 84,5 77,1 15

16 The information provided by the previous table allows to confirm how the coverage of some IVUs decrease as the level of desegregation increases, with the lower coverage being reached in agricultural intermediate goods. The IGE also publishes the IVU by branch of activity, without considering the geographical origin/destination. Indexes of 23 branches of activity are published for imported products, 18 export branches of activity and sections of the NACE-09. In the Basque Country, monthly data of the IVUs are published referring to the series at aggregate level of the total exports and imports. The rest of series are disseminated grouped by quarter, in the same way as all the foreign trade information published by EUSTAT. Nonetheless, the monthly indexes with which the quarterly indexes are built have been considered in this joint publication of the three autonomous communities. Due to the fact that the foreign trade data of a year are modified each month that information is received and are not final until ten months after the year end, the results will be provisional until the foreign trade data are final. 16