Scope and Frequency of Data Collection

The collection of energy data can be a complex and costly process, which depends very much on a country’s needs and circumstances, including the legal framework and institutional arrangements. It is important that countries undertake it on the basis of well-thought-out strategic decisions regarding the scope and coverage of data collection, the organization of the data collection process, the selection of appropriate data sources, and the use of reliable data collection methods [IRES, Ch. VII, para. 7.15, PDF p. 102, 2018].

The six scope dimensions

The scope and coverage of the collection of energy statistics are defined according to six dimensions [IRES, Ch. VII, para. 7.16(a)–(f), PDF pp. 102–103, 2018]:

(a) Conceptual design, which includes the objective and thematic coverage;

(b) Target population (see Energy Data Reporter Groups for the three reporter groups and the informal sector);

(c) Geographical coverage;

(d) Reference period of data collection;

(e) Frequency with which data are to be collected;

(f) Point in time of collection.

Conceptual design

The overall objective of the data collection should be clearly defined. The thematic coverage must take into account the type of statistics to be collected — for example, the flows and stocks of energy products and the units of measurement. International standards should be applied in the conceptual design process [IRES, Ch. VII, para. 7.17, PDF p. 103, 2018].

Geographical coverage

The geographical coverage identifies the area for which statistics are collected. For policy purposes it is generally fundamental to collect statistics at the national level; however, for analytical and policymaking purposes countries often compile energy statistics at a subnational level, implying more detailed geographical coverage. Subnational-level collection is often essential for planning future infrastructure, since it allows the different locations of production and consumption to be taken into account. On the consumption side, regional disaggregation is necessary, since energy use can vary significantly with climate, local behaviour, customs, economic activities, incomes and availability of energy products. Collecting such detailed information often implies higher data collection cost and requires additional methodological effort to avoid omissions or double-counting when collating regional data up to the national level [IRES, Ch. VII, para. 7.27, PDF p. 104, 2018].

Reference period vs. frequency

The reference period of energy data collected refers to the time period the data relate to. For example, oil production data may have a reference period of one month, household energy-use data a reference period of one quarter, and energy-behaviour data (e.g., data on measures taken to reduce energy use) a reference period of one year [IRES, Ch. VII, para. 7.28, PDF pp. 104–105, 2018].

The frequency of collection is distinct from the reference period: it is the result of a balance between users’ needs, the priority given to timeliness of particular data items, the level of detail required, data availability and available resources. Comprehensive annual data should be the initial objective when setting up an energy statistics programme, but higher-frequency (infra-annual) collections are critically important for timely assessment of a fast-changing energy situation [IRES, Ch. VII, para. 7.29, PDF p. 105, 2018].

Recommendation (7.29): countries are encouraged to conduct infra-annual collections on a regular basis within identified priority areas of energy statistics [IRES, Ch. VII, para. 7.29, PDF p. 105, 2018] — recommendations tracker row VII/7.29.

The three frequency tiers

• Annual data collections — collect energy data relating to the basic and most appropriate information needs; in general they cover production, supply and consumption at a detailed level of disaggregation for any energy products that make up a significant share of total energy supply [IRES, Ch. VII, para. 7.29, PDF p. 105, 2018].
• Infra-annual data collections (quarterly, monthly, etc.) — conducted when the need for frequent data is of high priority (e.g., monthly oil production and trade), but usually more restricted in level of detail (e.g., total consumption rather than consumption by consumer group) than annual collections, since higher frequency increases cost and reporting burden [IRES, Ch. VII, para. 7.29, PDF p. 105, 2018].
• Infrequent data collections (less frequent than annual) — generally conducted for specialized topics (e.g., deployment of fuel cells), to fill gaps in annual/infra-annual data (e.g., sub-sector breakdowns of minor products), to provide baseline information, or where data collection is particularly expensive (e.g., large consumer surveys or censuses) [IRES, Ch. VII, para. 7.29, PDF p. 105, 2018].

Point in time of collection

The point in time when collection is carried out should also be carefully considered, since it may affect the response rate — for example, avoiding sending questionnaires during holiday periods, or overlap with other surveys and administrative data collections such as tax filing [IRES, Ch. VII, para. 7.30, PDF p. 105, 2018].

Organization of data collection

Proper organization of the data collection process is fundamental for official energy statistics. The first important step is to identify the production, supply, transformation and consumption flows for each fuel, in order to clarify the processes, procedures and statistical units involved. It is then necessary to outline potential data sources for each flow, to determine whether accurate information can be obtained from them on a regular basis, making use of information they already hold for their own management purposes. From these descriptions, the kind of energy data obtainable from different sources can be determined and the collection process planned accordingly [IRES, Ch. VII, para. 7.31, PDF p. 105, 2018].

In general, data collection relies on the country’s legal framework and institutional arrangements (see Legal Framework and Institutional Arrangements), as well as on agreed collection methods — statistical business registers, administrative data, and census or sample surveys — to obtain comprehensive data. The most appropriate collection method should be selected taking into account the nature and specific characteristics of the given energy activity, data availability, and budget constraints [IRES, Ch. VII, para. 7.32, PDF p. 105, 2018].

Integrating energy collection with the wider statistical system

Recommendation (7.33): the collection of energy data should be seen as an integral part of the data collection activities of the national statistical system, to ensure the best possible data comparability and cost efficiency. Close collaboration between energy statisticians and compilers of industrial statistics, as well as statisticians responsible for household, labour force and financial surveys, is of paramount importance and should be fully encouraged and systematically promoted. A collaborative relationship creates better understanding of the information, provides an opportunity to incorporate energy items into non-energy-specific questionnaires (taking into account the priorities and specific needs of the energy industries), and facilitates cost-benefit analysis [IRES, Ch. VII, para. 7.33, PDF pp. 105–106, 2018] — recommendations tracker row VII/7.33.

Establishing or improving the regular programme of energy data collection should be part of a long-term strategic plan in the area of official statistics. Such a programme should be properly designed and executed to obtain the widest possible coverage and ensure the collection of accurate, detailed and timely energy statistics [IRES, Ch. VII, para. 7.34, PDF p. 106, 2018].

An integrated approach is especially important for collecting data on energy consumption, since many different data sources can be used. Data can be obtained directly or indirectly from appropriate economic units (enterprises or establishments and households) by censuses, surveys and/or administrative records. Because the number of energy consumers is larger than the number of energy suppliers, it may be necessary to exploit existing business surveys to identify establishments required to answer specific questions on energy consumption. Consistency of energy consumption data collected from various sources should be ensured [IRES, Ch. VII, para. 7.35, PDF p. 106, 2018].