The purpose of the SAM is to improve quality of database for modelling (multiplier analysis, price analysis, policy analysis and Computable General Equilibrium (CGE).

Yearly citation counts for the publication titled "Matrix scaling of subjective probabilities of economic forecasts".

The aim of this paper is to show that random matrix theory (RMT) can be a useful addition to the economist’s tool-kit in the analysis of macro-economic time series data. A great deal of applied economic work relies upon empirical estimates of the correlation matrix. However due to the finite size of both the number of variables and the number of observations, a reliable determination of the correlation matrix may prove to be problematic. The structure of the correlation matrix may be dominated by noise rather than by true information. Random matrix theory was developed in physics to overcome this problem, and to enable true information in a matrix to be distinguished from noise. There is now a large literature in which it is applied successfully to financial markets and in particular to portfolio selection. The author illustrates the application of the technique to macro-economic time-series data. Specifically, the evolution of the convergence of the business cycle between the capitalist economies from the late 19th century to 2006. The results are not in sharp contrast with those in the literature obtained using approaches with which economists are more familiar. However, there are differences, which RMT enables us to clarify.

This dataset consists of general economic indicators for all countries in the world as collated in the Department of State's Economic Engagement Matrix.

The Social Accounting Matrix (SAM) for Germany includes data on 163 production sectors, factors of production, indirect business taxes, households, corporations, government, gross fixed capital formation, changes in inventories, and the external accounts with the rest of the world. The SAM allows for economic analysis, policy evaluation, and economic modelling. The SAM is compiled by extending the EXIOBASE Input-Output accounts with data from Federal Statistical Office of Germany (DESTATIS) and using balancing items to ensure that the Total Income and Total Expenditure of the main transactors are in balance.

The binary matrix used to merge 166 sectors into 55 sectors.

Coefficients of theoretically most important comparisons based on Model 2.

The Calgary Equity Index is a decision-making tool designed to measure equity in Calgary, based on a social determinant of health (SDOH) framework. The SDOH are the range of interacting social and economic conditions that influence people’s health and well-being. This index provides an equity lens to examine the ways in which social and economic conditions are experienced and distributed among populations. It will help the City examine where inequities exist in different areas. Information is available for 113 Community Service Areas (CSAs) across Calgary. The CSAs were created by combining two adjacent Census Tracts to reach a population of around 10,000. The CSAs are numbered from 1 to 113, and are displayed on the map.

Paraguay is a small open economy, heavily dependent on agricultural commodities and on regional conditions. This has left the economy vulnerable to events over which it has little control, including international commodity prices and political and economic events in its neighbours. The most important economic problem for Paraguay is lack of growth. For example between 1990 and 1995, per capita Chilean GDP grew in average 5,3% while in Paraguay the average growth rate was only 0,5%. A study like the Social Accounting Matrix (SAM) is of particular importance for a country where the recovery of political rights and the consolidation of democratic institutions since 1989 have not been accompanied by economic growth and poverty alleviation.

Provides details of the changes to UK Economic Accounts tables.

This table presents the from-whom-to-whom matrices of several important financial instruments. The matrices provide information on the debtor/creditor relationships between sectors. The matrices provide a three dimensional overview on financial transactions, price changes and revaluations, other volume changes and balance sheets and the sectors and financial instruments involved. The sector on the assets side is the creditor, the sector on the liabilities side the debtor. The sectors non-financial corporations, financial corporations, general government, households including non-profit institutions serving households (NPISH) and the rest of the world are shown in this table. The sectors financial corporations and general government are broken down into subsectors.

Data available from: Annual figures from 1999. Quarterly figures from first quarter 1999.

Status of the figures: The figures from 1999 up to and including 2020 are final. Data of 2021, 2022 and 2023 are provisional. Since this table has been discontinued, provisional data will not become final.

Changes as of June 24th 2024: None. This table has been discontinued. Statistics Netherlands has carried out a revision of the national accounts. The Dutch national accounts are recently revised. New statistical sources, methods and concepts are implemented in the national accounts, in order to align the picture of the Dutch economy with all underlying source data and international guidelines for the compilation of the national accounts. This table contains revised data. For further information see section 3.

When will new figures be published? Not applicable anymore.

Descriptive Statistics of the Return Rate of the Stock (Chartists )

Matrix IT - 現在の値は、過去のデータ、予測、統計、チャートや経済カレンダー - Jul 2025.Data for Matrix IT including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Flows of intersectoral goods and services in the economy, depending on the production levels of each economic sector. Base year 2013.

This study shows the construction of labor quality and labor input indices for the U.S. Private Economy, 1977-2000.

The 2006 Nigeria SAM is a comprehensive, economy-wide data framework, representing the structure of the Nigerian economy; the links among production activities, income distribution, consumption of goods/services, savings and investment, and foreign trade of the economic agents in year 2006. This 2006 Nigeria SAM is a 61 sector square matrix table with the column and row beginning with activities account, followed by commodities account and thereafter accounts for the economic agent in the Nigerian economy. Each cell in the matrix represents the flow of economic activities in monetary terms from a column account (expenditure or outflow) to a row account (income or inflow). Also, each activity and commodity account begins with letter 'a ' and ' c' respectively. This 2006 SAM was built for the dynamic CGE (DCGE) model that examined the growth and investment options available in the agricultural sector for reducing poverty in Nigeria, and was an integral part of the Agricultural Policy Support Facilites activities for strengthening evidence-based policymaking in Nigeria. Given the agricultural policy analysis focus of the SAM and DCGE model, 34 sector of the SAM are under agriculture and included key cash and food crops as well as livestock sub-sector. The 2006 Nigeria SAM also includes 12 manufacturing (such as beef, textiles, and wood products); 2 mining sector (including crude petroleum and natural gas); and 13 service sectors (such as building and construction, electricity and water, and hotels and restaurants). While the total number of sector for the SAM is 61, the commodities account is 62 as fertilizer was treated as commodity rather than activity. The 2006 SAM data files comprise two worksheets; one for the SAM data and the other containing legend to the SAM data. The value for each of the cell entries is reported in naira million (2006 prices). The data used for building this SAM were obtained from various sources including but not limited to publications of the National Bureau of Statistics (NBS), the Central Bank of Nigeria (CBN), and the Federal Ministry of Agriculture and Water Resources (FMAWR). Data from an earlier SAM of the country developed by United Nations Development Programme (UNDP), 1995 are also used, and was balanced using the cross entropy estimation method. The SAM was built following the International Food Policy Research Institute (IFPRI) standard format (Lofgren et al. 2001).

The 2015 Water-Focused Social Accounting Matrix (WF-SAM) for Jordan represents a significant enhancement over the existing SAM introduced by (Raouf et al., 2021). This enhancement lies in its comprehensive integration of the water sector at the micro-account level. Constructed with thorough attention to detail, the 2015 WF-SAM for Jordan draws upon a triad of distinct data sources. Firstly, it incorporates micro-account data derived from the foundational SAM developed by Raouf et al. in 2021, acknowledged as the most contemporary SAM for Jordan, benefiting from current national and international data sources. Secondly, a contribution stems from the 2017 reports of the General Budget Department (GBD), furnishing actual financial allocations of Jordanian water utilities (General Budget Department, 2017a, 2017f, 2017e, 2017d, 2017c, 2017b). Adapting these allocations into novel account totals and deficits within the WF-SAM framework amplifies its comprehensiveness. The third data source comes from (MWI, 2015)and (Salamah, 2021), disclosing the nuanced cash flow interplay between the water-centric accounts and the entire economy, for instance, the municipal water sector allocates 12% of its total expenditures to the electricity commodity, establishing a symbiotic relationship. This calibrated interdependence of sectors elevates the precision and disaggregation of the 2015 WF-SAM for Jordan.

Out of the convention in this documentation, the 2015 JO SAM by (Raouf et al., 2021) is used in constructing proto-SAM and is identified as "Base-SAM." To enhance and modernize the representation of the water sector within the Base-SAM, budgetary components sourced from audited national public budget documents were carefully correlated with corresponding accounts within the SAM structure, adhering to the established ISIC standard economic classifications. This alignment resulted in the creation of a preliminary SAM, although it entailed further refinement to achieve equilibrium. Employing the cross-entropy SAM estimation algorithm, as set forth by (Robinson et al., 1998)), facilitated the fulfilment of the ultimate balanced state. The resultant Water-Focused Social Accounting Matrix (WF-SAM) is enclosed within the attached Excel workbook.

The WF-SAM for Jordan, includes 155 accounts, 57 activities, 63 commodities, one transaction cost account, 13-factor accounts, ten household accounts plus one enterprise account, and seven government-related accounts: one for the government itself and six for direct and indirect taxes and subsidies, with one saving and investment account and one currency exchange account, the rest of the world is represented in one account,” RoW.” The water sector is represented in three commodity accounts, two activity accounts, and one water subsidies account.

This dataset (WF-SAM) enables future research on an array of scenarios and shocks to assess policymakers in the ex-ante assessment of policy options and market conditions. The findings of this study provide valuable insights into the interplay between the water sector and the Jordanian economy and can inform policy decisions related to water resource management and development.

Electric Energy Matrix: Individually Simulated: Southeast/Central West: Nuclear: 2022 data was reported at 1,990.000 MW in Dec 2023. This stayed constant from the previous number of 1,990.000 MW for Nov 2023. Electric Energy Matrix: Individually Simulated: Southeast/Central West: Nuclear: 2022 data is updated monthly, averaging 1,990.000 MW from May 2020 (Median) to Dec 2023, with 44 observations. The data reached an all-time high of 1,990.000 MW in Dec 2023 and a record low of 1,990.000 MW in Dec 2023. Electric Energy Matrix: Individually Simulated: Southeast/Central West: Nuclear: 2022 data remains active status in CEIC and is reported by National Electric System Operator. The data is categorized under Brazil Premium Database’s Energy Sector – Table BR.RBA011: Electrical Energy: Matrix.

Matrix IT 負債 - 現在の値は、過去のデータ、予測、統計、チャートや経済カレンダー - Jul 2025.Data for Matrix IT | 負債 including historical, tables and charts were last updated by Trading Economics this last July in 2025.