جستجوی مقالات مرتبط با کلیدواژه "input-output tables" در نشریات گروه "اقتصاد"

In this article, we introduce three types of input-output tables and modify a central bank table from 2016 to illustrate the transition from the first generation of statistical bases to the second generation, which meets the new international trade theory’s database requirements. The third type of table is critical and is considered the starting point for such changes. Given the lack of such a table in Iran, this article offers three challenges, followed by three critical questions: first, what can be done if official compilers do not attempt to develop such an input-output table soon? Second, which of the two types of tables has more statistical errors than the modified tables? Third, which of the two input-output tables is better for measuring value-added content in gross exports? The central bank's most recent SUT and intermediate import utilization data from 2016 are utilized to investigate three questions. The data show that: calculating the third type of table can solve this lack of statistics. In comparison to the second table, the third table exhibits fewer statistical mistakes. Finally, the third type of table outperforms the second in terms of quantifying value-added content in gross exports.

The elasticity of aggregate output with respect to aggregate capital and labor is computed using the cost structure of the production network of Iran's economy without using the aggregate production function. Estimations are made using Input-Output tables and according to a method developed by Baqaee and Farhi (2019, 2020). Elasticities are computed for the years 1986, 1999, 2001, 2004, 2010, 2011, and 2016. Various assumptions regarding capital costs of production sectors lead to lower and upper bounds for capital elasticity. The bounds for capital elasticity of Iran's economy were 0.15-0.35 in 1986, up to 0.22-0.55 in 1999, 2001, and 2004, even higher to 0.28-0.59 in 2010 and 2011, and down to 0.21-0.42 in 2016. Labor elasticities are one minus capital elasticities. Notably, the bounds for capital elasticity steadily increased from 1986 until the early 2010s, followed by a decline. For the non-oil sectors, the bounds for capital elasticity and the spread between those bounds are smaller than the entire economy. The bounds for the non-oil economy are 0.15-0.32 in 1986, up to 0.17-0.47 from 1999 to 2011, and 0.17-0.35 in 2016. The results show that ignoring labor compensation from unincorporated sectors of the economy increases the capital elasticity by at least 0.17 points. Our estimations can be used for robustness check and sensitivity analysis wherever capital and labor elasticities are needed, such as growth accounting.

Understanding the water content of export and import products in international trade has an effective role in the optimal management of water in Iran as a country with water stress. The main purpose of this study is to identify the balance of water content of products in Iran's foreign trade. For this purpose, using the input-output tables - 2016 and considering the interrelationships and dependencies between major economic sectors including agriculture, mines, manufacturing, electricity and gas production, treatment, supply and wastewater, buildings, services and others, the Water footprint index, net import of virtual water and some indicators related to water consumption have been calculated. The results show that in 2016, Iran was a net importer of virtual water. Although the agricultural sector has the highest national water footprint ( 89%), according to the water consumption multiplier index, increasing water consumption in this sector has very little effect on increasing water consumption in other sectors. After the agricultural sector, the manufacturing sector has the highest intensity of indirect water consumption (3.5 cubic meters / million Rials), and the increase in water consumption in this sector has the greatest impact on increasing water consumption in the economy. So that the increase of one unit of water consumption in this sector increases the water consumption of the agricultural sector by 7 times and the water consumption of the whole country by 9 times. After the agricultural sector, the highest amount of virtual water content (direct and indirect water consumption) was allocated to the treatment, supply and wastewater sector(5.8 cubic meters / million Rials). The services and other sectors, which has been the largest net exporter of virtual water ( 217 million cubic meters), have the largest water footprint after agriculture.

The aim of developing labour accounts is to provide a complete and coherent picture of the labour market and organize the employment statistics in each country. The most important variables and components of labour accounts are employment, working hours and income from employment. Employment account is one of the most important components of labour accounts. In this paper, based on the recommendations of the World Labour Organization and the experience of countries such as the Netherlands, Australia, Italy, Denmark and Switzerland, for the first time, the employment account in Iran is provided. The main objective is to derive a comprehensive estimate of total employment in the country. To achieve this goal, employment statistics from regular household surveys are linked to the employment data from establishment surveys. The resulting data are reconciled based on a bottom-up approach until a coherent picture of the size and characteristics of employment emerge. The statistics obtained from labour accounts should also provide improved and more consistent data for macro-economic analysis of the labour market, in particular, the analysis of productivity and the relationship between employment and economic growth. Because in 2011, a number of statistical sources, including labour force survey, population and housing census and numerous establishment surveys have been implemented with the aim of achieving input-output tables, that year is considered as the base year for calculating labour accounts in Iran.

Input-Output Table (IOT) analysis is important especially concerning trade, environments, productivity for planning and policy making. Quality of the analyses depends on the estimation of Symmetric Input-Output Tables (SIOT) and also the use of the types of technology assumption (Product Technology versus Activity Technology). The choice of the type of technology concerning SIOT estimation has been left to the member countries by the UN Manual. Choosing technology assumption in Iran has been based on expert judgments, institutional data requirement and avoiding negative elements. The question which arises here is that, would it be possible to choose the appropriate type of technology for estimation of SIOT in Iran? The main aim of this paper is to suggest an econometric test of hypothesis method concerning the choosing of technology type. For this reason, we suggest a Fisher type (F) test in which the Product Technology or the Activity technology will be chosen. If the Product Technology is dominant, the SIOT will be estimated based on the Product Technology. Otherwise, the Activity Technology may be applied. The results of the tests concerning 2011 SIOT have shown that Product Technology Hypotheses is more appropriate for some sectors, whereas Activity Technology Hypotheses for other sectors are not valid.