The Australian Greens' Public Property Developer: An Input–Output Analysis

: The preparation of input output tables aims to present a picture of the interrelationships and interconnections among sector units in the economy as a whole, so that the input output model is a complete and comprehensive analysis tool. For the purposes of planning and evaluating the overall development outcomes of both national and smaller scale (district / city level), the regional development planning approach model can use an input-output analysis model. Through the analysis of the location quention can be seen the diversity of the economic base of a region's society. Against the areas analyzed can be classified sectors that are able to compete in their own territory or that can compete with other regions. Based on the analysis of 40 economic sectors in Bandung, as many as 16 sectors able to compete with other regions, and the rest can only compete in the area of Bandung . Keywords : O utput I nput M odel, Location Quotient, I ndustry C lassification, O utput, L abor

Comprehensive economic loss assessment of disaster based on CGE model and IO model—A case study on Beijing “7.21 Rainstorm”

This study aims to look at the estimated structural changes in the input output table for DKI Jakarta Province in 2024. Estimates for changes in the structure are obtained by making projections of the input-output table for DKI Jakarta Province in 2024 using the Dynamic Input Output (DIO) model, namely by embedding the econometric model into the input output model, using the 2016 based year, 52 economic sectors, and 22 data series from 2000 to 2021.DIO is a hybrid model that places more emphasis on non-survey aspects that combines macro-econometric equations with identity equations in input-output analysis. This model has many dynamic equations consisting of 425 equation model. The parameters value of the equation are estimated using a combination of three estimation methods: (1) Ordinary Least Square, (2) First Order of Autoregressive, and (3) Second Order of Autoregressive. The general balance value in the DIO model is formulated using the Gauss-Seidel iteration "RAS" method.The results of the study show that in 2024 the corporate services sector, the chemical, pharmaceutical and traditional medicine industry sector, and the transportation equipment industry sector are the dominant sectors in shaping changes in the structure of intermediate demand. The Construction Sector, the Corporate Services sector, and the transportation equipment industry sector are the dominant sectors shaping changes in the structure of intermediate input. The construction sector, the real estate sector, and the wholesale and retail trade sector, not cars and motorcycles, are the dominant sectors in shaping changes in the structure of final demand. For the gross value added component, the Wholesale and Retail Trade sector, Not Cars and Motorcycles, the Private Information and Communication sector, and the Financial Intermediary Services sector other than the Central Bank are the largest sectors in the formation of structural changes.

The main problems of constructing multiregional input-output (IO) models used for the development of spatial and sectoral long-term national economy forecasts are caused by the absence of proper statistics. Therefore, it is necessary to make up the input-output tables (IOTs) based on a limited set of direct and indirect indicators that measure spatial patterns of production, consumption, capital formation, etc., sufficiently accurate for filling up multiregional IO models. The paper discusses Russian IOT spatial mapping problems and proposes an approach to partial automation of the procedures necessary for regional IOT construction (by federal districts). The regionalization was carried out using a static IO model with the bounding sum control. As a result, a set of consistent regional tables for 2015 was developed, with the eight IOT sum equalling Russia’s IOT. Based on the estimated regional IOTs, a static multiregional input-output model (OMIOM) across federal districts for 2015 was made up. The model allows us to proceed to the follow-up phase, i. e., developing a semi-dynamic model for long-term national economic projection computations

The mining industry (MI) has played a key role in ensuring a stable supply of minerals for industrial production and human survival. The Chinese government is implementing various policies to promote the MI and needs quantitative information on the economic role and effects of the MI. Thus, this article uses comprehensive and multi-period input-output (IO) analysis to investigate the roles of four mining sectors, including the entire mining sector in the Chinese national economy, from the period 2007–2017. To this end, three models are employed. First, the production-inducing effects, value-added creation effects, and wage-inducing effects of 1 dollar of production in the MI sector are analyzed using a demand-driven model. One dollar of production or investment in the sector causes 0.862–1.171 dollars of production, 0.271–0.333 dollar of value-added, and 0.106–0.125 dollar of wage, respectively. Second, by applying a supply-driven model, it is found that one dollar of supply shortage in the MI causes 4.383–5.949 dollars of production failure throughout the national economy. Third, by utilizing a price-side model, it is discovered that a 10% increase in the price of output of the MI raises the overall price level by 0.108%–0.171%. The results of this article were critical to enlighten policy-makers to forward ever-improvement on the MI and combine the MI within national economic system reform and planning, by offering a clear vision of how MI will affect the various sectors and the economic system as a whole.

Applying physical input–output analysis to estimate land appropriation (ecological footprints) of international trade activities

The paper argues that input–output analysis existed long before it received its name and Wassily Leontief made it popular as a tool of empirical analysis and a foundation of economic policy. It grew out of an attempt to ascertain the capacity of an economic system to reproduce itself and generate a surplus that can be used for various purposes. Primitive pronouncements are encountered in early civilizations, for example Mesopotamia, in terms of the ratio of the amount of grain produced and the amount of it used up, directly and indirectly. These ideas reappeared in a more sophisticated form at the time of the inception of systematic economic analysis in the 17th and 18th centuries in Europe and found a two-sector expression in François Quesnay's Tableau économique. The material input–output structure was then considered the core of the economic system that contained one of the keys to basically all other important economic phenomena and magnitudes. The way in which the potentialities embodied in the input–output structure, conceived as a system of production, have, or have not, been exploited over time define both the problems and perspectives of contemporary input–output analysis. Three aspects will be scrutinized more closely: the problem of value added, the treatment of fixed capital and the problem of technical change. Happily enough, while the problems are huge, the prospects are encouraging. There is no fear that input–output analysts will soon have to look for new fields of research because the old ones have been exhausted.

Potential economic and energy impacts of substituting adaptive reuse for new building construction: A case study of Ontario

The success of the sliding mode control (SMC) is due to the simplicity of its implementation and its robustness against external disturbances via state space and input output model. In spite of this characteristic, the sliding mode control (SMC) suffers from a main drawback known as the ‘chattering phenomenon’. In order to overcome this problem, a new discrete second order sliding mode control via input output model is proposed in this paper. A stability analysis of the proposed control was then studied. To illustrate the effectiveness of the proposed discrete second order sliding mode control law, a classical discrete sliding mode control and discrete second order sliding mode control were applied to a real discrete second order system via input output model. The experimental results of the proposed discrete sliding mode control law show good performances in terms of the rejection of the external disturbances and the reduction of the chattering phenomenon.

The operation of Industrial Ecosystem (IES) should benefit both profitable and environmental objectives. There should be some quantitative relationships between the two objectives among different sectors of IES. For specifying these relationships, Leontief Input-Output(I-O) analysis is an effective economic method. The framework of IES's 1-0 analysis is developed in this paper that denotes both the value of production and the consumption of environmental resources. Based on the analysis, a multiobjective optimization model is proposed which gives attention to the economy and environment at the same time and the feasible solution procedure is provided. The case study of a Combined Heat and Power(CHP) eco-industrial park further confirms that the model will play an important role in the decision-making and evaluating of IES.

The main objective of this article is to assess the carbon footprint of Brazilian families based on the Household Expenditure Survey (POF), 2008-2009, from the Brazilian Institute of Geography and Statistics (IBGE). The methodology used to quantify the Brazilian households’ carbon footprint has comprised three data sources: i) Household expenditure Survey, 2008-2009; ii) Leontief matrix of Brazilian accounts, year 2010; and iii) 2009 World Input-Output Database (WIOD) environmental inventory. Initially, an input-output (IO) model was created. Next, the results from the IO model were combined with the information of the POF. The poorest families, with a monthly income of up to $ 415.00, emit less than 1.5 metric tons per year, in contrast, the wealthiest families, with a monthly income above $ 5,187.50, release around 18.5 tons, almost 12 times more. It was found that an increase in income, results in an increase in CO2eq emissions. Thus, while the poorest families, which represent more than 20% of the total Brazilian families, cause 7% of the total emissions, the wealthiest families cause 16% of the total emissions although they represent only 4% of the total families. It was observed that the food category loses importance as income increases, while the opposite occurs in the services category. For the poorest families, there is great importance in the housing category, mostly caused by the consumption of electricity and LPG. Therefore, important measures for economic growth supported by actions become particularly relevant.

Wassily Leontief, a winner of the Nobel Prize in Economic Sciences, has been called “the father of input–output analysis.” In the 1930s, striving to depict the interrelationships among the various segments of the U.S. economy, he and his associates constructed and analyzed national input–output tables for 1919 and 1929. Leontief’s classic book The Structure of American Economy, 1919–1929 was published in 1941. Twelve years later, Leontief and others authored Studies in the Structure of the American Economy. Of note was a chapter by Walter Isard entitled “Some Empirical Results and Problems of Regional Input–Output Analysis.” Between 1966 and 1977, a team of researchers led by Philip Bourque of the University of Washington and Eldon Weeks of Washington State University produced a unique series of survey-based regional input–output tables for the state. Focusing on the 1972 Washington input–output study for illustrative purposes, this chapter discusses the structure of regional input–output tables, the estimation of the input–output transactions, and the formulation of regional input–output models. The chapter concludes with an impact analysis—calculating the economic impact of professional baseball—the most common use of regional input–output models.

this paper we examine the necessary and sufficient conditions for constancy of the value input-output coefficients. In his well-known article Klein1 studied the same problem. Nevertheless, there is a striking difference between his approach and ours. Klein assumes that all inputand output prices are known, either as fixed or as given functions of input demand. He subsequently shows that every production function which is zero-homogeneous in all inputs and outputs yields constant value shares of inputs in the outputs, assuming optimal allocation of both. This is true whenever one specific vector of inputand output prices is considered. We, however, derive conditions of invariance of value shares for any exogenously determined variable vector of input prices and output prices. This additional requirement restricts the class of admissible production functions. First, we consider the case of a single homogeneous output per sector. We show that constancy of value input-output coefficients holds good if and only if the production function is of the linear-homogeneous CobbDouglas type. The sufficient condition is well-known, but contrarily to common belief the necessity of the condition has as yet not been established.

PurposeThe purpose of this study is to examine the total economic impact of tourism at the regional level in Central Finland. This paper aims to clarify the extent to which tourism contributes to regional output, employment, income and taxes in tourism-related sectors.Design/methodology/approachThis study is based on a regional input–output analysis. The author calculates the effects of tourism on regional output, demand, wages, employment and national and regional taxes in Central Finland.FindingsThe author’s regional input–output analysis reveals that tourism has a substantial impact on production in Central Finland (including the direct and indirect effects of consumption by tourists in different sectors). Moreover, the effects of tourism expenditures on employment and residents’ incomes in tourism-related sectors in Central Finland are quite significant.Research limitations/implicationsMany limitations of this study stem from the assumptions of the input–output model. Other limitations relate to the analysis of the impacts of tourism on household taxes, savings, consumption and net income. Our study uses average figures, which may overstate the effect of tourist expenditures on taxes because tourism jobs are often low paying.Practical implicationsThe study yields results that can be used to frame regional policy. The results may be useful for policymakers in planning for tourist attractions. Furthermore, local authorities may use the results to guide decisions regarding infrastructure investments or improvements to the operating environment of tourism industries.Originality/valueMany studies analyse the economic impact of events at the regional level using input–output analysis. National-level tourism impact studies using the input–output technique have also been conducted. Studies focussed on the economic impact of tourism at the regional level typically examine the macroeconomic (income, output and employment) effects of tourism. Consequently, these studies have focussed on estimating output, employment and income multipliers (Mazumder et al., 2012). The author’s contribution is a regional input–output analysis of direct and indirect impacts of tourism expenditures on production, demand, wages, income and employment in the whole economy at the regional level (in Central Finland). The author also analyses the impacts of tourism on national and regional taxes. The results of this study could be used by planners and policymakers involved in regional planning and development.

In economic literature, some information deficiencies and computational complexities have traditionally been solved through the aggregation of data. In input–output (IO) modelling, researchers have been interested in aggregation since the 1950s. Extending the conventional IO aggregation approach to the social accounting matrix (SAM) framework may help to identify the effects caused by the problems of information that usually appear in the linear SAM models. This article applies the theory of IO aggregation to the SAM model and presents a comparison of the IO aggregation bias and the SAM aggregation bias.