Input-output based analysis of intersectoral linkages for economic diversification in Oman

Objective - This study aims to identify Malaysia's machinery and equipment (M&E) industry local supply chain, classify its key industries, and estimate the economic effects of changes in final demand within the industry. Methodology - This study employs a quantitative input–output analysis to assess both the strength and distance of linkages between the machinery and equipment (M&E) industry and other sectors in Malaysia. Industries are classified according to normalized backward and forward linkages, and multiplier analyses are used to evaluate the economic effects of changes in final demand for the M&E industry. Findings - Results indicate that the M&E industry in Malaysia is primarily a backward linkage-oriented sector, stimulating growth in upstream industries through its demand for inputs. The analysis further identifies five key industries, including M&E, within its supply chain. Scenario-based multiplier simulations reveal negative economic impacts from reduced export demand for the M&E industry, but positive impacts from investment in the M&E sector and its related industries. The results also indicate the M&E industry's reliance on external demand. Novelty - This study demonstrates the value of systems thinking by integrating scenario analysis with supply-chain linkages, industrial classifications, and multiplier effects to produce a more comprehensive economic assessment. The approach highlights potential policy insights for improving public resource allocation in Malaysia. Type of Paper - Empirical Keywords: Machinery and Equipment Industry; Input-Output Analysis; Supply Chain JEL Classification: C67, D57, L60 URI: http://gatrenterprise.com/GATRJournals/JBER/vol10.2_5.html DOI: https://doi.org/10.35609/jber.2025.10.2(5)

The paper identifies the sources of changes in energy consumption and GHG emissions in India using Input-Output Structural Decomposition Analysis (SDA) during the period 1993-1994 to 2003-2004. The result shows that changes in final demand structure and volume of changes in final demand are the key factors responsible for changes in energy requirements and GHG emissions respectively. It further develops few simulation exercises to estimate the energy requirements and GHG emissions during the Twelfth Plan. The implications of these scenarios provide a better insight for the derivation of future policy towards reduction in energy consumption resulting in climate change impact.

Conventional studies on the impacts of economic shocks using global input-output tables (sensitivity analyses) assume stable production structures and thus, only reveal the marginal impacts of changes in final demand. However, when economic shocks occur, whether at home or abroad, economic agents are expected to react to reduce the negative impact or amplify the positive effects. The ability of a country to contain economic losses can be defined as the resilience to economic shocks. Using the OECD's annual Inter-Country Input-Output (ICIO) tables, 1995 to 2011, this paper investigates the relationship between changes in final demand and production structures for 61 economies. Our findings are summarised as follows. Production and final demand structures tend to change to reduce the negative feedbacks from final demand shocks. During economic downturns, structures tend to change so that the dependence on domestic services increases, while the dependence on domestic demand for goods, and the dependence on foreign demand for domestic goods and services, both decrease. Therefore, the domestic service sector seems to play a key role in temporarily containing the negative feedback. Countries that are able to prop up their economy by domestic service sectors instead of domestic goods and foreign sectors are more resilient to negative economic shocks.

With the increasing frequency of extreme weather events, global concerns regarding climate change have intensified, with carbon dioxide widely recognized as the primary driver of global warming and climate disruption. It is necessary to investigate how to develop industries to meet the constant GDP growth and minimum carbon emissions. This study investigates the optimization of industrial structure under China’s ‘Dual Carbon’ Goal in Guangdong Province from 2012 to 2017, employing a multi-objective programming model. Using the input–output table, carbon emissions across 42 industries are calculated based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission factor method. According to Hirschman’s theory of industrial interdependence, the economic and carbon emission linkage coefficients between these industries are obtained by calculating the Ghosh inverse matrix and the Leontief inverse matrix to analyze the economic forward and backward linkage of the industries, as well as the carbon emission forward and backward linkage. The impact of industry input and output on the urban economy and the resulting carbon emission problems are discussed, and industries are divided into encouraged and restricted industries. Using a multi-objective programming model, the expected final demand, changes in final demand, and expected carbon emissions of these industries under the ‘Dual Carbon’ Goal, with the target of maintaining the same economic growth rate and promoting carbon reduction, are analyzed. The results show that most industries in Guangdong Province need to reduce final demand, including the highest carbon-emitting industries and industries that are relatively restricted by scale in development. The policy implications of optimizing the industrial structure to reduce carbon emissions are provided.

Over the last decades, Morocco has been facing increasingly severe water scarcity. To quantify water use in Morocco, we refer to the water footprint (WF) concept, including both direct and indirect water use. WF considered covers internal WF and exported virtual water (VW). We used the input-output structural decomposition analysis (SDA) to quantitatively analyze the drivers of changes in Morocco’s sectoral WF from 1995 to 2015. The considered mechanisms governing WF changes are the technological, economic system efficiency, and structural effects. The WF growth experienced in Morocco primarily resulted from final demand changes. The technological effect acted as an additional increase factor. Nevertheless, the economic system efficiency effect contributed to the water conservation process. Unfortunately, it was not sufficient to reverse the expansion of Morocco’s WF resulted from other driving factors. Agriculture is the dominant economic sector in WF changes, regardless of any driving factor and any period considered. The study provides insight into Morocco’s water policy limits and helps develop policies towards sustainable water resources planning and management. That is by suggesting that final demand structure adjustment and technological innovation in the agricultural sector should be at the center of Morocco’s strategies in addressing water scarcity.

Analysis of changing hidden energy flow in Vietnam

Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD

List of tables List of figures Editors' preface Preface Introduction: the puzzle of the 1930s 1. Long-term economic growth and the problem of recovery in the United States, 1929-39 2. The transformation of American industry in the interwar period 3. A reassessment of investment failure in the interwar economy 4. Technical change during the interwar years 5. The effective demand problem of the interwar period I: cyclical and structural unemployment 6. The effective demand problem of the interwar period II: cyclical and secular changes in final demand 7. New deal economic policy and the problem of recovery 8. Contemporary economic problems in historical perspective Bibliography Index.

Net farm income is affected by changes in final demand, in marketing charges, and in production costs. BAE publishes data relating to each of these three sets of factors. This article attempts a new combination of these data for a recent year, with agriculture divided into nine major commodity groups. Although the tentative and preliminary nature of the data must be emphasized, information of this kind is needed for several purposes, including estimation of the effect of changes in specific marketing and production cost items upon net income from different commodities. The success of newer approaches to the study of relationships between agriculture and the general economy also depends upon the development of accurate and detailed information of this kind.

The decomposition of a matrix multiplier derived from a social accounting matrix (SAM) by Pyatt and Round [(1979). Accounting and Fixed Price Multipliers in a Social Accounting Matrix Framework. Economic Journal, 89, 850–873] has prompted a number of subsequent applications. In one of the earliest examples Stone [(1985). The Disaggregation of the Household Sector in the National Accounts, Chapter 8. In: G. Pyatt and J.I. Round (eds.) Social Accounting Matrices: A Basis for Planning. Washington, DC, The World Bank, 145–185] made the intriguing observation that the higher order (circular) effects of an exogenous change in final demand on the distribution of income and the structure of production were more or less independent of the sectoral composition of the initial injection. Our initial objective in this article is to explore this phenomenon of distributional invariance and to derive sufficient conditions for it. We then argue that these conditions have important implications for the design of SAMs, for the taxonomies they adopt and for levels of disaggregation, all of which strongly condition the quality of results that can be generated via subsequent modelling.

The transportation sector has an important role in the economy of Indonesia, especially in the Central Java Province. This sector is the artery of the distribution of goods and people in the regions and countries, especially in supporting trade. In additionto the increasing share of Central Java's GRDP from year to year, this sector also absorbs a fairly high workforce. The businesses of this sector also include all levels of formal and informal community businesses from small to large scales. This study analyzes how the transportation sector supports the economy of Central Java by using the Input-Output approach. By applying the 2013 Central Java Input-Output table, the impact of transportation sector activities is examined through the input provider sector (including imported inputs other than domestic), as well as the product buyers' sector of the transportation sector. Based on the path analysis, it can be identified the dependence of other production sectors on the transportation sector. Then, it can be examined the impact of change in final demand and primary input in this sector on economic and sectoral output.

The contribution of this paper is twofold. First, it uses the available official Input–Output data for the Western Balkans economies to estimate the output and value added multipliers of the sectors identified as being either current or emerging strengths within the context of Smart Specialisation. These multipliers indicate the potential impact of changes in final demand for certain products and sectors. This permits the identification of the industries associated with high indirect and induced effects, and to form ideas about the sectoral interdependencies of the economies. For instance, it appears that many sectors related to construction are promising in terms of economic potential related to demand-side monetary injections in Albania. Second, a Multi-Regional dataset is used to investigate the international integration of the Western Balkans economies in terms of participation in the Global Value Chains. The latter has increased over time in the region, but it appears that some economies are benefitting relatively more than others from it.

This study aims to analyze the linkages forward and backward sectors of Agriculture, Forestry and fisheries in the economic development of Central Java province. This study uses data Input Output table of Central Java in 2016. The method of data analysis used in this study is Input-Output Analysis. The results showed that the subsector in the Agriculture, Forestry and fisheries sector that has the highest value of direct and indirect backward linkage is the livestock subsector. This means that the livestock subsector means that each increase in final demand in the livestock subsector by 1 unit will increase the output of other economic sectors that are used directly or indirectly as inputs to the livestock subsector by 1.5330 units. On the other hand, the value of direct and indirect future linkages in the agricultural, forestry and fisheries sectors is the highest, namely the food crop subsector with a value of 1.3903. This means that every increase in output in all sectors of the economy by 1 unit will increase the output of the food crop subsector by 1.3903 which is used directly as input for all sectors of the economy. Keywords: Backward Linkage, Forward Linkage, Economic Development, Agriculture, Forestry And Fisheries Sectors

Indonesia lagged behind most Asian developing economies in growth and indus trialization during the 1960s. In the 1970s, however, Indonesia experienced very high real growth and this was reflected in rapid expansion of the industrial sector. There was a subtle change in policy emphasis during the mid-1970s away from the import substitution strategy in favour of a more export-oriented approach. This study seeks to evaluate how successful this was in making use of input-output analysis, using data from 1971, 1975, and 1980. The sources of output expansion are decomposed into four categories: domestic final demand, export demand, import substitution, and technological change. The findings indicate that the measures designed to stimulate export growth were moderately successful.

In this study, an input output table was developed which was used to examine the empirical evidence on the strength of agricultural growth multipliers, in the facets of income, output and employment. The first order multiplier effect of agriculture was 0.3481 for output, 0.0327 for income and 0.0524 for employment. It contributions to the economy of Limpopo Province was ranked ninth for output and income multipliers and eighth for employment. Trade services were ranked first in all three sets multipliers. From the study, it was concluded that more poverty could be reduced with increased investment trade services sector as it gives more returns to investments. Key words: Input-output analysis, GRIT, Limpopo Province, South Africa.