The Pioneering Stage in Input-Output Economics: The Soviet National Economic Balance 1923-24, After Fifty Years

1975 ◽  
Vol 57 (1) ◽  
pp. 27 ◽  
Author(s):  
Nicolas Spulber ◽  
Kamran Moayed Dadkhah
2017 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Tajerin Tajerin ◽  
Risna Yusuf ◽  
Sastrawidjaja Sastrawidjaja ◽  
Asnawi Asnawi

Keterkaitan sektor perikanan dalam perekonomian nasional akan menentukan peran strategis sektor tersebut dalam pembangunan perikanan dan pemulihan perekonomian nasional. Untuk itu telah dilakukan kajian mengenai keterkaitan sektor perikanan ”dalam arti luas” dengan menggunakan metode analisis keterkaitan ke belakang (backward lingkage) dan ke depan (forward lingkage) berdasarkan pendekatan model input output. Data yang digunakan dalam kajian ini adalah data sekunder dari table input output tahun 1990, 1995 dan 2000. Hasil kajian menunjukkan bahwa selama periode 1990-2000, secara rata-rata keterkaitan sektor perikanan dalam perekonomian nasional masih relatif lemah dengan indeks keterkaitan berkisar sebesar 0,46-1,10. Kecenderungan penguatan keterkaitan ke belakang terjadi pada perikanan darat, sedangkan penguatan keterkaitan ke depan terjadi pada industri pengolahan dan pengawetan ikan. Selain itu, keterkaitan antara kelompok perikanan primer (perikanan laut dan perikanan darat) dan kelompok perikanan sekunder (industri pengeringan dan penggaraman ikan dan industri pengolahan dan pengawetan ikan) lebih mencerminkan keterkaitan ke depan berupa aliran pasokan komoditas ikan untuk bahan baku. Namun keterkaitan itu masih relatif lemah dan cenderung semakin lemah. Tittle: Fisheries Sector Linkages in The National Economy: An Input-Output Approach.Fisheries sector linkage in National Economy will determine the strategic roles of the sector for its development and National Economic recovery. In line with this, a study was conducted to determine backward and forward linkage of the sector using input output model approach. Secondary data were used, that are input output tables of the year 1990, 1995 and 2000. The results of the study showed that during the period of 1990 - 2000, the average linkage of these sector in National economy are relatively weak with the index of linkage approximately of 0,46 - 1,10.Stronger backward linkage was observed in inland fisheries, while stronger forward linkage demonstrated on industrial fish processing and preservation. The linkage of primary fisheries group (sea and inland fisheries) to the secondary fisheries group (industrial fish processing) indicating the forward linkage such as fish supply as raw materials. However, the linkage is relatively weak.


Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2351
Author(s):  
Xuefeng Li ◽  
Xiuli Liu

Wastewater propagation chains (WPCs) measure inter-sector average propagation lengths (APL) of wastewater discharge. To achieve sustainable wastewater management, one needs to understand the propagation mechanisms by identifying WPCs at a national level over time. However, the traditional model of identifying WPCs is prone to retaining APLs with lower values but larger wastewater discharge intensities, ignoring many linkages whereby intensities are less than a preset threshold. Nevertheless, these overlooked linkages are valuable in understanding wastewater propagation mechanisms. This study proposed a new model coupled input-output analysis with the graphical theory, called the average propagation lengths-hub covariance graph (APL-HCG). This model can investigate WPCs where the closeness of sector linkages exceeds the preset thresholds. Furthermore, it is capable of retaining linkages for identifying hub wastewater propagation chains (HWPCs). Based on APL-HCG, the resultant HWPCs are decomposed as separated sub-chains which are basically composed of linkages among certain significant sectors belonging to the secondary industry or the tertiary industry. Scenario analyses show that HWPCs are effective in reducing wastewater discharge in the national economic system. The total wastewater discharge would decrease by 1.36%, 2.53%, 2.46%, and 2.11% if we reduced 10% of the final demand of all sectors in HWPCs in 2002, 2007, 2012, and 2017. The APL-HCG model outperforms the traditional model on WPCs by 0.14%, 1.61%, 0.47%, and 0.10%, respectively. The APL-HCG model is 0.21%, 0.68%, 0.70%, and 0.35% better than the scenario of random sampling with the number of sectors equal to HWPCs, respectively. Certain policy implications were provided to reduce wastewater effectively at the national level.


2020 ◽  
Vol 10 (2) ◽  
pp. 117
Author(s):  
Kastana Sapanli ◽  
Tridoyo Kusumastanto ◽  
Sugeng Budiharsono ◽  
Agus Sadelie

Amanat UU 32 tahun 2014 tentang Kelautan salah satunya percepatan dan penguatan ekonomi nasional dari potensi kelautan yang ada. Penelitian ini mengkaji kontribusi PDB ekonomi kelautan; dampak pengembangan ekonomi kelautan; dan implikasi kebijakan pengembangan ekonomi kelautan. Metode penelitian menggunakan analisis data sekunder. Data yang digunakan adalah data sekunder tahun 2010-2015 yang diperoleh dari Badan Pusat Statistik (BPS). Data dianalisis secara deskriptif kuantitatif menggunakan model I-O (Input-Output) yang diupdate ke tahun 2015. Hasil penelitian menunjukkan bahwa persentase produk kelautan terhadap PDB terus meningkat mencapai 28.01 % pada tahun 2015. Berdasarkan kajian terhadap dampak ekonomi yang dihasilkan, perlu diprioritaskan pengembangan ekonomi kelautan pada tiga sektor yaitu: industri kelautan, perikanan dan pariwisata bahari. Prinsip kebijakan pengembangan ekonomi kelautan harus inovatif dan berkelanjutan yang bertumpu pada peningkatan daya saing, modernisasi sistem produksi, penguatan kapasitas pelaku industri dan berbasis komoditas.Title: Dynamics and Policies of Indonesia’s Ocean Economic DevelopmentLaw number 32 of 2014 about The Sea mandates the national economic acceleration and empowerment from the potential of marine. This research examined the contribution of the ocean economy to GDP, impact of ocean economic development, and policy implication of ocean economic development. The research used secondary data analysis method. It used secondary data of 2010-2015 that were collected from Statistics Indonesia. Data were analyzed with quantitative descriptive method with I-O model (input-output), that were updated to 2015. The results showed that the percentage of marine products contribution to GDP increased to 28.01% in 2015. Based on the analysis of economic impact, it is necessary to prioritize the ocean economic development on three sectors: marine industry, fisheries, and marine tourism. The ocean economic development policies must be innovative, sustainable, increasing competitiveness, modernizing production systems, and strengthening the capacity of industrial and commodity-based players.


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