Research article

The 2014 Mongolian Social Accounting Matrix

  • Received: 13 February 2020 Accepted: 31 March 2020 Published: 07 April 2020
  • JEL Codes: C82, E01, E16

  • This paper describes the construction of the Mongolian Social Accounting Matrix (SAM) for 2014 in detail. The SAM has fifty-six sectors, seventy commodities, two types of production factors (capital and labor), three types of institutions (households, government and the rest of the world) along with capital accounts, three types of taxes (direct taxes, import duties and indirect taxes on commodities) and investment accounts (public investment, private investment and changes in inventories).

    Citation: Tsolmon Baatarzorig, Nyambaatar Batbayar, Ragchaasuren Galindev, Oyunzul Tserendorj. The 2014 Mongolian Social Accounting Matrix[J]. National Accounting Review, 2020, 2(2): 138-154. doi: 10.3934/NAR.2020008

    Related Papers:

    [1] Ancheng Deng, Xiaoqiang Sun . Dynamic gene regulatory network reconstruction and analysis based on clinical transcriptomic data of colorectal cancer. Mathematical Biosciences and Engineering, 2020, 17(4): 3224-3239. doi: 10.3934/mbe.2020183
    [2] Qian Li, Minawaer Hujiaaihemaiti, Jie Wang, Md. Nazim Uddin, Ming-Yuan Li, Alidan Aierken, Yun Wu . Identifying key transcription factors and miRNAs coregulatory networks associated with immune infiltrations and drug interactions in idiopathic pulmonary arterial hypertension. Mathematical Biosciences and Engineering, 2023, 20(2): 4153-4177. doi: 10.3934/mbe.2023194
    [3] Jiaxin Luo, Lin Wu, Dinghui Liu, Zhaojun Xiong, Linli Wang, Xiaoxian Qian, Xiaoqiang Sun . Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data. Mathematical Biosciences and Engineering, 2021, 18(6): 7774-7789. doi: 10.3934/mbe.2021386
    [4] Youlong Lv, Jie Zhang . A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines. Mathematical Biosciences and Engineering, 2019, 16(3): 1228-1243. doi: 10.3934/mbe.2019059
    [5] Changxiang Huan, Jiaxin Gao . Insight into the potential pathogenesis of human osteoarthritis via single-cell RNA sequencing data on osteoblasts. Mathematical Biosciences and Engineering, 2022, 19(6): 6344-6361. doi: 10.3934/mbe.2022297
    [6] Ming-Xi Zhu, Tian-Yang Zhao, Yan Li . Insight into the mechanism of DNA methylation and miRNA-mRNA regulatory network in ischemic stroke. Mathematical Biosciences and Engineering, 2023, 20(6): 10264-10283. doi: 10.3934/mbe.2023450
    [7] Cicely K. Macnamara, Mark A. J. Chaplain . Spatio-temporal models of synthetic genetic oscillators. Mathematical Biosciences and Engineering, 2017, 14(1): 249-262. doi: 10.3934/mbe.2017016
    [8] Ignacio Alvarez-Castro, Jarad Niemi . Fully Bayesian analysis of allele-specific RNA-seq data. Mathematical Biosciences and Engineering, 2019, 16(6): 7751-7770. doi: 10.3934/mbe.2019389
    [9] David Iron, Adeela Syed, Heidi Theisen, Tamas Lukacsovich, Mehrangiz Naghibi, Lawrence J. Marsh, Frederic Y. M. Wan, Qing Nie . The role of feedback in the formation of morphogen territories. Mathematical Biosciences and Engineering, 2008, 5(2): 277-298. doi: 10.3934/mbe.2008.5.277
    [10] Shengjue Xiao, Yufei Zhou, Ailin Liu, Qi Wu, Yue Hu, Jie Liu, Hong Zhu, Ting Yin, Defeng Pan . Uncovering potential novel biomarkers and immune infiltration characteristics in persistent atrial fibrillation using integrated bioinformatics analysis. Mathematical Biosciences and Engineering, 2021, 18(4): 4696-4712. doi: 10.3934/mbe.2021238
  • This paper describes the construction of the Mongolian Social Accounting Matrix (SAM) for 2014 in detail. The SAM has fifty-six sectors, seventy commodities, two types of production factors (capital and labor), three types of institutions (households, government and the rest of the world) along with capital accounts, three types of taxes (direct taxes, import duties and indirect taxes on commodities) and investment accounts (public investment, private investment and changes in inventories).




    [1] Ayadi M, Salem HH (2014) Construction of financial social accounting matrix for Tunisia. Int J Bus Social Sci 5: 216-221.
    [2] Baatarzorig TS, Galindev R, Maisonnave H (2019) Effects of ups and downs of the Mongolian mining sector. Environ Dev Econ 23: 527-542.
    [3] Boughanmi H, Zaibet L, Al-Jabri O, et al. (2002) Constructing a social accounting matrix: Concepts and use in economic policy analysis. Agric Sci 7: 1-11.
    [4] Cicowiez M, Lofgren H (2018) Technical Note on the Construction of a Social Accounting Matrix for Mongolia 2015.
    [5] Harun M, Zakariah AR, Azali M (2012) Constructing a social accounting matrix framework to analyze the impact of public expenditure on income distribution in Malaysia. Jurnal Ekonomi Malaysia 46: 63-83.
    [6] Keuning SJ, de Ruijter WA (1988) Guidelines to the construction of a social accounting matrix. Rev Income Wealth 34: 71-100. doi: 10.1111/j.1475-4991.1988.tb00561.x
    [7] Pyatt G, Round JI (1977) Social accounting matrices for development planning. Rev Income Wealth 23: 339-364. doi: 10.1111/j.1475-4991.1977.tb00022.x
    [8] Round JI (2003) Constructing SAMs for development policy analysis: Lessons learned and challenges ahead. Econ Syst Res 15: 161-183. doi: 10.1080/0953531032000091153
  • This article has been cited by:

    1. William Chad Young, Ka Yee Yeung, Adrian E Raftery, Identifying dynamical time series model parameters from equilibrium samples, with application to gene regulatory networks, 2019, 19, 1471-082X, 444, 10.1177/1471082X18776577
    2. Feng Liu, Qicheng Mei, Fenglan Sun, Xinmei Wang, Hua O Wang, 2018, Stability and Neimark-Sacker Bifurcation Analysis for Single Gene Discrete System with Delay, 978-988-15639-5-8, 961, 10.23919/ChiCC.2018.8483728
    3. Xiao Liang, William Chad Young, Ling-Hong Hung, Adrian E. Raftery, Ka Yee Yeung, Integration of Multiple Data Sources for Gene Network Inference Using Genetic Perturbation Data, 2019, 26, 1557-8666, 1113, 10.1089/cmb.2019.0036
    4. Xiao Liang, William Chad Young, Ling-Hong Hung, Adrian E. Raftery, Ka Yee Yeung, 2018, Integration of Multiple Data Sources for Gene Network Inference using Genetic Perturbation Data, 9781450357944, 601, 10.1145/3233547.3233692
    5. Sanrong Liu, Haifeng Wang, 2019, Chapter 15, 978-981-15-0120-3, 186, 10.1007/978-981-15-0121-0_15
    6. Bei Yang, Yaohui Xu, Andrew Maxwell, Wonryull Koh, Ping Gong, Chaoyang Zhang, MICRAT: a novel algorithm for inferring gene regulatory networks using time series gene expression data, 2018, 12, 1752-0509, 10.1186/s12918-018-0635-1
    7. William Chad Young, Adrian E. Raftery, Ka Yee Yeung, Model-based clustering with data correction for removing artifacts in gene expression data, 2017, 11, 1932-6157, 10.1214/17-AOAS1051
    8. Nimrita Koul, Sunilkumar S Manvi, 2020, A Perturbation based Algorithm for Inference of Gene Regulatory Networks for Multiple Myeloma, 978-1-7281-4108-4, 862, 10.1109/ICESC48915.2020.9155886
    9. Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez, Machine learning applications in drug development, 2020, 18, 20010370, 241, 10.1016/j.csbj.2019.12.006
    10. Chengye Zou, Xiaopeng Wei, Qiang Zhang, Changjun Zhou, Passivity of Reaction–Diffusion Genetic Regulatory Networks with Time-Varying Delays, 2018, 47, 1370-4621, 1115, 10.1007/s11063-017-9682-7
    11. Wenxia Zhou, Xuejun Li, Lu Han, Shengjun Fan, 2021, Chapter 2, 978-981-16-0752-3, 35, 10.1007/978-981-16-0753-0_2
  • Reader Comments
  • © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3887) PDF downloads(357) Cited by(0)

Article outline

Figures and Tables

Tables(12)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog