سامتی، مرتضی؛ صامتی، مجید و قضاوی، رسول (1387). بررسی اثر ترکیب بودجه دولت بر رفاه اجتماعی در ایران: دوره زمانی (1382-1360).
مجله توسعه و سرمایه، 1(2)، 70-49.
https://jdc.uk.ac.ir/article_1892.html.
عسگری، حشمتاله؛ مریدیان، علی و هواس بیگی، فاطمه (1403). تأثیر پیچیدگی اقتصادی و نابرابری درآمد با تأکید بر نقش شاخص توسعه انسانی در اقتصاد ایران با رویکرد ARDL بوت استرپ.
مجله توسعه و سرمایه، 9(2)، 56-35.
https://jdc.uk.ac.ir/article_3262.html.
علیزاده، محمد؛ نعمتی، غلامرضا؛ فطرس، محمدحسن؛ خداوردی سامانی، مریم و کبیری، دینا (1401). شناسایی عوامل مؤثر بر رفاه اجتماعی ایران تحت نااطمینانی: رویکرد متوسط گیری بیزی
. اقتصاد باثبات، 3(1)، 61-99.
https://sedj.usb.ac.ir/article_6703.html.
محمدی، تیمور؛ خیابانی، ناصر؛ بهرامی، جاوید و فهیمیفر، فاطمه (1399). مقایسه روشهای مختلف پیش بینی رشد اقتصادی ایران با تأکید بر مدلهای گزینشی نمودن و متوسطگیری الگوی پویا.
پژوهشهای اقتصادی (رشد و توسعه پایدار)، ۲۰(۴)،۹۳-۱۲۳.
https://ecor.modares.ac.ir/article-18-38166-fa.html.
مهرآرا، محسن؛ رضایی برگشادی، صادق (1395). بررسی عوامل مؤثر بر رشد اقتصادی ایران مبتنی بر رویکرد متوسط گیری بیزین (BMA) و حداقل مربعات متوسط وزنی (WALS).
پژوهشهای رشد و توسعه اقتصادی، 6(23)، 114-89.
https://egdr.journals.pnu.ac.ir/article_2724.html.
نوری نائینی، محمدسعید؛ قاسمی، حسامالدین و کاظمی تربقان، مریم سادات (1396). بررسی عوامل مؤثر بر شاخص توسعه انسانی در ایران با استفاده از روکرد میانگینگیری بیزی.
پژوهشهای رشد و توسعه اقتصادی، 8(29)، 45-60.
https://egdr.journals.pnu.ac.ir/article_3039.html.
References
Alderman, H., & Yemtsov, R (2014). How can safety nets contribute to economic growth?
The World Bank Economic Review, 28(1), 1–20. DOI:
10.1093/wber/lht011.
Alizadeh, M., Nemati, G., Fotros, M.H., Khodaverdi Samani, M., & Kabiri, D. (2022). Identifying factors affecting Iran’s social welfare under uncertainty: A Bayesian average approach.
Stable Economy Journal, 3(1), 61-97.
https://sedj.usb.ac.ir/article_6703.html?lang=en [In Persian].
Arisman, A. (2018). Determinant of human development index in ASEAN countries.
Signifikan J. Ilmu Ekon, 7(1), 113-122. DOI:
10.15408/sjie.v7i1.6756.
Asgari, H., Moridian, A., & Havasbeigi, F. (2024). The impact of economic complexity on income inequality with emphasis on the role of human development index in Iran's economy with ARDL bootstrap approach.
Journal of Development and Capital,
9(2), 35-56.
https://jdc.uk.ac.ir/article_3262.html?lang=en [In Persian].
Aye, G., Gupta, R., Hammoudeh, S., & Kim, W.J. (2015). Forecasting the price of gold using dynamic model averaging.
International Review of Financial Analysis, 41, 257–266.
https://doi.org/10.1016/j.irfa.2015.03.010.
Baur, D.G., Beckmann, J., & Czudaj, R. (2016). A melting pot- Gold price forecasts under model and parameter uncertainty.
International Review of Financial Analysis, 48, 282–291.
https://doi.org/10.1016/j.irfa.2016.10.010.
Bruns, S.B., & Ioannidis, J.P.A. (2019). Determinants of economic growth: Different time different answer?
Journal of Macroeconomics, 63, 103-185. DOI:
10.1016/j.jmacro.2019.103185.
Clapp, J. (2000). Development as freedom. SAGE Publications. Sage UK: London, England. [
Researchgate].
Claudia, K.S., & Arif, M. (2022). Determinant analysis of human development index (HDI) in semarang residency. In
International Conference on Economics and Business Studies (ICOEBS 2022) pp. 52-58. Atlantis Press. DOI:
10.2991/aebmr.k.220602.008.
Cook, J.T., & Frank, D.A. (2008). Food security, poverty, and human development in the United States. Annals of the New York Academy of Sciences, 1136(1), 193–209. DOI:
10.1196/annals.1425.001.
Di Filippo, G. (2015). Dynamic model averaging and CPI inflation forecasts: A comparison between the euro area and the United States.
Journal of Forecasting, 34(8), 619-648.
https://doi.org/10.1002/for.2350.
Forni, M., Hallin, M., Lippi, M. & Reichlin, L. (2003). Do financial variables help forecasting inflation and real activity in the Euro area?
Journal of Monetary Economics, 50, 1243–1255.
https://doi.org/10.1016/S0304-3932(03)00079-5.
Forni, M., Hallin, M., Lippi, M., & Reichlin, L. (2004). The generalized dynamic factor model consistency and rates.
Journal of Econometrics, 119(2), 231–255. DOI:
10.1198/016214504000002050.
Forni, M., Reichlin, L., Hallin, M., & Lippi, M. (2000). The generalized dynamic-factor model: Identification and estimation.
Review of Economics and Statistics, 82(4), 540-554.
https://www.jstor.org/stable/2646650.
Greve, J., Grün, B., Malsiner‐Walli, G., & Frühwirth‐Schnatter, S. (2022). Spying on the prior of the number of data clusters and the partition distribution in Bayesian cluster analysis.
Australian & New Zealand Journal of Statistics, 64(2), 205–229.
https://doi.org/10.1111/anzs.12350.
Gupta, R., Hammoudeh, Sh., Kim, W.J., & Simo-Kengne, B.D. (2014). Forecasting China’s foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals, financial stress and economic uncertainty.
North American Journal of Economics and Finance, 28, 170-189. DOI:
10.1016/j.najef.2014.02.003.
Khan, M.A., & Milne, G. (2019). Global governance, neoliberalism and national responses: The case of Bangladesh’s ready‐made garment (RMG) sector.
Development Policy Review, 37, O230-O247. DOI:
10.1111/dpr.12383.
Koop, G., & Korobilis, D. (2009). Bayesian multivariate time series methods for empirical macroeconomics.
SSRN Electronic Journal.
https://ssrn.com/abstract=1514412.
Koop, G., & Korobilis, D. (2011). UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?
Economic Modelling, 28, 2307–2318. DOI:
10.2139/ssrn.1509724.
Koop, G., McIntyre, S., Mitchell, J., & Poon, A. (2020). Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970.
J. Appl. Econometrics, 35, 176-197.
https://doi.org/10.1002/jae.2748.
Kurniawan, B., Kusdiana, D., Suryaman, R., & Priadana, M. (2023). The influence of macroeconomic factors and corruption on human development in ASEAN-7. In Proceedings of the
6th International Conference of Economics, Business, and Entrepreneurship, ICEBE, 13-14 September 2023, Bandar Lampung, Indonesia. DOI:
10.4108/eai.13-9-2023.2341207.
Marcellino, M., & Stock, H.J., & Watson, M.W. (2003). Macroeconomic forecasting in the euro area: Country specific versus area-wide information.
European Economic Review, 47(1), 1-18. DOI:
10.1016/S0014-2921(02)00206-4.
Mark, C., Metzner, C., Lautscham, L., Strissel, P.L., Strick, R., & Fabry, B. (2018). Bayesian model selection for complex dynamic systems
. Nat Commun, 9(1), 1803.
https://www.nature.com/articles/s41467-018-04241-5.
Mehrara, M., & Rezaei Bargoshadi, S. (2016). The determinants of economic growth in Iran based on Bayesian model averaging and weighted averaging least square.
Economic Growth and Development Research, 6(23), 114-89.
https://egdr.journals.pnu.ac.ir/article_2724.html?lang=en [In Persian].
Mohammadi, T., Khiabani, N., Bahrami, J., & Fahimifar F. (2020). Comparison of different methods of predicting Iran's economic growth with an emphasis on dynamic model selection and dynamic model averaging.
The Economic Research (Sustainable Growth and Development), 20(4), 93-123.
http://ecor.modares.ac.ir/article-18-38166-fa.html [In Persian].
Naser, H., & Alaali, F. (2018). Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach.
Empirical Economics, 55(4), 1757–1777. [
Repec].
Nattrass, N., & Seekings, J. (2018). Employment and labour productivity in high unemployment Countries.
Development Policy Review, 36, O769-O785.
https://doi.org/10.1111/dpr.12313.
Noori Naeini, M.S., Ghasemi, H., & Kazemi Torbaghan, M.S. (2017). Examination of affecting factors on Iran’s human development index using Bayesian model averaging approach.
Economic Growth and Development Research, 8(29), 45-60
https://egdr.journals.pnu.ac.ir/article_3039.html?lang=en [In Persian].
Paus, E. (2009). The rise of China: Implications for Latin American development.
Development Policy Review, 27(4), 419–456. DOI:
10.1111/j.1467-7679.2009.00454.x.
Peet, R., & Hartwick, E. (2015). Theories of development: Contentions, arguments, alternatives. Guilford Publications. DOI:
10.26458/jedep.v4i4.127.
Raftery, A.E., Kárný, M., & Ettler, P. (2010). Online prediction under model uncertainty via dynamic model averaging: Application to a cold rolling mill.
Technometrics, 52(1), 52–66. DOI:
10.1198/TECH.2009.08104.
Sachs, J.D. (2005). Investing in development: A practical plan to achieve the millennium development goals. United Nations Development Programme.
UN Millennium Project. Earthscan. [
PDF].
Sala-I-Martin, X., Doppelhofer, G., & Miller, R.I. (2004): Determinants of long-term growth: Bayesian averaging of classical estimates (BACE).
American Economic Association 94(4), 813–835. [
PDF].
Sameti, M., Sameti, M., & Ghazavi, R. (2008). Studying the effect of state budget composition for social welfare in Iran: During the years (1981-2003).
Journal of Development and Capital,
1(2), 49-70.
https://jdc.uk.ac.ir/article_1892.html?lang=en [In Persian].
Sayifullah, S., & Gandasari, T.R. (2016). Pengaruh indeks pembangunan manusia dan pengangguran terhadap kemiskinan di Provinsi Banten.
Jurnal Ekonomi-Qu, 6(2), 236-255.
http://dx.doi.org/10.35448/jequ.v6i2.4345.
Schumacher, J., Hoffmann, P., Schmäl, C., Schulte-Körne, G., & Nöthen, M.M. (2007). Genetics of dyslexia: The evolving landscape.
Journal of Medical Genetics, 44(5), 289–297. DOI:
10.1136/jmg.2006.046516.
Sen, A. (1985). Commodities and capabilities. OUP Catalogue, Oxford University Press. [
Abebooks].
Sen, A. (1999). Democracy as a universal value.
Journal of Democracy, 10(3), 3-17. [
PDF].
Sen, A. (2001). Development as freedom. Oxford Paperbacks. [
PDF].
Soebagiyo, D. (2007). Disparitas pembangunan Dan Faktor-faktor Yang Mempengaruhinya (Studi Kasus Di Daerah Sumbagsel).
Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan, 1(1), 21-34. DOI:
10.23917/jep.v1i1.3890.
Stock, J.H., & Watson, M.W. (2002). Forecasting using principal components from a large number of predictors.
Journal of the American Statistical Association, 97, 1167-1179.
https://www.jstor.org/stable/3085839.
Sulistyowati, U., & Magna, M.S. (2023). The impact of policies during Covid-19 by factors affecting the human development index in soloraya using regression method.
International Journal of Multidisciplinary Research and Literature, 2(3), 316-322.
https://ijomral.esc-id.org/index.php/home/article/view/118.
Sumiyarti, S., Firdayeti, F., & Handayani, K. (2022). Determinants of human development index: Case study of provinces in Indonesia. Proceedings of the first lekantara annual conference on public administration, literature, social sciences, humanities, and education, LePALISSHE 2021, August 3, 2021, Malang, Indonesia.
http://dx.doi.org/10.4108/eai.3-8-2021.2315091.
Syofya, H. (2018). Effect of poverty and economic growth on Indonesia human development index.
Jurnal Ilmiah Universitas Batanghari Jambi, 18(2), 416–423. DOI:
10.33087/jiubj.v18i2.486.
Telch F., & Appe S. (2022). How can countries improve human development? Four distinct national planning strategies and the challenges for human development ahead.
Development Policy Review, Overseas Development Institute, vol. 40(2), March.
https://doi.org/10.1111/dpr.12561.
Tsai, M.C. (2006).Macro-structural determinants of political freedom in developing countries: A cross-national analysis.
Social Indicators Research, 76(2), 317–340. DOI:
10.1007/s11205-005-0207-9.
United Nations. (1990). Human development Report 1990
. UNDP. [
PDF].
Van der Hoeven, R. (2003). Into the twenty-first century: Assessing social and political concerns
. In H.van Ginkel, B. Barrett, J. Court, J. & J. Velasquez (Eds.), Human development and the environment: Challenges for the United Nations in the new millennium.
United Nations University Press.
https://www.researchgate.net/publication/44828355.
Van Wolferen, K. (2003). Conceptual challenges of a globalizing economy. In H. van Ginkel, B. Barrett, J. Court, J. & J. Velasquez (Eds.), Human Development and the Environment: Challenges for the United Nations in the New Millennium.
United Nations University Press.
https://digitallibrary.un.org/record/469068?ln=ar&v=pdf.
Yolanda, Y. )2017). Analysis of factors affecting inflation and its impact on human development index and poverty in Indonesia. European Research Studies Journal, 20(4), 38–56. DOI: 10.35808/ersj/873.
Zhang, Ch., & Frederick A., & Matsen, I.V. (2018). Generalizing tree probability estimation via Bayesian networks
. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. CesaBianchi, and R. Garnett (eds.), Advances in
Neural Information Processing Systems 31, 1451–1460. DOI:
10.48550/arXiv.1805.07834.
Zhou, Y., Lin, R., & Lee, J.J. (2021). The use of local and nonlocal priors in Bayesian test-based monitoring for single-arm phase II clinical trials.
Pharm Stat. 20(6), 1183-1199.
https://doi.org/10.1002/pst.2139.