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A Portable Dynamic Microsimulation Model for Population, Education and Health Applications in Developing Countries

  1. Martin Spielauer  Is a corresponding author
  2. Olivier Dupriez  Is a corresponding author
  1. Consultant for The World Bank Development Data Group, United States
  2. The World Bank Development Data Group, United States
Research article
Cite this article as: M. Spielauer, O. Dupriez; 2019; A Portable Dynamic Microsimulation Model for Population, Education and Health Applications in Developing Countries; International Journal of Microsimulation; 12(3); 6-27. doi: 10.34196/ijm.00205
8 figures and 5 tables

Figures

DYNAMIS-POP simulation projections for prenatal care, three scenarios.
DYNAMIS-POP simulation projections for immunization rates by mother’s education, base scenario w/o prenatal care.
DYNAMIS-POP simulation projections for immunization rates by mother’s education, four alternative scenarios.
DYNAMIS-POP simulation projections for immunization rates, six scenarios.
Distribution of mother’s education of one-year old children. DYNAMIS-POP projection and DHS data.
Increase in immunization rates: projected total increases and increases due to composition effects.
Figure A1–1
Age heaping in the 2001 Census of Nepal and its treatment preparing data for DYNAMIS-POP.
Figure A1–2
Underreporting of young children in the 2001 Census of Nepal. The red bars are ‘missing children’ when back-projecting children 0–4 using the number of children born in Nepal age 10–14 in the 2011 Census.

Tables

Table 1
A simplified classification of caste and ethnicities in Nepal according to the The World Bank (2006) study on „Unequal Citizens. Gender, Caste and Ethnic Inclusion in Nepal
% Total population GSEA / NLSS II (10 groups) 2001 census (103 groups)
Hindu caste groups (57.5%) 1.BC (Hill) Brahman, Chhetri, Thakuri, Sanyasi
2.BC (Tarai) Kayashta, Rajput, Baniya, Marwadi, Jaine, Nurang, Bengali
3.Tarai Middle Castes Yadev,Teli, Kalwar, Sudi, Sonar, Lohar, Koiri, Kurmi, Kanu, Haluwai, Hajam/Thakur, Badhe, Rajbhar, Kewat Mallah, Numhar, Kahar, Lodha, Bing/Banda, Bhediyar, Mali, Kamar Dhunia
4.Dalits (Hill) Kami, Damai, Sarki, Gaine, Badi
5.Dalits (Tarai) Chamar, Musahar, Tatma, Bantar, Dhusadadh/Paswan, Khatway, Dom, Chidimar, Dhobi, Halkhor, Unidentified Dalit
Janajatis (37.2%) 6.Newar All Newari Castes
7.Janajatis (Hill) Magar,Tamang, Rai, Gurung, Limbu, Sherpa, Bhote, Walung, Buansi, Hyolmo, Gharti/Bhujel, Kumal, Sunuwar, Baramu, Pahari, Adivasi Janajati, Yakkha, Shantal, Jirel, Darai, Dura, Majhi, Dunuwar, Thami, Lepcha, Chepang, Bote, Raji, Hayu,Raute, Kasunda
8.Janajatis (Tarai) Tharu, Dhanuk, Rajbanshi, Tajpuriya, Gangai, Dhimal, Meche, Kisan, Munda, Santhal/Satar/Dhangad/Jhangad, Koche, Pattarkatta/Kusbadiya
Muslims (4.3%) 9.Muslims Muslim, Churoute
Others (1%) 10.Others
Table 2
Descriptive results of prenatal care and immunization rates. Source: DHS 2001 and DHS 2011, own calculations
Prenatal care Immunization DHS 2001 Immunization DHS 2011
DHS 2001 DHS 2011 No Prenatal Care Prenatal Care All DHS 2001 All DHS 2011
Region Eastern 56.5% 90.6% 61.7% 83.7% 74.1% 87.7%
Central 54.1% 84.7% 46.6% 72.3% 60.5% 83.1%
Western 55.2% 84.1% 44.2% 81.5% 64.8% 91.2%
Mid-West 38.2% 82.1% 60.4% 85.2% 69.9% 84.7%
Far-West 35.5% 91.4% 44.3% 89.7% 60.4% 93.7%
Ethnicity Brahaman/Chhetri 53.5% 89.7% 58.8% 90.2% 75.6% 90.7%
Tarai/Madhesi 54.6% 91.1% 41.5% 66.4% 55.1% 82.0%
Hill Dalits 44.4% 86.8% 53.0% 83.9% 66.7% 87.0%
Tarai/Madhesi Dalits 54.6% 89.0% 37.6% 39.7% 38.8% 83.8%
Newar/Janajati 49.3% 80.5% 56.0% 89.0% 72.3% 93.5%
Muslim 49.9% 89.8% 28.7% 47.1% 37.9% 57.4%
Other 39.1% -- 46.3% 57.1% 50.5% --
Education of mother Never entered school 40.2% 79.6% 47.7% 71.8% 57.4% 78.1%
Primary school dropout 58.0% 88.2% 78.1% 86.8% 83.1% 92.9%
Primary and above 86.2% 93.0% 71.1% 92.2% 89.3% 94.8%
Mother’s age >30 34.9% 70.7% 47.9% 73.5% 56.8% 82.4%
26–30 43.7% 85.1% 48.9% 77.0% 61.2% 86.7%
21–25 52.6% 90.4% 52.9% 84.1% 69.3% 87.8%
18–20 65.0% 89.5% 63.2% 79.7% 73.9% 88.2%
<18 62.8% 90.6% 48.9% 80.7% 68.9% 89.1%
Sex Female 47.8% 84.4% 50.6% 79.4% 64.3% 85.7%
Male 53.0% 88.1% 53.3% 80.5% 67.7% 88.2%
Prenatal care No -- -- -- -- 51.8% 70.3%
Yes -- -- -- -- 79.9% 89.6%
TOTAL 50.3% 86.2% 51.8% 79.9% 65.9% 87.0%
Table 3
Regression results of logistic regression models for prenatal care and immunization based on DHS 2001 and DHS 2011 data. Own calculations. The coefficients are expressed as odds ratios
Prenatal care Immunization DHS 2001 Immunization
DHS 2001 No Prenatal Care Prenatal Care All DHS 2011
Constant 0.626 ** 1.709 5.213 *** 2.419 *** 3.986 ***
Male (Female reference) 1.299 1.052 1.260 * 1.248
Mother entered primary school (No school reference) 1.743 ** 3.926 *** 1.487 2.978 *** 2.779 **
Mother graduated primary education 7.590 *** 2.700 * 2.424 * 4.347 *** 3.444 ***
Central region (Eastern region reference) 0.951 0.526 * 0.591 . 0.581 *** 0.786
Western region 0.754 0.407 ** 0.612 0.479 *** 0.923
Mid-Western region 0.528 ** 0.711 0.782 0.647 * 0.680
Far-Western region 0.459 *** 0.336 ** 0.962 0.374 *** 1.643
Tarai/Madhesi (Brahaman/Chheri reference) 0.447 * 0.360 * 0.457 *** 0.728
Hill Dalits 0.878 0.750 0.851 0.843
Tarai/Madhesi Dalits 0.399 . 0.107 *** 0.240 *** 1.059
Newar and Janajati 0.758 1.091 0.835 1.654
Muslim 0.263 ** 0.147 *** 0.231 *** 0.235 ***
Other 0.570 0.185 *** 0.355 ***
Mother’s birth cohort 1 (25–29 at birth; 30+ reference) 1.199 1.129 1.263 1.185 1.245
Mother’s birth cohort 2 (20–24 at birth) 1.485 * 1.192 2.043 * 1.470 ** 1.170
Mother’s birth cohort 3 ( ≤ 20 at birth) 2.326 *** 1.903 * 1.441 1.808 *** 1.411
Young Mother (age <18; 18+ reference) 0.819 0.408 . 0.919 0.586 ** 0.863
Sample size (n) 1,295 649 646 1,295 943
Table 4
DYNAMIS-POP simulation projections for prenatal care, three scenarios
Prenatal care scenarios Prenatal care rate
2002 2012 2022 2032
Scenario X0 - Base (used in immunization scenarios A0 and A1) 52.0% 67.2% 76.0% 81.5%
Scenario X1 - Closing regional gaps (used in A2 and A3) 52.0% 71.7% 79.9% 84.8%
Scenario X2 - Closing all prenatal care gaps (use in A4 and A5) 52.0% 90.7% 91.6% 91.7%
Table 5
DYNAMIS-POP simulation projections for immunization rates, six scenarios
Immunization scenarios Immunization rate
2002 2012 2022 2032
Scenario A0 - Base (prenatal care scenario X0 - Base) 68.1% 77.2% 81.3% 83.8%
Scenario A1 - Closing ethnic gaps (prenatal care scenario X0 - Base) 68.2% 83.2% 87.1% 89.3%
Scenario A2 - Closing regional gaps (prenatal care scenario X1 - closing regional gaps) 68.2% 83.8% 86.6% 88.3%
Scenario A3 - Closing ethnic & regional gaps (prenatal care scenario X1 - closing regional gaps) 68.2% 88.8% 91.5% 92.8%
Scenario A4 - Closing ethnic & regional & all prenatal care gaps (prenatal care scenario X2) 68.2% 91.0% 92.4% 93.2%
Scenario A5 - Closing prenatal care gaps only (prenatal care scenario X2) 68.1% 81.7% 83.5% 84.9%

Data and code availability

DYNAMIS-POP is based on data readily available for most developing countries. It is designed to be easily ported to countries. We provide a version for an imaginary country usable for testing, training, and as a template for creating new country applications. Data provided with the model are synthetically generated non-confidential data. All data-based parameters as well as the starting population are generated from a set of four data files which can be derived from population census data and from the data collected through a Demographic and Health Survey (DHS), a Multiple Indicator Cluster Survey (MICS), or equivalent. Parameter generation is highly automated to facilitate porting the model to new country contexts by adapting just a few country-specific set-up files. Equally, besides a specific country setup module, which must be adapted to account for country-specific features like geographical regions or the definition of ethnical groups, all modules are generic.

DYNAMIS-POP is fully documented, and all its components are freely available. DYNAMIS-POP is created using freely available software. Its code - including the full set of statistical analysis files for parameter generation and estimation - is available for download at dynamis.ihsn.org. The analysis presented in this paper was performed with DYNAMIS-POP version 2.202. The model is implemented in Modgen, a generic microsimulation programming language developed and maintained at Statistics Canada. All statistical analysis is performed using the open-source statistical package R. Statistical analysis files are documented and include statistical and graphical output of analysis results. DYNAMIS-POP has an intuitive graphical user interface and runs on a standard personal computer. The model documentation includes a step-by-step implementation guide which can be used as textbook for Modgen programming.

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