Pith. sign in

REVIEW 4 major objections 5 minor 43 references

The Families that Stay Together: A Network Analysis of Dynastic Power in Philippine Politics

T0 review · 4 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read Clan structure, not seat share, predicts lower HDI in Philippine provinces

desk verdict Serious descriptive value and clever network metrics, but the headline HDI/clan-structure claim rests on a CGC that measures whole-network sparsity, not within-clan inequality. read the letter →

arxiv 2505.21280 v1 pith:WVUUQJRA submitted 2025-05-27 econ.GN q-fin.EC

Rafael Acuna , Aldie Alejandro , Robert Leung This is my paper
classification econ.GNq-fin.EC
keywords politicaldynastiesnetworkanalysisPhilippinesCentralityGiniCoefficientConnectedComponentDensityHumanDevelopmentIndexpartyhoppingHerfindahl-Hirschman
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to show that the structure of political dynasties—how power is distributed inside a clan and how clans connect to one another—matters more for local development than how much power dynasties concentrate. Using election data from 2004 to 2022 and graph-theory indicators built from name-based family links, it reports two headline findings. Dynastic candidates change parties significantly more often than non-dynastic candidates across every election cycle. And provinces with high inequality of influence within clans (Centrality Gini Coefficient) and high inter-clan connection (Connected Component Density) have significantly lower Human Development Index scores, while simple concentration (HHI) does not predict HDI. The authors conclude that anti-dynasty policy should focus on clan structure and collusion rather than on concentration alone.

What carries the argument

The carrying objects are four graph-theoretic indicators computed on province-year networks whose vertices are elected politicians and whose weighted edges encode shared surnames or middle names, with weights scaled by position and approximate consanguinity. Political HHI measures concentration of weighted seat share across Leiden-detected communities; the Centrality Gini Coefficient (CGC) measures inequality of weighted degree centrality across all politicians in the network; Connected Component Density (CCD) measures how many politicians belong to the same connected component; and Average Community Connectivity (ACC) measures, via vertex connectivity, how many nodes must be removed to break a clan apart. The Leiden algorithm supplies the clan boundaries, and the Linear Mixed Model with province-level random intercepts carries the development regressions.

What would settle it

Re-estimate the HDI regression restricting CGC to the giant connected component or to dynastic members only, or add a control for the share of isolated nodes; if the significant negative coefficient on CGC disappears, the 'clan structure' interpretation is an artifact of network sparsity. The Mountain Province 2007 case (CGC=0.978 with exactly two linked politicians) is a natural out-of-sample test.

Watch

Extended reading notes

Core claim

The paper's central claim is that a ruling dynasty's effect on development is shaped more by the internal and inter-clan geometry of family networks than by the sheer share of seats a clan controls. Concretely, in a linear mixed model with provincial random effects and time fixed effects, the Centrality Gini Coefficient (the Gini index of politicians' weighted degree centralities) and the Connected Component Density (one minus the ratio of connected components to politicians) both carry significant negative coefficients in predicting provincial HDI, whereas the Political Herfindahl-Hirschman Index is insignificant. The same model finds no significant link between any dynastic indicator and poverty incidence. In the reverse direction, poverty incidence is positively associated with intra-clan cohesion (ACC) and its lag with inter-clan density (CCD), while higher HDI predicts a lower Centrality Gini Coefficient. The paper presents these results as evidence that clan structure, rather than power concentration alone, is the chief determinant of a dynasty's developmental impact.

Load-bearing premise

The claim that high CGC captures power asymmetry within clans rests on a metric computed over the whole political network, including many isolated non-dynastic politicians, so a high CGC can be produced by a single small connected pair in a sparse network rather than by inequality within a clan.

Editorial extensions

If this is right

  • If clan structure is the operative channel, then policies that break inter-clan alliances or disperse power within clans may matter more than caps on seat concentration.
  • Higher party-hopping among dynasts implies that strengthening parties as credible long-term organizations could reduce reliance on kinship networks.
  • The reverse-direction results imply a feedback loop: poverty makes clans tighter-knit and more interconnected, which in turn predicts lower HDI, potentially locking poor provinces into dynastic rule.
  • The insignificance of HHI for HDI qualifies prior work that used concentration alone, suggesting those estimates may understate or misattribute the developmental cost of dynasties.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The CGC is defined over all politicians, not just clan members, so the paper's interpretation of high CGC as "inequalities of influence between clan members" is not strictly supported by the metric; high CGC can arise from network sparsity (e.g., Mountain Province 2007), so the HDI-CGC coefficient may partly reflect fragmentation rather than intra-clan inequality.
  • Because family ties are inferred from shared surnames and middle names, the network may overstate dynastic structure in provinces with common surnames, though within-province matching mitigates this.
  • The bidirectional LMM results suggest a self-reinforcing equilibrium that could be modeled explicitly in future work, e.g., as a dynamical system of dynasty density and development.
  • The same indicator set could be applied to other countries with weak parties and strong kinship politics to test whether clan structure is the generalizable driver.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper reconstructs provincial political kinship networks from Philippine local election returns (2004–2022), identifies clans via the Leiden community-detection algorithm, and proposes four network indicators: Political HHI, Centrality Gini Coefficient (CGC), Connected Component Density (CCD), and Average Community Connectivity (ACC). It reports that dynasties have grown stronger and more interconnected, that dynastic candidates switch parties more often than non-dynasts, and that provinces with high CGC and high CCD have significantly lower Human Development Index scores in a Linear Mixed Model with provincial random intercepts and time fixed effects.

Significance. If the interpretation of the indicators were valid, the paper would provide a useful set of structural measures for studying political dynasties and a provocative empirical result—that clan structure, rather than concentration per se, predicts lower human development. The paper is unusually transparent about some modeling choices (e.g., explicitly labeling the node weights arbitrary) and provides extensive appendix tables, which aids reproducibility. The algebraic equivalence between the two CGC formulas is correctly demonstrated. However, the central developmental claim rests on a metric whose definition does not match the paper's stated interpretation, and the absence of sensitivity analyses leaves the quantitative conclusions vulnerable to the arbitrary weights and community-detection settings.

major comments (4)
  1. [Definition 2.4.5, Eq. (2.4.2.2); Section 5.1.2; Table 5.3] The CGC is defined as the Gini coefficient of weighted degree over all politicians in the provincial network; community or clan labels never enter its computation. The abstract's characterization of CGC as 'inequalities of influence between clan members' is therefore not supported by the metric's definition. The paper's own example of Mountain Province 2007 (CGC = 0.978) is a network with exactly one two-node family and all other politicians isolated, so the high CGC is driven by many zero-degree nodes, i.e., network sparsity, not by within-clan asymmetry. Consequently, the HDI regression coefficient for CGC (-0.336, p < 0.001) cannot be interpreted as evidence about power asymmetries within clans; it may simply capture the share of isolated politicians. The paper should either redefine CGC using within-community degree distributions or include the share of isolated nodes / network sparsity as a control variable and re-estimate the HDI model.
  2. [Section 4.2, Table 4.4, Section 4.2.1] The node weights (Councilor 2, Vice Mayor 3, Mayor 5, etc.) are explicitly described as arbitrary, and the Leiden resolution is fixed at 1 with no sensitivity analysis. Since both CGC and HHI depend directly on these choices, and since CGC is one of the two significant predictors in the headline HDI regression, the qualitative conclusions should be shown to be robust across a reasonable range of weight schemes and resolution parameters. At a minimum, the authors should report the correlation between the metrics under alternative settings or re-run the LMM for a few representative choices.
  3. [Section 5.2] The abstract and conclusion state that party-hopping rates are significantly higher among dynastic candidates 'across every election cycle,' but the only reported inferential result is a single Wilcoxon signed-rank test (statistic 56691.5, p = 0.0039) that appears to pool all province–year pairs. No per-cycle test results are shown. Please either provide the per-cycle test statistics and p-values or revise the claim to state that the difference is significant when all cycles are pooled.
  4. [Section 5.3.1, Table 5.4] The LMM's conditional R2 of 0.8352 versus OLS R2 of 0.093 is presented as evidence that the model provides a strong fit, but conditional R2 includes the variance explained by provincial random intercepts, which are not the dynastic indicators of interest. The paper should also report marginal R2 and standardized fixed-effect coefficients so that the reader can judge how much of the variation in HDI is actually associated with CGC and CCD, as opposed to province-level heterogeneity.
minor comments (5)
  1. [Definition 2.4.6] The definition heading reads 'Connected Component Density (CDC)' while the notation and all later uses are 'CCD'; please make the abbreviation consistent.
  2. [Table 5.3] The table header says 'Dependent Variable: Provincial Human Poverty Index (HDI)'; this should read 'Provincial Human Development Index.'
  3. [Section 5.1.3, Figure 5.6 caption] The caption refers to 'Bulacan in 2014' but the data cover the 2013 election; please correct the year.
  4. [Section 5.1.2, Figure 5.4 caption] The caption says 'Mountain Province in 2022' while the text and table identify the highest CGC as Mountain Province 2007; please reconcile.
  5. [Throughout] There are several typographical errors, including 'holisistic' (Section 4.5.1), 'anectodal' (Section 3.4), 'disefranchisement' (Section 6.0.3), and 'Politican' (Table 4.3). A careful proofread is needed.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the network indicators are deterministic functions of pre-specified kinship edges, and the HDI, poverty, and party-hopping outcomes are external data not used to fit the indicators.

full rationale

The derivation chain is self-contained in the sense relevant to circularity. The four indicators (HHI, CGC, CCD, ACC) are closed-form functions of the reconstructed kinship network; the edge weights and node position weights are fixed a priori in Tables 4.4 and 4.5, and the Leiden community-detection resolution is fixed at 1 (Section 4.2.1). No socioeconomic outcome (HDI or poverty) is used to calibrate these weights, choose the community-detection parameters, or define any indicator. The HDI and poverty data are external (PSA, HDN) and are matched to the network metrics with a stated two-year lag (Section 4.5.2), so the LMM results in Section 5.3 are genuine associations between independently measured outcomes and network-derived regressors rather than fitted-input predictions. The algebraic equality between the two CGC formulas (Equations 2.4.2.1 and 2.4.2.2) is explicitly derived in the text and is correctly shown; it is a tautological reformulation, not a circular claim. The party-hopping finding is also non-circular: dynastic status is defined by simultaneous office-holding within a detected community, while the outcome is a separate variable indicating a change of party affiliation between successive terms (Section 4.1.3); the two definitions do not overlap. There are no load-bearing self-citations: all cited prior work (Querubin, Mendoza et al., Cruz et al., Traag et al., etc.) is external to the three thesis authors, and no uniqueness theorem or prior result by the same authors is invoked to force the choice of indicators. The most commonly raised concern—that CGC is computed over all politicians in the provincial network rather than restricted to clan members, so its interpretation as 'inequalities of influence between clan members' is strained (see the Mountain Province 2007 example in Section 5.1.2)—is a construct-validity limitation, not a circularity. CGC is not defined in terms of HDI, poverty, or clan-structure outcomes, and the HDI regression does not reduce to the definition of CGC. The paper's own scope and limitations section acknowledges the name-matching heuristic and the use of secondary data, but it does not conceal any input-output identity. Therefore the correct circularity finding is 0.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The analysis introduces no new entities like particles or forces. It does introduce four network-derived indicators, but these are mathematical summaries, not invented physical entities. The key assumptions are the kinship-by-name axiom, the Leiden-as-dynasty mapping, and the influence-weighting scheme. The free parameters (node weights, scalar factors, resolution) are not fitted to the outcome but are arbitrary, and the central results are not shown to be robust to them.

free parameters (3)
  • Position node weights = Councilor 2, Board Member 2, Vice Mayor 3, Vice Governor 3, Mayor 5, House Rep 5, Governor 5
    Chosen by hand in Section 4.2, Table 4.4. All four dynastic indicators depend on these weights.
  • Consanguinity scalar factors = 1.00 same middle+last, 0.75 same last, 0.50 matching middle+last, 0.25 same middle
    Table 4.5. Arbitrary scaling of edge weights; no external validation or sensitivity analysis.
  • Leiden resolution = 1
    Section 4.2.1. Community structure, and therefore all community-based indicators, changes with resolution; no robustness check reported.
assumptions (4)
  • domain assumption Matching surname or middle name within the same province implies kinship.
    Stated in Sections 1.3 and 4.2; false positives from common surnames are acknowledged but not quantified.
  • domain assumption Communities detected by the Leiden Algorithm correspond to actual political dynasties.
    Section 4.2.1; Leiden is a heuristic and the detected communities are treated as families throughout.
  • domain assumption The assigned node weights reflect relative political influence.
    Section 4.2; weights are 'arbitrary' by the authors' own statement, and all metrics inherit this assumption.
  • ad hoc to paper CGC measures inequality of influence between clan members.
    Definition 2.4.5 computes CGC over all n politicians in the province, not just within clans; the interpretive claim in the abstract and Section 4.3.2 goes beyond the definition.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The Families that Stay Together: A Network Analysis of Dynastic Power in Philippine Politics." pith.science (2026). https://pith.science/paper/WVUUQJRA

@misc{pith2026250521280,
  author       = {Pith},
  title        = {Pith review of: The Families that Stay Together: A Network Analysis of Dynastic Power in Philippine Politics},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/WVUUQJRA}},
  note         = {Machine review of arXiv:2505.21280}
}
read the original abstract

Dynasties have long dominated Philippine politics. Despite the theoretical consensus that dynastic rule erodes democratic accountability, there is limited empirical evidence establishing dynasties' true impact on development. A key challenge has been developing robust metrics for characterizing dynasties that facilitate meaningful comparisons across geographies and election cycles. Using election data from 2004 to 2022, we leverage methods from graph theory to develop four indicators to investigate dynastic evolution: Political Herfindahl-Hirschman Index (HHI), measuring dynastic power concentration; Centrality Gini Coefficient (CGC), reflecting inequalities of influence between clan members; Connected Component Density (CCD), representing the degree of inter-clan connection; and Average Community Connectivity (ACC), quantifying intra-clan cohesion. Our analysis reveals three key findings. Firstly, dynasties have grown stronger and more interconnected, occupying an increasing share of elected positions. Dominant clans have also remained tightly knit, but with great power imbalances between members. Secondly, we examine variations in party-hopping between dynastic and non-dynastic candidates. Across every election cycle, party-hopping rates are significantly higher (p<0.01) among dynastic candidates than non-dynasts, suggesting that the dominance of dynasties may weaken institutional trust within parties. Finally, applying a Linear Mixed Model regression, controlling for geographic random-effects and time fixed-effects, we observe that provinces with high power asymmetries within clans (high CGCs) and with deeply interconnected clans (high CCDs) record significantly lower (p<0.05) Human Development Index scores. These findings suggest that clan structure, rather than power concentration alone--may be the chief determinant of a ruling dynasty's developmental impact.

Figures

Figures reproduced from arXiv: 2505.21280 by the authors.

Figure 2.1
Figure 2.1. An Example of a Graph Let G be the graph illustrated in [PITH_FULL_IMAGE:figures/full_fig_p015_2_1.png] view at source ↗
Figure 2.2
Figure 2.2. An example of a network, color-coded by communities [PITH_FULL_IMAGE:figures/full_fig_p017_2_2.png] view at source ↗
Figure 2.3
Figure 2.3. In some algorithms, it is possible that the node 0 in (a) will [PITH_FULL_IMAGE:figures/full_fig_p019_2_3.png] view at source ↗
Figures from the paper (18 more)
Figure 4.1
Figure 4.1. Figure 4.1: Example of the Graph Weighting Scheme [PITH_FULL_IMAGE:figures/full_fig_p048_4_1.png]
Figure 4.2
Figure 4.2. Figure 4.2: The Largest Connected Component of Political Network in Samar [PITH_FULL_IMAGE:figures/full_fig_p050_4_2.png]
Figure 5.1
Figure 5.1. Figure 5.1: Boxplot of Political Herfindahl-Hirschman Index (HHI) [PITH_FULL_IMAGE:figures/full_fig_p069_5_1.png]
Figure 5.2
Figure 5.2. Figure 5.2: Networks with the Lowest and Highest Political HHI [PITH_FULL_IMAGE:figures/full_fig_p070_5_2.png]
Figure 5
Figure 5. Figure 5: illustrates the dynastic networks in Camarines Sur (2004) and [PITH_FULL_IMAGE:figures/full_fig_p071_5.png]
Figure 5.3
Figure 5.3. Figure 5.3: Boxplot of Centrality Gini Coefficient (CGC) [PITH_FULL_IMAGE:figures/full_fig_p072_5_3.png]
Figure 5
Figure 5. Figure 5: depicts the distribution of provincial CGCs from 2004 to 2022. [PITH_FULL_IMAGE:figures/full_fig_p073_5.png]
Figure 5.4
Figure 5.4. Figure 5.4: Networks with the Lowest and Highest Centrality Gini Coefficient [PITH_FULL_IMAGE:figures/full_fig_p073_5_4.png]
Figure 5.5
Figure 5.5. Figure 5.5: Boxplot of Connected Component Density (CCD) [PITH_FULL_IMAGE:figures/full_fig_p075_5_5.png]
Figure 5.6
Figure 5.6. Figure 5.6: Networks with the Lowest and Highest Connected Component [PITH_FULL_IMAGE:figures/full_fig_p076_5_6.png]
Figure 5.7
Figure 5.7. Figure 5.7: Giant Component of the Network in Maguindanao (2022) [PITH_FULL_IMAGE:figures/full_fig_p078_5_7.png]
Figure 5.8
Figure 5.8. Figure 5.8: Boxplot of Average Community Connectivity (ACC) [PITH_FULL_IMAGE:figures/full_fig_p079_5_8.png]
Figure 5.9
Figure 5.9. Figure 5.9: Networks with the Lowest and Highest Average Community Con [PITH_FULL_IMAGE:figures/full_fig_p080_5_9.png]
Figure 5
Figure 5. Figure 5: shows provinces which yielded the highest and lowest ACC. [PITH_FULL_IMAGE:figures/full_fig_p081_5.png]
Figure 5.10
Figure 5.10. Figure 5.10: Proportion of Dynastic and Non-Dynastic Politicians by Elec [PITH_FULL_IMAGE:figures/full_fig_p083_5_10.png]
Figure 5.11
Figure 5.11. Figure 5.11: Boxplot of Party Hopping Rate per Dynastic Status [PITH_FULL_IMAGE:figures/full_fig_p084_5_11.png]
Figure 5.12
Figure 5.12. Figure 5.12: Violin Plot of Average Party-Dynasty Overlap across election [PITH_FULL_IMAGE:figures/full_fig_p085_5_12.png]
Figure 5.13
Figure 5.13. Figure 5.13: Distribution of Poverty Incidences (POV) per electoral year [PITH_FULL_IMAGE:figures/full_fig_p095_5_13.png]

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

43 extracted references · 40 canonical work pages

  1. [1]

    Mea- suring political dynasties in Metro Manila

    Romeo T. Balanquit, Lianca O. Coronel, and Jose Y. Yambao. “Mea- suring political dynasties in Metro Manila”. In: Philippine Review of Economics (Online ISSN 2984-8156) 54.1 (Nov. 2, 2017). Number: 1, pp. 120–137. issn: 2984-8156. url: https://pre.econ.upd.edu.ph/ index.php/pre/article/view/952 (visited on 03/10/2025)

    work page 2017

  2. [2]

    Going beyond Crosscoun- try Averages: Growth, Inequality and Poverty Reduction in the Philip- pines

    Arsenio M. Balisacan and Nobuhiko Fuwa. “Going beyond Crosscoun- try Averages: Growth, Inequality and Poverty Reduction in the Philip- pines”. In: World Development 32.11 (Nov. 1, 2004), pp. 1891–1907. issn: 0305-750X. doi: 10 . 1016 / j . worlddev . 2004 . 05 . 010. url: https://www.sciencedirect.com/science/article/pii/S0305750X04001408 (visited on 03/10/2025)

    work page 2004

  3. [3]

    35 (Bangsamoro Electoral Code of 2022)

    Bangsamoro Autonomy Act No. 35 (Bangsamoro Electoral Code of 2022). Official text, Bangsamoro Parliament. 2022

    work page 2022

  4. [4]

    Inequality in democracy: Insights from an empirical analysis of political dynasties in the 15th Philippine Congress

    Edsel Beja Jr et al. Inequality in democracy: Insights from an empirical analysis of political dynasties in the 15th Philippine Congress . July 15,

    work page

  5. [5]

    Fundamentals of graph theory

    Allan Bickle. Fundamentals of graph theory. en. Pure and Applied Un- dergraduate Texts. Providence, RI: American Mathematical Society, May 2020

    work page 2020

  6. [6]

    An Em- pirical Analysis of Vote Buying Among the Poor: Evidence from Elec- 112 tions in the Philippines (forthcoming in Southeast Asia Research)

    Tristan Canare, Ronald Mendoza, and Mario Antonio Lopez. “An Em- pirical Analysis of Vote Buying Among the Poor: Evidence from Elec- 112 tions in the Philippines (forthcoming in Southeast Asia Research)”. In: (Feb. 2018)

    work page 2018

  7. [7]

    Ateneo Policy Center Political Dynasties Dataset

    Ateneo Policy Center. Ateneo Policy Center Political Dynasties Dataset

    work page

  8. [8]

    Politician Family Networks and Electoral Outcomes: Evidence from the Philippines

    Cesi Cruz, Julien Labonne, and Pablo Querub ´ ın. “Politician Family Networks and Electoral Outcomes: Evidence from the Philippines”. In: American Economic Review 107.10 (Oct. 2017), pp. 3006–37. doi: 10.1257/aer.20150343 . url: https://www.aeaweb.org/articles? id=10.1257/aer.20150343

    work page doi:10.1257/aer.20150343 2017

Show all 43 references
  1. [9]

    Corrup- tion risk and political dynasties: exploring the links using public pro- curement data in the Philippines

    Daniel Bruno Davis, Ronald U. Mendoza, and Jurel K. Yap. “Corrup- tion risk and political dynasties: exploring the links using public pro- curement data in the Philippines”. In: Economics of Governance 25.1 (Mar. 1, 2024), pp. 81–109. issn: 1435-8131. doi: 10.1007/s10101- 023-...

    2024 doi

  2. [10]

    Network Analysis for Economics and Finance: An Application to Firm Ownership

    Janina Engel, Michela Nardo, and Michela Rancan. “Network Analysis for Economics and Finance: An Application to Firm Ownership”. In: Data Science for Economics and Finance: Methodologies and Applica- tions. Ed. by Sergio Consoli, Diego Reforgiato Recupero, and Michaela Saisana...

    2021 doi

  3. [11]

    Police nab suspect in ambush-slay of Mt

    Cecille Suerte Felipe Bebot Sison Jr. Police nab suspect in ambush-slay of Mt. Province mayor . Feb. 2011. url: https://www.philstar.com/ nation/2011/02/18/658032/police-nab-suspect-ambush-slay- mt-province-mayor

    2011

  4. [12]

    Understanding layered dominance of political dynasties in India: A de-hyphenated reading of dynastic representation and dynasty-led parties

    Ambar Kumar Ghosh. “Understanding layered dominance of political dynasties in India: A de-hyphenated reading of dynastic representation and dynasty-led parties”. In: Asian Journal of Comparative Politics 8.3 (Sept. 1, 2023). Publisher: SAGE Publications, pp. 727–747. issn: 205...

    2023 doi

  5. [13]

    Swati Goswami, C. A. Murthy, and Asit K. Das. Sparsity Measure of a Network Graph: Gini Index . 2016. arXiv: 1612.07074 [cs.DM]. url: https://arxiv.org/abs/1612.07074

    2016 arXiv

  6. [14]

    The Lanao Sultanate in the 17th Century Zak¯ at System With Special Reference to the Islamic Perspectives of Al-M¯ award ¯ ı

    Sohayle Hadji et al. “The Lanao Sultanate in the 17th Century Zak¯ at System With Special Reference to the Islamic Perspectives of Al-M¯ award ¯ ı”. In: (Oct. 2020), p. 2018

    2020

  7. [15]

    National power and the structure of foreign trade

    Albert O Hirschman. National power and the structure of foreign trade. The Politics of the international economy. Berkeley, CA: University of California Press, Feb. 1981

    1981

  8. [16]

    Political dynas- ties, term limits and female political representation: Evidence from the Philippines

    Julien Labonne, Sahar Parsa, and Pablo Querubin. “Political dynas- ties, term limits and female political representation: Evidence from the Philippines”. In: Journal of Economic Behavior & Organization 182 (Feb. 1, 2021), pp. 212–228. issn: 0167-2681. doi: 10.1016/j.jebo. 114 ...

    2021 doi

  9. [17]

    AN ACT PROHIBITING THE ESTABLISHMENT OF POLITICAL DYNASTIES

    Panfilo Lacson. AN ACT PROHIBITING THE ESTABLISHMENT OF POLITICAL DYNASTIES . July 2019. url: https : / / legacy . senate.gov.ph/lisdata/3024627075!.pdf

    2019

  10. [18]

    As- sessing the Relationship of Human Development Index (HDI) and Gov- ernment Expenditure on Health and Education in Selected ASEAN Countries

    Danielle Ann Lantion, Gabrielle Mus˜ ngi, and Ronaldo Cabauatan. “As- sessing the Relationship of Human Development Index (HDI) and Gov- ernment Expenditure on Health and Education in Selected ASEAN Countries”. In: International Journal of Social and Management Stud- ies 4.6 (...

    2023 doi

  11. [19]

    Ampatuans, Ecleos, Sinsuats, Midtimbangs unrivalled in turfs

    Vino Lucero. Ampatuans, Ecleos, Sinsuats, Midtimbangs unrivalled in turfs. en-US. May 2016. url: http : / / pcij . org / 2016 / 05 / 04 / ampatuans-ecleos-sinsuatsbrmidtimbangs-unrivalled-in-turfs/

    2016

  12. [20]

    Political dynasties and poverty: measurement and evidence of linkages in the Philippines

    Ronald Mendoza et al. “Political dynasties and poverty: measurement and evidence of linkages in the Philippines”. In: Ateneo School of Gov- ernment Publications (Apr. 1, 2016). url: https://archium.ateneo. edu/asog-pubs/63

    2016

  13. [21]

    Mendoza, Miann Banaag, and Michael Henry Yusingco

    Ronald U. Mendoza, Miann Banaag, and Michael Henry Yusingco. Term Limits and Political Dynasties: Unpacking the Links . Rochester, NY, Mar. 20, 2019. doi: 10 . 2139 / ssrn . 3356437. url: https : / / papers.ssrn.com/abstract=3356437 (visited on 04/10/2025)

    2019

  14. [22]

    Mendoza, Jan Fredrick Cruz, and David Barua Yap II

    Ronald U. Mendoza, Jan Fredrick Cruz, and David Barua Yap II. Polit- ical Party Switching: It’s More Fun in the Philippines . Rochester, NY, 115 Sept. 23, 2014. doi: 10.2139/ssrn.2492913 . url: https://papers. ssrn.com/abstract=2492913 (visited on 04/11/2025)

    2014 doi

  15. [23]

    Mendoza, Joshua Hiwatig, and Miann Banaag

    Ronald U. Mendoza, Joshua Hiwatig, and Miann Banaag. Dynastic Political Networks: Insights from the Case of Western Samar, Philip- pines. Rochester, NY, July 16, 2020. doi: 10 . 2139 / ssrn . 3652960. url: https : / / papers . ssrn . com / abstract = 3652960(visited on 11/17/2024)

    2020

  16. [24]

    Mendoza, Leonardo M

    Ronald U. Mendoza, Leonardo M. Jaminola, and Jurel Yap. From Fat to Obese: Political Dynasties after the 2019 Midterm Elections . Rochester, NY, Sept. 1, 2019. doi: 10 . 2139 / ssrn . 3449201. url: https://papers.ssrn.com/abstract=3449201 (visited on 03/11/2025)

    2019

  17. [25]

    Political Dynasties and Poverty: Resolv- ing the ’Chicken or the Egg’ Question

    Ronald U. Mendoza et al. “Political Dynasties and Poverty: Resolv- ing the ’Chicken or the Egg’ Question”. In: SSRN Electronic Journal (2013). issn: 1556-5068. doi: 10 . 2139 / ssrn . 2292277. url: http : //www.ssrn.com/abstract=2292277 (visited on 11/17/2024)

    2013

  18. [26]

    Political Dynasties and Terrorism: An Em- pirical Analysis Using Data on the Philippines

    Ronald U. Mendoza et al. “Political Dynasties and Terrorism: An Em- pirical Analysis Using Data on the Philippines”. In: Asian Journal of Peacebuilding 10.2 (Nov. 30, 2022), pp. 435–459. issn: 22882693, 22882707. doi: 10 . 18588 / 202210 . 00a266. url: https : / / kiss . kstud...

    2022

  19. [27]

    Political dynasties, business, and poverty in the Philippines

    Ronald U. Mendoza et al. “Political dynasties, business, and poverty in the Philippines”. In: Journal of Government and Economics 7 (Sept. 1, 2022), p. 100051. issn: 2667-3193. doi: 10.1016/j.jge.2022.100051. 116 url: https : / / www . sciencedirect . com / science / article /...

    2022

  20. [28]

    8 in every 10 district reps be- long to dynasties

    Guinevere Latoza Miranda Maujerie. 8 in every 10 district reps be- long to dynasties. More than half are reelectionists in 2025 . PCIJ.org. Oct. 26, 2024. url: http://pcij.org/2024/10/26/lower- house- district - representatives - political - dynasties - reelection/ (visited on...

    2025

  21. [29]

    Philippine Human Development Re- port

    Human Development Network PH. Philippine Human Development Re- port. 2022

    2022

  22. [30]

    Political Parties, Family Dynasties, and the Budget Surplus Trap: Addressing the Public Goods Deficit in the Philippines

    Hannah Pimentel. Political Parties, Family Dynasties, and the Budget Surplus Trap: Addressing the Public Goods Deficit in the Philippines . Nov. 21, 2024. url: https : / / blogs . lse . ac . uk / seac / 2024 / 11 / 21 / political - parties - family - dynasties - and - the - bu...

    2024

  23. [31]

    Political Reform and Elite Persistence: Term Lim- its and Political Dynasties in the Philippines

    Pablo Querubin. Political Reform and Elite Persistence: Term Lim- its and Political Dynasties in the Philippines . Rochester, NY, 2012. url: https : / / papers . ssrn . com / abstract = 2108036(visited on 11/18/2024)

    2012

  24. [32]

    10755: An Act Strengthening the Sangguniang Ka- bataan (SK) Reform Act of 2015

    Republic Act No. 10755: An Act Strengthening the Sangguniang Ka- bataan (SK) Reform Act of 2015 . Official Gazette of the Republic of the Philippines. 2015

    2015

  25. [33]

    Can Social Protection Weaken Clientelism? Con- sidering Conditional Cash Transfers as Political Reform in the Philip- 117 pines

    Arun R. Swamy. “Can Social Protection Weaken Clientelism? Con- sidering Conditional Cash Transfers as Political Reform in the Philip- 117 pines”. In: Journal of Current Southeast Asian Affairs 35.1 (2016), pp. 59–90. doi: 10.1177/186810341603500103. eprint: https://doi. org / ...

    2016 doi

  26. [34]

    Political dynasties in the Philip- pines: Persistent patterns, perennial problems

    Teresa Tadem and Eduardo Tadem. “Political dynasties in the Philip- pines: Persistent patterns, perennial problems”. In: South East Asia Research 24 (July 2016). doi: 10.1177/0967828X16659730

    2016 doi

  27. [35]

    Mapping the Philip- pines’ Defective Democracy

    Julio C. Teehankee and Cleo Anne A. Calimbahin. “Mapping the Philip- pines’ Defective Democracy”. In: Asian Affairs: An American Review 47.2 (2020), pp. 97–125. doi: 10.1080/00927678.2019.1702801

    2020

  28. [36]

    Official text

    The 1987 Constitution of the Republic of the Philippines . Official text. 1987

    1987

  29. [37]

    From Louvain to Leiden: guaranteeing well-connected communities

    V. A. Traag, L. Waltman, and N. J. van Eck. “From Louvain to Leiden: guaranteeing well-connected communities”. In: Scientific Reports 9.1 (Mar. 2019). issn: 2045-2322. doi: 10.1038/s41598- 019- 41695- z. url: http://dx.doi.org/10.1038/s41598-019-41695-z

    2019 doi

  30. [38]

    Variability and Mutability

    “Variability and Mutability”. In: Journal of the Royal Statistical Soci- ety 76.6 (Dec. 2018), pp. 619–622. issn: 0952-8385. doi: 10.1111/j. 2397- 2335.1913.tb03065.x. eprint: https://academic.oup.com/ jrsssa/article- pdf/76/6/619/49683089/jrsssa\_76\_6\_619. pdf. url: https:/...

    2018

  31. [39]

    Political Dynasties and Human Devel- opment Investments: Evidence of Linkage from Rizal Province, Philip- 118 pines

    John Emmanuel B. Villanueva. “Political Dynasties and Human Devel- opment Investments: Evidence of Linkage from Rizal Province, Philip- 118 pines”. In: Philippine Journal of Public Administration 64.2 (Mar. 14, 2022). Number: 2, pp. 90–126.issn: 3028-1296. url: https://journal...

    2022

  32. [40]

    Politics of Poverty Governance: an Introduction

    Zhongyuan Wang and Sujian Guo. “Politics of Poverty Governance: an Introduction”. In: Journal of Chinese Political Science 27 (June 2022). doi: 10.1007/s11366-022-09804-4

    2022 doi

  33. [41]

    Network analysis literacy

    Katharina A Zweig. Network analysis literacy. en. 1st ed. Lecture Notes in Social Networks. Vienna, Austria: Springer, Aug. 2014. 119 Appendices 120 Appendix A Appendix A.0.1 Linear Regression Trend Analysis Figure A.1: Trend Analysis of Political Herfindahl-Hirschman Index Fi...

    2014

  34. [2012]

    url: https://mpra.ub.uni-muenchen.de/40104/ (visited on 03/06/2025)

    2025

  35. [2016]

    inclusivedemocracy

    url: https : / / www . inclusivedemocracy . ph / data - and - infographics

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.