Linganisha mbinu

	Distributive Politics Analysis	Patronage Network Analysis	Vote Buying Analysis
Nyanja	Political Economy	Political Economy	Political Economy
Familia	Regression model	Process / pipeline	Regression model
Mwaka wa asili	1986	1972	2008
Mwanzilishi	Gary Cox & Mathew McCubbins (core); Avinash Dixit & John Londregan (swing)	James C. Scott; S. N. Eisenstadt & Luis Roniger	Simeon Nichter; Ezequiel Gonzalez-Ocantos et al.
Aina	Regression analysis of electorally motivated spending allocation	Network-analytic pipeline for clientelist structures	Measurement-and-targeting regression model
Chanzo asilia	Cox, G. W., & McCubbins, M. D. (1986). Electoral Politics as a Redistributive Game. The Journal of Politics, 48(2), 370-389.	Scott, J. C. (1972). Patron-Client Politics and Political Change in Southeast Asia. American Political Science Review, 66(1), 91-113.	Nichter, S. (2008). Vote Buying or Turnout Buying? Machine Politics and the Secret Ballot. American Political Science Review, 102(1), 19-31.
Majina mbadala	Electoral Targeting Analysis, Swing versus Core Voter Analysis, Pork Barrel Politics Analysis, Tactical Redistribution Analysis	Patron-Client Network Analysis, Patronage Pyramid Analysis, Brokerage Network Analysis, Clientelist Network Mapping	Electoral Clientelism Measurement, Turnout Buying Analysis, Vote-Buying Targeting Model, List-Experiment Vote Buying
Zinazohusiana	3	3	3
Muhtasari	Distributive politics analysis studies how governments allocate divisible public spending — grants, transfers, projects, and pork — across districts and groups to maximize electoral support. Two competing theories anchor the field. The swing-voter logic, formalized by Avinash Dixit and John Londregan in 1996 (building on Lindbeck and Weibull), holds that parties target marginal districts where votes are most responsive to spending. The core-voter logic, associated with Gary Cox and Mathew McCubbins's 1986 redistributive-game model, holds that parties instead reward loyal supporters whose preferences and reliability they know best. The empirical method is a regression of observed transfers on electoral characteristics — district marginality and partisan alignment — to test which targeting strategy the data reveal.	Patronage network analysis is a relational pipeline for representing patron-client politics as a directed network and measuring its structure with the tools of social network analysis. Building on James C. Scott's 1972 account of patron-client politics in Southeast Asia and Eisenstadt and Roniger's 1984 comparative study of clientelism and trust, the approach treats the vertical, asymmetric bond between a powerful patron and a dependent client — typically mediated by brokers — as the elementary tie. By coding who is connected to whom, in which direction, and with what resource content, the analyst can compute centrality, brokerage, and structural-hole measures to reveal the pyramidal architecture through which protection and resources flow down and loyalty and support flow up.	Vote buying analysis is the measurement-and-modeling toolkit for studying the distribution of private goods or cash in exchange for electoral support. Two problems define the field. First, who is being paid: Simeon Nichter's 2008 article showed that machines frequently engage in turnout buying — paying their own already-loyal supporters to show up — rather than the classic vote buying of swing voters, a distinction with sharp implications for who gets targeted. Second, how to measure something respondents are reluctant to admit: Gonzalez-Ocantos and colleagues' 2012 study demonstrated that direct survey questions sharply understate vote buying because of social-desirability bias and that list experiments recover far higher, more credible prevalence. Vote buying analysis combines such debiased measurement with regression models of targeting.