Income Segregation Analysis in Limited‐Data Contexts: A Methodology Based on Iterative Proportional Fitting
نویسندگان
چکیده
Since the 1950s, researchers in Urban Geography have created multiple instruments for measuring income segregation. However, computation of such indexes requires availability data and population distribution small areal units. This approach is problematic countries cities where a government's decennial census does not collect or report small-enough units to capture variability within neighborhood. To address this gap, we use Iterative Proportional Fitting (IPF) combine neighborhood-level with an individual-level survey then estimate area discrete continuous distributions each area. We show that it possible compute segregation indices based solely on estimated probability without need generate full synthetic obtain integer counts. test our empirical method case Mexican cities, which global local are computed bootstrapped confidence intervals. The major contributions article twofold. First, uses income-data generation measure Secondly, demonstrates linkage between measures feasibility computing them directly from same IPF income.
منابع مشابه
Symmetric Iterative Proportional Fitting
This supplement consists of several parts that refer directly to specific topics in the paper: A Proof of Equation (2) B Proof of Lemma 3.1 (Symmetric biproportional fit) C Technical details on why ”local affinity” is sufficient in Section 4.1 D Proof of Theorem 4.2 (Convergence of PSIPF) E Proof of Lemma 4.4 (L1-monotony) F Proof of Lemma 4.5 (Volume bounds) G Proof of Lemma 4.6 (Limit points)...
متن کاملSymmetric Iterative Proportional Fitting
Iterative Proportional Fitting (IPF) generates from an input matrix W a sequence of matrices that converges, under certain conditions, to a specific limit matrix Ŵ . This limit is the relative-entropy nearest solution to W among all matrices of prescribed row marginals r and column marginals c. We prove this known fact by a novel strategy that contributes a pure algorithmic intuition. Then we f...
متن کاملPutting Iterative Proportional Fitting on the Researcher’s Desk
...................................................................................................................................ii
متن کاملOn Improving the Efficiency of the Iterative Proportional Fitting Procedure
Iterative proportional fitting (IPF) on junction trees is an important tool for learning in graphical models. We identify the propagation and IPF updates on the junction tree as fixed point equations of a single constrained entropy maximization problem. This allows a more efficient message updating protocol than the well known effective IPF of Jiroušek and Přeučil (1995). When the junction tree...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Geographical Analysis
سال: 2023
ISSN: ['0016-7363', '1538-4632']
DOI: https://doi.org/10.1111/gean.12367