A simulation model of Mexican internal migration flows: empirical application of a spatial interaction model

"In this paper spatial interaction theory is challenged in order to test if it is suitable to support the design and construction of an operative model of the Mexican internal migration flows. The main conceptual and operative aspects of the model are presented, the design and model building process is explained, the results of the calibration analysis are examined and a simulation exercise of migration policy evaluation is undertaken. The operative migration model presented in this paper seems useful to analyze and evaluate numerous migration policies, which suggest that spatial interaction theory offers a promising conceptual and operative foundation to analyze internal migration flows in Mexico." (EXCERPT)     

Frequency of monotonicity failure under Instant Runoff Voting: estimates based on a spatial model of elections

It has long been recognized that Instant Runoff Voting (IRV) suffers from a defect known as nonmonotonicity, wherein increasing support for a candidate among a subset of voters may adversely affect that candidate’s election outcome. The expected frequency of this type of behavior, however, remains an open and important question, and limited access to detailed election data makes it difficult to resolve empirically. In this paper, we develop a spatial model of voting behavior to approach the question theoretically. We conclude that monotonicity failures in three-candidate IRV elections may be much more prevalent than widely presumed (results suggest a lower bound estimate of 15 % for competitive elections). In light of these results, those seeking to implement a fairer multi-candidate election system should be wary of adopting IRV.     

A covariance structure model for the analysis of spatial differences in Mexican mortality

"This article examines some of the possible determinants of spatial mortality differentials in Mexico, on the basis of [a] path analytical model with latent variables." (SUMMARY IN ENG)     

A spatial model of legislative voting with perceptual error

This paper presents a unidimensional spatial model of voting in which members of Congress vote based on an imprecise perception of roll-call alternatives. The model is applied to the Senate roll-call votes of 1977 to estimate the ideal points of the senators, and to examine the role of a liberal-conservative dimension in describing votes on economic issues relative to social issues. In light of the spatial model, the paper argues that “standard” models of roll-call voting are not based on a theory of choice, and hence, that it is difficult to interpret their results. Alternatives to standard models, based on the spatial model, are developed and are used to analyze the role of ideology in deciding a specific economic issue: coal strip-mining.     

A test of the predictive dimensions model in spatial voting theory

We model correlated voter-candidate issue data within the framework of the Enelow-Hinich spatial model of predictive dimensions. The empirical consequences of this model of the issue data are surprising and allow for an indirect test of the Enelow-Hinich spatial model. The central prediction of the correlated data model we construct, which depends critically on the underlying spatial model, is tested with issue data from the 1980 NES pre-election interview. The test results are highly supportive of the model's predictions. We conclude both that the spatial model of predictive dimensions is empirically supported and that candidate spatial locations estimated by the model are not an artifact of correlated voter-candidate issue data.     

An analysis of the neighborhood impacts of a mortgage assistance program: A spatial hedonic model

Down payment or closing cost assistance is an effective program in addressing the wealth constraints of low‐and moderate‐income homebuyers. However, the spillover effect of such programs on the neighborhood is unknown. This paper estimates the impact of the City of Dallas Mortgage Assistance Program (MAP) on nearby home values using a hedonic model of home sales from 1990 to 2006. We define neighborhoods of 1,000 feet around each sale and estimate the average differences in sales prices between neighborhoods with various numbers of MAP properties before and after their appearance. We find that MAP properties tend to locate in neighborhoods with lower property values; however, unless a concentration of MAP properties forms, the infusion of MAP properties has little detrimental impact on neighboring property values. Moreover, low concentration of MAP properties has a modest positive impact on surrounding property values. © 2010 by the Association for Public Policy Analysis and Management.     

Multiparty electoral competition in the Netherlands and Germany: A model based on multinomial probit

A typical assumption of electoral models of party competition is that parties adopt policy positions so as to maximize expected vote share. Here we use Euro-barometer survey data and European elite-study data from 1979 for the Netherlands and Germany to construct a stochastic model of voter response, based on multinomial probit estimation. For each of these countries, we estimate a pure spatial electoral voting model and a joint spatial model. The latter model also includes individual voter and demographic characteristics. The pure spatial models for the two countries quite accurately described the electoral response as a stochastic function of party positions. We use these models to perform a thought experiment so as to estimate the expected vote maximizing party positions. We go on to propose a model of internal party decision-making based both on pre-election electoral estimation and post-election coalition bargaining. This model suggests why the various parties in the period in question did not adopt vote maximizing positions. We argue that maximizing expected vote will not, in general, be a rational party strategy in multiparty political systems which are based on proportional representation.     

Eligibility for the Medicare buy-in programs, based on a survey of income and program participation simulation.

Medicare buy-in programs are designed to reduce out-of-pocket expenses of beneficiaries with modest income and assets. This article provides estimates of the size of the Medicare beneficiary population eligible for the Qualified Medicare Beneficiary (QMB) program, the Specified Low-Income Medicare Beneficiary (SLMB) program, and the Qualified Individual-1 (QI-1) program. The buy-in programs use the same resource limits (twice those used in the Supplemental Security Income (SSI) program) but different thresholds for determining income eligibility. The QMB program uses 100 percent of the poverty line as the cutoff, QI-1 covers persons above 120 percent but at or below 135 percent of the poverty line, and the SLMB program is in between. Making informed judgments about the rate of participation in the buy-in programs and the need for outreach requires an accurate estimate of the size of the eligible population. If that population is underestimated, policymakers might come to unduly optimistic conclusions about current buy-in participation. In contrast, an overestimate may make current participation seem too low. If policymakers react to an upwardly biased estimate of the eligible population by increasing outreach, they are bound to be disappointed by the results of that effort. Estimates of the eligible population from past studies of the QMB and SLMB programs range from 5.1 million to 9.1 million. In the absence of new information, it is difficult to judge the accuracy of those estimates because the methodologies had substantial shortcomings that might bias the results. The most common shortcomings include the lack of high-quality, monthly income data and the lack of information on assets from the same data file that was used to estimate participation and income eligibility for Medicare. The current study uses the most recently available (as of August 2000) Survey of Income and Program Participation (SIPP) file that is matched to the Social Security Administration's (SSA's) administrative records. The data file covers 1995 information. Estimates were also obtained using 1991 data to assess the sensitivity of eligibility estimates to the year chosen. The SIPP has several major advantages over other data sources because it contains relevant, high-quality information on both income and assets for establishing financial eligibility for the buy-in programs. First, the SIPP collects detailed and conceptually appropriate information on monthly, rather than annual, income and therefore has more complete information about income than do other surveys. As a result, SIPP-based estimates of poverty are substantially lower than estimates based on the Current Population Survey. Second, the SIPP also collects information on assets at the individual level. Thus, the survey provides enough detail to measure the major income and asset exclusions directly. Finally, the SIPP data are matched to SSA administrative records: Medicare eligibility can therefore be accurately measured, and self-reported data on Social Security and SSI benefits can be replaced with more accurate monthly information. Our 1995 simulation estimates that approximately 4.8 million persons in the U.S. noninstitutionalized population were eligible for the QMB program and an additional 1.6 million for the SLMB program. The total--roughly 6.5 million--is within the range of estimates from past studies but is closer to the lower end, suggesting that the eligible population is smaller than was previously believed. When the estimated QI-1 eligible population of 0.9 million is added, the total for the three buy-in programs is 7.4 million. Because the QI-1 program did not exist in 1995, only the estimated 6.5 million QMBs and SLMBs would actually have been eligible to receive benefits. The 7.4 million figure represents the 1995 Medicare beneficiaries who would be eligible for buy-in under program rules for 2000. Adjusting that number to account for increases in the Medicare population between 1995 and 1999 yields an estimated eligible population of 7.8 million in 1999. Compared with other elderly Medicare recipients, eligible elderly QMBs and SLMBs have poorer health, more functional limitations, and higher rates of health care use. Thus, not only are their income resources relatively limited, but their need for potentially expensive medical care is also greater. Similar differences were not found in health, functional limitations, and health care use among disabled participants in the QMB and SLMB programs. Our estimates imply that about 2.5 million noninstitutionalized individuals were eligible for but not enrolled in the QMB and SLMB programs in 1999. That finding suggests that fewer eligibles may be available for targeting by outreach efforts than was previously believed. Outreach may be more difficult than it would be with a larger eligible population. (ABSTRACT TRUNCATED)     

A model for disaggregating political change

We present a model for identifying the components of aggregate change in an electorate between two points in time. When the electorate is constant in size, change in the mean opinion disaggregates into two components: conversion among those who continue to participate in the electorate (Stayers), and replacement of those who drop out of the electorate at Time₁ (Dropouts) by Newcomers to the electorate at Time₂. We add to this simple formulation the possibility of variation in the size of the electorate. When an electorate expands, the model includes a mobilization term to accommodate the fact that there are more Newcomers at Time₂ than Dropouts at Time₁. When an electorate shrinks in size, the demobilization term reflects the fact that Newcomers as a group are smaller than Dropouts. The model includes appropriate weights for each component so that the change in opinion (or any other aggregate characteristic in the electorate) can be allocated across the three components. We apply the model to Iowa caucus attenders in both parties between 1984 and 1988, and we suggest that the model can be also productively applied to a variety of contexts besides nomination politics, where fluctuations in the size of electorates are significant.Ronald B. Rapoport. College of William and Mary.     

A forecasting model for state expenditures

In this study, the median voter model is applied to the problem of predicting state public expenditures in four major categories: human services, elementary and secondary education, higher education, and health services. Demand functions for public services are derived within a formal utility-maximizing model. The resulting model is estimated using time-series data for a representative state and the model is used to predict state spending for fiscal year 1985. The results of the estimation are consistent with the predictions of the median voter model and the forecasts correspond closely to those made by the State Bureau of the Budget. In contrast, a naive autoregressive model of state spending performs poorly.     

Action research: A model for organizational learning

Traditionally, social research has relied on systematic methods to control variation in the collection of data in order to validate relationships observed among the social phenomena under study. Ironically, many critical problems in the actual operation of public organizations are not amenable to such rigorous controls. An alternative mode of analysis, action research, may prove more useful since it takes into account the dynamic nature of organizations, emphasizing the production of valid information, the element of Fee and informed choice by organization members, and the goal of engendering commitment to action by those involved. Simulated operations designed to enhance the performance of public agencies in unforeseen emergencies provide a setting in which to evaluate the effectiveness of action research as a tool for organizational problem-solving.     

A policy-selection/ goal-formulation model for public systems

This paper attempts to present an analytical framework of analysis of problems relating to public systems. Current optimization models, which originated in the private sector, are not adequate to handle the complexity of the decision making processes in public policy analysis. The proposed model aims at lessening ideological debates over statements of goals, and it emphasizes policy selection through goal redefinitions where both goals and policies are formulated simultaneously. The model is based on an iterative process where consensus over policies is arrived at between the policy maker and the constituents of the public system. The principal feature of the model is that it incorporates political debates and bargains, and provides for the development of insight.     

A critique of quasiexperimental and statistical controils for measuring program effects: Application to urban growth control

Most studies evaluating the effect on housing prices of regulatory programs for controlling urban growth use econometric methods (hedonic price models) without considering the research-design aspects of the task. The article examines the strengths and weaknesses of several quasiexperimental and statistical methods for measuring the effect of growth-control programs, using criteria extracted from theory. The methodological critique is tested empirically by comparing several methods using data from the growth-control community of Davis, California and from three comparison communities. The empirical test demonstrates that different research designs can produce, large differences in the magnitudes of estimated effects, and that adding statistical controls to quasiexperimental controls permits the detection of smaller effects.