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Below results based on the criteria 'Random Effects models'
Total number of records returned: 5

1
Paper
A Random Effects Approach to Legislative Ideal Point Estimation
Bailey, Michael

Uploaded 04-21-1998
Keywords ideal points
random effects models
Bayesian estimation
em algorithm
Abstract Conventionally, scholars use either standard probit/logit techniques or fixed-effect methods to estimate legislative ideal points. However, these methods are unsatisfactory when a limited number of votes are available: standard probit/logit methods are poorly equipped to handle multiple votes and fixed-effect models disregard serious ``incidental parameter'' problems. In this paper I present an alternative approach that moves beyond single-vote probit/logit analysis without requiring the large number of votes needed for fixed-effects models. The method is based on a random effects, panel logit framework that models ideal points as stochastic functions of legislator characteristics. Monte Carlo results and an application to trade politics demonstrate the practical usefulness of the method.

2
Paper
Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data
Bell, Andrew
Jones, Kelvyn

Uploaded 09-11-2013
Keywords Random Effects models
Fixed Effects models
Random coefficient models
Mundlak formulation
Fixed effects vector decomposition
Hausman test
Endogeneity
Panel Data
Time-Series Cross-Sectional Data
Abstract This article challenges Fixed Effects (FE) modelling as the ‘default’ for time-series-cross-sectional and panel data. Understanding differences between within- and between-effects is crucial when choosing modelling strategies. The downside of Random Effects (RE) modelling – correlated lower-level covariates and higher-level residuals – is omitted-variable bias, solvable with Mundlak’s (1978a) formulation. Consequently, RE can provide everything FE promises and more, and this is confirmed by Monte-Carlo simulations, which additionally show problems with another alternative, Plümper and Troeger’s Fixed Effects Vector Decomposition method, when data are unbalanced. As well as being able to model time-invariant variables, RE is readily extendable, with random coefficients, cross-level interactions, and complex variance functions. An empirical example shows that disregarding these extensions can produce misleading results. We argue not simply for technical solutions to endogeneity, but for the substantive importance of context and heterogeneity, modelled using RE. The implications extend beyond political science, to all multilevel datasets.

3
Paper
Does Democracy Reduce Infant Mortality? Evidence from New Data, for 181 Countries between 1970 and 2009
Ramos, Antonio Pedro

Uploaded 07-28-2014
Keywords Regime Type
Democratization
Child Mortality
Panel Data
Longitudinal Models
Random Effects Models
Abstract Which form of government is most responsive to its citizens' needs? This paper focuses on child mortality to investigate the causal link between political regimes and welfare. I use a new data set that includes 181 countries between 1970 and 2008, with no missing observations and less measurement error than has been previously available. While new data suggests that democracies are associated with better health outcomes, it remains unclear whether this is due to a causal effect of regime type on health. I argue that the best way to detect the effects of democracy on child mortality is to investigate whether democratization episodes were followed by significant reductions in child mortality. Child mortality in most countries has declined in the last forty years. My results indicate that democratic transitions accelerate the downward trend in child mortality, especially in low income countries where mortality rates are typically high. Surprisingly, however, I also find that democratic transitions lead to short-term increases in child mortality for middle-income countries. This heterogeneity in the effects of democratic transitions has not been previously documented and calls for further research.

4
Paper
Does Democracy Reduce Infant Mortality? Evidence from New Data, for 181 Countries between 1970 and 2009
Ramos, Antonio Pedro

Uploaded 07-28-2014
Keywords Regime Type
Democratization
Child Mortality
Panel Data
Longitudinal Models
Random Effects Models
Hierarchical Models
Abstract Which form of government is most responsive to its citizens’ needs? This paper focuses on child mortality to investigate the causal link between political regimes and welfare. I use a new data set that includes 181 countries between 1970 and 2008, with no missing observations and less measurement error than has been previously available. While new data suggests that democracies are associated with better health outcomes, it remains unclear whether this is due to a causal effect of regime type on health. I argue that the best way to detect the effects of democracy on child mortality is to investigate whether democratization episodes were followed by significant reductions in child mortality. Child mortality in most countries has declined in the last forty years. My results indicate that democratic transitions accelerate the downward trend in child mortality, especially in low income countries where mortality rates are typically high. Surprisingly, however, I also find that democratic transitions lead to short-term increases in child mortality for middle-income countries. This heterogeneity in the effects of democratic transitions has not been previously documented and calls for further research.

5
Poster
Political Regimes and Infant Death: Democratization and Its Consequences for Infant Mortality, 1970-2008.
Ramos, Antonio Pedro

Uploaded 04-10-2013
Keywords child mortality
democratization
longitudinal models
random effects models
bent lines
Abstract In this study, I investigate the causal linkage between political regimes and health outcomes over 180 countries between 1970 and 2010. While there are a number of previous empirical studies on this topic, the results of those studies are mixed and even contradictory. Missing data and measurement error present a major challenge. The main outcome of interest---child mortality--was until very recently poorly measured or unmeasured for many countries, specially for dictatorships and low-income countries. A lack of comparable measures of political regimes across time periods and countries also contributes to the contradictory findings in the existing literature. Finally, new statistical techniques that capture the important over-time dynamics that we expect to find in the translation of regime type into health outcomes have not previously been applied. Thus, though there are many examples of wealthy democracies with low infant mortality and high infant mortality countries are disproportionally autocratic, it remains unclear whether regime type causes lower levels of child mortality. Recently a group of health scholars compiled a high resolution data set based on 16,174 measurements of mortality rate of children younger than 5 years old for 187 countries from 1970 to 2009. There measurements are based upon information from all available sources, including vital registration systems, summary birth histories in censuses and surveys, and complete birth histories ([CITE]). I revisit the connection between regime type and infant mortality using this data set and flexible Bayesian statistical techniques that are specially tailored for the problem. To gain greater leverage on the causal effect of political regime on health outcomes, I focus on democratization episodes occurring since 1970. I present hierarchical longitudinal models tracking over-time changes in mean child mortality and investigate whether democratization episodes are followed by systematics changes from previous trend in infant mortality. I also apply matching techniques to compare changes in infant mortality following democratization episodes to change in infant mortality in similar countries which did not democratized during the same period. I find that there is little if any effect of democracy on health outcomes.


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