
1 
Paper

Can Voting Reduce Welfare? Evidence from the US Telecommunications Sector
Falaschetti, Dino

Uploaded 
06152004

Keywords 
Electoral Institutions Voter Turnout Capture Theory Regulatory Commitment Telecommunications Policy Economic Welfare

Abstract 
Voter turnout is popularly cited as reflecting a polity's health. The
ease with which electoral members influence policy can, however,
constrain an economy's productive capacity. For example, while
influential electorates might carefully monitor political agents, they
might also "capture" them. In the latter case, electorates transfer
producer surplus to consumers at the expense of social welfare  i.e.,
a "healthy" polity's economy rests at an inferior equilibrium. I
develop evidence that the US telecommunications sector may have
realized such an outcome. This evidence is remarkably difficult to
dismiss as an artifact of endogeneity bias, and appears important for
several audiences. For example, the normative regulation literature
calls for constraints on producers' market power, while the
institutions and commitment literature calls for checks on political
agents' opportunism. Evidence that I develop here suggests that,
unbound by similar constraints, electoral principals might effectively
control their political agents while significantly retarding their
economic agents' productive incentives. 

2 
Paper

TimeSeriesCrossSection Issues: Dynamics, 2004
Beck, Nathaniel
Katz, Jonathan

Uploaded 
07242004

Keywords 
Timeseriescrosssection data lagged dependent variables Nickell bias specification integration

Abstract 
This paper deals with a variety of dynamic issues in the analysis of
timeseriescrosssection (TSCS) data raised by recent papers; it also more
briefly treats some crosssectional issues. Monte Carlo analysis shows
that for typical TSCS data that fixed effects with a lagged dependent
variable performs about as well as the much more complicated Kiviet
estimator, and better than the AndersonHsiao estimator (both designed
for panels). It is also shown that there is nothing pernicious in
using a lagged dependent variable, and all dynamic models either
implicitly or explicitly have such a variable; the differences between
the models relate to assumptions about the speeds of adjustment of
measured and unmeasured variables. When adjustment is quick it is hard
to differentiate between the models, and analysts may choose on
grounds of convenience (assuming that the model passes standard
econometric tests). When adjustment is slow it may be the case that
the data are integrated, which means that no method developed for the
stationary case is appropriate. At the crosssectional level, it is
argued that the critical issue is assessing heterogeneity; a variety
of strategies for this assessment are discussed. 

3 
Paper

Imitative and Evolutionary Processes that Produce Coordination Among American Voters
Mebane, Walter R.

Uploaded 
07112003

Keywords 
imitation evolutionary game strategic coordination voting

Abstract 
I examine the extent to which evolutionary game models based on the
idea of pure imitation may help to explain recent empirical findings
that the American electorate is involved in a situation of largescale
strategic coordination. Pure imitation in this context is the idea
that some voters who are dissatisfied with their current strategy look
around and adopt the strategy of the first voter they encounter who
has attributes similar to theirs. The current analysis is part of a
plan to use evolutionary models to motivate simulations based on
National Election Studies data. The model implies that all voters
ultimately use strategic coordination, although competing strategies
disppear at different rates, depending on the voter's partisanship. 

4 
Paper

The BinomialBeta Hierarchical Model for Ecological Inference: Methodological Issues and Fast Implementation via the ECM Algorithm
de Mattos, Rogerio S.
Veiga, Alvaro

Uploaded 
10172002

Keywords 
ecological inference hierarchical models binomialbeta distribution ECM Algorithm

Abstract 
The binomialbeta hierarchical model from King, Rosen, and Tanner (1999)
is a recent contribution to ecological inference. Developed for the 2x2
tables case and from a bayesian perspective, the model is featured by
the compounding of binomial and beta distributions into a hierarchical
structure. From a sample of aggregate observations, inference with this
model can be made regarding values of unobservable disaggregate
variables. The paper reviews this EI model with two purposes: First, a
faster approach to use it in practice, based on explicit modeling of
the disaggregate data generation process along with posterior maximization
implemented via the ECM algorithm, is proposed and illustrated with an
application to a real dataset; second, limitations concerning the use
of marginal posteriors for binomial probabilities as the vehicle of
inference (basically, the failure to respect the accounting identity)
instead of the predictive distributions for the disaggregate proportions
are pointed. In the concluding section, principles for EI model building
in general and directions for further research are suggested. 

5 
Paper

StateLevel Opinions from National Surveys: Poststratification using Hierarchical Logistic Regression
Park, David K.
Gelman, Andrew
Bafumi, Joseph

Uploaded 
07122002

Keywords 
Bayesian Inference Hierarchical Logit Poststratification Public Opinion States Elections

Abstract 
Previous researchers have pooled national surveys in order to construct
statelevel opinions. However, in order to overcome the small n problem
for less populous states, they have aggregated a decade or more of
national surveys to construct their measures. For example, Erikson,
Wright and McIver (1993) pooled 122 national surveys conducted over 13
years to produce statelevel partisan and ideology estimates. Brace,
SimsButler, Arceneaux, and Johnson (2002) pooled 22 surveys over a
25year period to produce statelevel opinions on a number of specific
issues. We construct a hierarchical logistic regression model for the
mean of a binary response variable conditional on poststratification
cells. This approach combines the modeling approach often used in
smallarea estimation with the population information used in
poststratification (see Gelman and Little 1997). We produce statelevel
estimates pooling seven national surveys conducted over a nineday
period. We first apply the method to a set of U.S preelection polls,
poststratified by state, region, as well as the usual demographic
variables and evaluate the model by comparing it to statelevel election
outcomes. We then produce statelevel partisan and ideology estimates by
comparing it to Erikson, Wright and McIver's estimates. 

6 
Paper

Monotone Comparative Statics in Models of Politics: A Method for Simplifying Analysis and Enhancing Empirical Content
Bueno de Mesquita, Ethan
Ashworth, Scott

Uploaded 
08182004

Keywords 
game theory formal theory empirical implications of theoretical models comparative statics

Abstract 
We elucidate a powerful yet simple method for deriving comparative statics conclusions for a wide variety of models: Monotone Comparative Statics (Milgrom and Shannon, 1994). Monotone comparative static methods allow researchers to extract robust, substantive empirical implications from formal models that can be tested using ordinal data and simple nonparametric tests. They also replace a diverse range of more technically di±cult mathematics (facilitating richer, more realistic models), a large set of assumptions that are hard to understand or justify substantively (highlighting the political intuitions underlying a model's results), and a complicated set of methods for extracting implications from models. We present an accessible introduction to the central monotone comparative statics results and a series of practical tools for using these techniques in applied models (with reference to original sources, when relevant). Throughout we demonstrate the techniques with examples drawn from political science. 

7 
Paper

Is All Politics and Economics Local? National Elections and Local
Wawro, Gregory
Himmelberg, Charles P.

Uploaded 
07142001

Keywords 
elections economic conditions voting behavior aggregation

Abstract 
Scholars have long sought to understand the causal relationships
between economics and political participation. Of particular concern
has been how economic experiences have affected individuals' decisions
to participate in elections and cast votes for candidates of different
political parties. Practically all of the studies on elections in the
United States have focused on national aggregate economic conditions
and national aggregate political outcomes, while only a handful of
studies have focused on whether state and local economic conditions
affect federal elections. The conclusion one would reach from these
studies is that the adage ``all politics is local'' does not apply to
economics and elections. In fact, despite the findings of some early
studies (e.g. Tufte 1975), recent research would lead us to conclude
that economic conditions have no direct effects on congressional
elections (Erikson 1990; Alesina and Rosenthal 1995). According to
these recent studies, the economy is related to congressional
elections only indirectly through its effects on presidential
elections. And even in presidential elections, a key economic
indicatorunemploymentappears to have little to no effect on
presidential elections.
In this paper, we question the conclusions of previous studies by
considering how the failure to correctly model vote shares at the
local level could produce misleading results on the effects for
economic conditions on elections in local analysis. We develop a
model for local vote shares by adapting a model derived in the
empirical literature on demand for differentiated products. Our model
explicitly accounts for nonlinearity and aggregation in vote share
functions and so avoids some of the problems of standard linear
specifications of vote shares that are common in the literature. We
estimate our model using data at the local level to assess the impact
of economic conditions on presidential vote shares and turnout in the
1992 election. We find that local unemployment does affect
presidential votes and these effects vary by demographic groups in
interesting ways. 

8 
Paper

Estimating Risk and Rate Levels, Ratios, and Differences in CaseControl Studies
King, Gary
Zeng, Langche

Uploaded 
05062001

Keywords 
Logistic Models CaseControl Studies Relative Risk Odds Ratio Risk Ratio Risk Difference Hazard Rate Rate Ratio Rate Difference

Abstract 
Classic (or ``cumulative'') casecontrol sampling designs do not admit
inferences about quantities of interest other than risk ratios, and
then only by making the rare events assumption. Probabilities, risk
differences, and other quantities cannot be computed without knowledge
of the population incidence fraction. Similarly, density (or ``risk
set'') casecontrol sampling designs do not allow inferences about
quantities other than the rate ratio. Rates, rate differences,
cumulative rates, risks, and other quantities cannot be estimated
unless auxiliary information about the underlying cohort such as the
number of controls in each full risk set is available. Most scholars
who have considered the issue recommend reporting more than just risk
and rate ratios, but auxiliary population information needed to do
this is not usually available. We address this problem by developing
methods that allow valid inferences about all relevant quantities of
interest from either type of casecontrol study when completely
ignorant of or only partially knowledgeable about relevant auxiliary
population information. 

9 
Paper

Strategic voting in mixedmember electoral systems: The Italian case
Benoit, Kenneth
Laver, Michael
Giannetti, Daniela

Uploaded 
08262000

Keywords 
elections italy strategic voting ecological inference

Abstract 
The new Italian electoral system has two elements, a plurality element
in single member districts and a PR element in larger multimember
constituencies. The plurality element provides strong incentives for
groups of parties to form preelectoral coalitions. The PR element
offers incentives for parties to contest the elections
individually. We can think of two types of voter. The first type, whom
we characterize as "strategic," votes for his or her first choice
party in the PR election since there is no strategy that can improve
on this. In the plurality election, a strategic voter supports the
candidate sponsored by the coalition with which his or her first
choice party is affiliated, even if this is not from the first choice
party. The second type of voter, whom we characterize as
"nonstrategic," also votes for his or her first choice party in the
PR election. In the plurality election, the nonstrategic voter will
vote for a first choice party if a candidate of this party is on the
ballot but, if not, votes unpredictably. In this paper, we model the
"strategic" and "non strategic" elements of the vote flowing to
candidates in the plurality element of the election. Using data from
the 1996 and 1994 elections on both PR and plurality voting patterns
in each single member district, and confining ourselves to districts
where there is a runoff between two coalitions, we are able to
estimate the relative numbers of strategic and non strategic voters
in each district, and characterize this in terms of a range of
strategic variables. 

10 
Paper

Why Lagged Dependent Variables Can Suppress the Explanatory Power of Other Independent Variables
Achen, Christopher H.

Uploaded 
07142000

Keywords 
time series autoregressive lags serial correlation budgets arms races

Abstract 
In many time series applications in the social sciences, lagged dependent variables have no obvious causal interpretation, and researchers omit them. When they are left out, the other coefficients take on sensible values. However, when an autoregressive term is put in ``as a control,'' it often acquires a large, statistically significant coefficient and improves the fit dramatically, while many or all of the remaining substantive coefficients collapse to implausibly small and insignificant values. Occasionally, the substantive variables even take on the wrong sign.
This paper explains why this phenomenon occurs and how the resulting confusions have often misled researchers into inaccurate inferences. The standard findings that government budgets are caused primarily by past budgets and that arms races are driven mainly by domestic forces are shown to be likely statistical artifacts. Applications are made to vector autoregressions, errorcorrection models, and panel studies. 

11 
Paper

TheStage Estimation of Stochastic Truncation Models with Limited Dependent Variables
Boehmke, Frederick

Uploaded 
04132000

Keywords 
selection bias stochastic truncation maximum likelihood simulation monte carlo initiative interest groups

Abstract 
Recent work has made progress in estimating models involving selection bias of a par
ticularly strong nature: all nonrespondents are unit nonresponders, meaning that no data
is available for them. These models are reasonable successful in circumstances where the
dependent variable of interest is continuous, but they are less practical empirically when it
is latent and only discrete outcomes or choices are observed. I develop a method in this
paper to estimate these models that is much more practical in terms of estimation. The
model uses a small amount of auxiliary information to estimate the selection equation and
these parameters are then used to estimate the equation of interest in a maximum likelihood
setting. After presenting monte carlo analysis to support the model, I apply the technique
to a substantive problem: which interest groups are likely to turn to the initiative process
to achieve their policy goals. 

12 
Paper

Multiculturalism, Diversity, and Prejudice
Branton, Regina P.
Jones, Bradford S.

Uploaded 
03271999

Keywords 
random coefficients multilevel analysis multiculturalism racial politics

Abstract 
In this paper, we consider the relationship between racial and
ethnic diversity and individuals' assessments of racial and ethnic
groups measured on several public opinion items. To examine these
issues, we merge 1992 National Election Study data
with U.S. Census Bureau demographic data measured at the
congressional district level. We then develop an index of
diversity that is based on the distribution of racial and ethnic
groups in the congressional district. To examine the relationship
between diversity and individuallevel attitudes toward racial and
ethnic groups, we estimate a series of models treating the
response variable as a function of both individuallevel
attributes and districtlevel attributes. This approach allows us
to assess, among other things, if diversity is associated with
more positive or negative evaluations of racial and ethnic groups.
The models herein are all estimated as mixed effects models to
account for the clustering of observations within congressional
districts. We find that diversity is associated with group affect and
individuals' placement on policy issues; however, in contrast to
some of the extant literature, we
find that racial and ethnic diversity is nonlinearly associated
with group affect: extremely low and extremely high levels of
racial and ethnic diversity are associated with lower racial and
ethnic group evaluations, while districts that are moderately
diverse are associated with higher evaluations. This result also
holds for some of the policy items examined. Specifically, we
find that support for government assistance to blacks, and to a
lesser extent, support for affirmative action, exhibits this
nonlinearity with regard to racial and ethnic diversity.
We also find this pattern for individuals' assessment of welfare
recipients. 

13 
Paper

Does Size Matter? Exploring the Small Sample Properties of Maximum Likelihood Estimation
Hart, Jr., Robert A.
Clark, David H.

Uploaded 
04201999

Keywords 
small samples ML Type II errors bootstrap

Abstract 
The last two decades have witnessed an explosion in the use of
computationally intensive methodologies in the social sciences as
computer technology has advanced. Among these empirical methods are
Maximum Likelihood (ML) procedures. ML estimators possess a variety
of desirable qualities, perhaps most prominent of which is the
asymptotic efficiency of the standard errors. However, the behavior
of the estimators in general, of the estimates of the standard errors
in particular, and thus of inferential hypothesis tests are uncertain
in small sample analyses. In political science research, small
samples are routinely the subject of empirical investigation using ML
methods, yet little is known regarding what effect sample size has on
a researcher's ability to draw inferences
This paper explores the behavior of ML estimates in probit models
across differing sample sizes and with varying numbers of independent
variables in Monte Carlo simulations. Our experimental results allow
us to conclude that: a) the risk of making Type I errors does not
change appreciably as sample size descends; b) the risk of making Type
II errors increases dramatically in smaller samples and as the number
of regressors increases. 

14 
Paper

Deliberation and Voting at the Federal Convention of 1787
Londregan, John B.

Uploaded 
07131999

Keywords 
Scaling Deliberation Legislation

Abstract 
This paper examines the deliberative voting of the Federal
Convention of 1787, and contrasts this type of voting with
the more commonly observed position taking behavior that
characterizes most legislatures. The analysis constructs an
empirical model that incorporates proposal valence, which at
the federal convention corresponded to proposals' contribution
to the ``ratifiability" of the constitution, and uses
information contained in the authorship of proposals to overcome
the identification problems that plague empirical spatial models
of voting. The estimated issue positions of the state delegations
reveal a significant cleavage on an two issue dimensions;
one corresponding to the balance between the states and the
central government and the other dealing with the extent of the
powers granted to the federal governmen 

15 
Paper

Strategic Voting in Germany. Evidence employing King's Ecological Inference
Gschwend, Thomas

Uploaded 
10201999

Keywords 
Germany election voting EI

Abstract 
Germany provides an especially interesting case for the study of strategic
voting because they use twoballot system on Election Day. Voters are
encouraged to split their votes using different strategies. This is called
emph{sophisticated voting}. I disentangle different types of sophisticated
voting that have been mixed in the literature so far: On the first vote
there is emph{tactical} voting, and on the second vote there is emph{loan}
voting. Therefore, I focus particularly on ticketsplitting patterns. The
data set I use contains official election results of first and second votes
for all WestGerman districts from the federal election of 1998. To obtain
estimates that determine quantity of straight and splitticket voting
between political parties I employ King's method of Ecological Inference
(EI). Using these estimates as independent variables in linear regression
models, I show that tactical and loan voters secured the representation of
FDP and the Greens in the German Parliament. 

16 
Paper

The Two Faces of Public Opinion
Berinsky, Adam

Uploaded 
04131998

Keywords 
public opinion selection bias item nonresponse social desirability bivariate probit

Abstract 
In this paper I trace out the aggregate effects of the social forces in the
survey interview that might influence the opinions which individuals express.
First, I advance the "Mediated Communication" theory of the survey response,
which builds on existing models of public opinion in the political science
literature by accounting for effects related to the social context of the
survey setting. I then discuss how the aggregation process could compound
these individuallevel effects to create an opinion signal which is a poor
representation of the collective public's policy preferences. As an
illustration of these effects and the resulting difficulties involved in
measuring aggregate opinion on socially sensitive issues, I use National
Elections Study (NES) data from 19901994 to show that public opinion
polls overstate support for school integration. Specifically, individuals
who harbor antiintegration sentiments are likely to hide their socially
unacceptable opinions behind a mask of indifference. Finally, in order
to confirm the validity of these findings, I show that the same methods
which predict that opinion polls understate true opposition to government
involvement in school integration also predict the results of the 1989
New York City mayoral election  an election where the charged racial
atmosphere made accurate polling difficult, if not impossible  more
accurately than the marginals of the preelection polls taken in the weeks
leading to the election. All told, these results suggests that survey
questions on school integration  and more generally questions on racial
attitudes  may provide an inaccurate picture of true public sentiment on
such sensitive issues. 

17 
Paper

Cointegration Tests when Data are NearIntegrated
De Boef, Suzanna
Granato, Jim

Uploaded 
04221998

Keywords 
time series nearintegration ECMs DickeyFuller tests Monte Carlo

Abstract 
Testing theories about political change requires analysts
to make assumptions about the nature of the memory of their
time series. Applied analyses are often based on inferences
that the time series of interest are integrated and
cointegrated. Typically these analyses rest on DickeyFuller
pretests for unit roots and tests for cointegration based on
the residuals from a cointegrating regression in the context
of the EngleGranger twostep methodology. We argue that
this approach is not a good one and use Monte Carlo results
to show that these tests can lead analysts to falsely
conclude that the data are cointegrated (or nearly
cointegrated) when the data is nearintegrated and not
cointegrating. Further, analysts are likely to falsely conclude
the relationship is not cointegrating when it is. We show how
inferences are highly sensitive to sample size and the signal to
noise ratio in the data. We suggest that analysts use the
single equation error correction test for cointegrating
relationships, and that caution be used in all cases where
nearintegration is a reasonable alternative to unit roots.
Finally, we suggest that in many cases analysts can drop the
language of cointegration and adopt single equation error
correction models when the theory of error correction is
relevant. 

18 
Paper

Democracy and Exchange Rates: An Experimental Study
Freeman, John R.
Hays, Jude
Stix, Helmut

Uploaded 
07171998

Keywords 
Markov switching model exchange rates comparative democracy political economy

Abstract 
The world's financial markets are becoming increasingly liberalized and interconnected. There is much debate about whether this development is socially desirable. Of increasing interest in this debate are the implications of the globalization of finance for democracy.
The relationship between the workings of currency markets and democratic institutions is studied. The economic literature on exchange rate determination is briefly reviewed. The Markov switching model is considered as one of the most useful with which to analyze the politics of exchange rate determination. Next, the political science literature is discussed, including the research on electoral systems and comparative democracy. Out of this discussion emerge several competing propositions about how political (re)equilibration affects currency markets, more specifically, what the Markov switching framework should show about the impact of electoral outcomes and political polls on compound returns (the log difference of the exchange rate) in some or all democracies. A design for testing these propositions then is laid out and implemented.
The results support the view that democratic politics affects currency markets. In particular, opinion polls about chief executive and government performance have a direct effect on the probabilities of switches between currency regimes. This suggests that these polls cause currency traders to revise their expectations about the stability of governments and (or) the content of public policy. In addition, the results refute claims that pluralist and majoritarian forms of democracy are more likely to be a source of trader uncertainty and hence regime shifts than corporatist and consensual forms of democracy. There is some evidence that (democratic) institutional "incoherency" (Garrett, 1998) is a source of market uncertainty and therefore that the effects of opinion polls and other political variables on the probabilities of regime shifts are greater in the respective countries. 

19 
Paper

Intrainstitutional Mobility in the Postreform House of Representatives
Wawro, Gregory

Uploaded 
08261998

Keywords 
legislative entrepreneurship legislative organization maximum likelihood methods mobility analysis career concerns vacancy competition

Abstract 
Theory: When deciding whom to promote to prestigious positions within
the House, members will favor those individuals who are the most likely to use
the resources associated with prestigious positions to produce legislation
when there is substantial demand for it. Members will select those
individuals who have demonstrated a propensity for engaging in legislative
entrepreneurship because they are the most qualified in this regard.
Hypothesis: "The job ladders hypothesis": Members who engage
in legislative entrepreneurship are more likely to move up the job ladder to
prestigious positions within the committee and party hierarchies in the House.
Method: I develop measures of legislative entrepreneurship using data
on the characteristics of bills sponsored by members and members' testimony
before committees. I develop a statistical model that addresses the problems
of analyzing intrainstitutional mobility and the problems with assessing
entrepreneurial ability. With this model I perform a multivariate analysis to
assess the effects of legislative entrepreneurship while accounting for other
variables that previous studies have found to affect intrainstitutional
mobility.
Results: Engaging in legislative entrepreneurship increases the
probability that members of the majority party will advance to full committee,
subcommittee, and party leadership positions. 

20 
Paper

Electoral Reform and Legislative Structure: The Effects of Australian Ballot Laws on House Committee Tenure
Katz, Jonathan
Sala, Brian R.

Uploaded 
01011995

Keywords 
congress personal vote australian ballot duration model

Abstract 
Most scholars agree that members of Congress are strongly motivated by
their desire for reelection. This assumption implies that MCs adopt
institutions, rules and norms of behavior in part to serve their
electoral interests. Direct tests of the electoral connection are
rare, however, because significant, exogenous changes in the electoral
environment are difficult to identify. In this paper, we develop and
test an electoral rationale for the norm of committee tenure, in which
returning MCs typically retain their same assignments. We examine
tenure patterns before and after a major, exogenous change in the
electoral system  the states' rapid adoption of Australian Ballot
laws in the early 1890s. The ballot changes, we argue, induced new
``personal vote'' electoral incentives, which contributed to the
adoption of ``modern'' Congressional institutions such as ``property
rights'' to committee assignments. We demonstrate that there was a
marked increase in assignment stability after 1892, when a majority of
states had put the new ballot laws into force  earlier than previous
studies have suggested. 

21 
Paper

Estimating the Same Quantities from Different Levels of Data: Time Dependence and Aggregation in Event Count Models
King, Gary
Signorino, Curtis S.
Alt, James E.

Uploaded 
00000000

Keywords 
(none submitted)

Abstract 
Binary, count, and duration data all code for discrete events occurring
at points in time. Although a single data generation process can
produce any of these three data types, the statistical literature is not
very helpful in providing methods to estimate parameters of the same
process from each. In fact, only a single theoretical process exists
for which known statistical methods can estimate the same parameters 
and it is generally limited to count and duration data. The result is
that seemingly trivial decisions about which level of data to use can
have important consequences for substantive interpretations. We
describe the theoretical event process for which results exist, based on
timeindependence. We also derive a new set of models for a
timedependent process and compare their predictions to those of a
commonly used model. Any hope of avoiding the more serious problems of
aggregation bias in events data is contingent on first deriving a much
wider arsenal of statistical models and theoretical processes that are
not constrained by the particular forms of data that happen to be
available. 

22 
Paper

Bootstrap Methods for Nonnested Hypothesis Tests
Mebane, Walter R.
Sekhon, Jasjeet

Uploaded 
07201996

Keywords 
Cox Test Bootstrap LISREL Endogenous Switching Regression TobitStyle Censoring

Abstract 
Cox (1961; 1962) proposed a fairly general method that can be used to
construct powerful tests of alternative hypotheses from separate statistical
families. We prove that nonparametric bootstrap methods can produce
consistent and secondorder correct approximations to the distribution of the
Cox statistic for nonnested LISRELstyle covariance structure models. We use
the method to investigate a question about the specification of a LISREL model
used by Kinder, Adams and Gronke (1989). In a second applicationa pair of
nonnested endogenous switching regression models with tobitstyle censoring,
applied to real datawe illustrate how bootstrap calibration can be used to
correct the size of the test when the test distribution is being estimated by
Monte Carlo simulation due to concern about nonregularity. 

23 
Paper

Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 
10271997

Keywords 
conditional probability decision analysis elections electoral campaigning forecasting political science presidential elections rare events rational choice subjective probability voting power

Abstract 
Researchers sometimes argue that statisticians have little to
contribute when few realizations of the process being estimated are
observed. We show that this argument is incorrect even in the
extreme situation of estimating the probabilities of events so rare
that they have never occurred. We show how statistical forecasting
models allow us to use empirical data to improve inferences about
the probabilities of these events.
Our application is estimating the probability that your vote will be
decisive in a U.S. presidential election, a problem that has been
studied by political scientists for more than two decades. The
exact value of this probability is of only minor interest, but the
number has important implications for understanding the optimal
allocation of campaign resources, whether states and voter groups
receive their fair share of attention from prospective presidents,
and how formal ``rational choice'' models of voter behavior might be
able to explain why people vote at all.
We show how the probability of a decisive vote can be estimated
empirically from statelevel forecasts of the presidential election
and illustrate with the example of 1992. Based on generalizations
of standard political science forecasting models, we estimate the
(prospective) probability of a single vote being decisive as about 1
in 10 million for close national elections such as 1992, varying by
about a factor of 10 among states.
Our results support the argument that subjective probabilities of
many types are best obtained via empiricallybased statistical
prediction models rather than solely mathematical reasoning. We
discuss the implications of our findings for the types of decision
analyses that are used in public choice studies. 

24 
Paper

Heterogeneity and Disperson in the BetaBinomial Model
Palmquist, Bradley

Uploaded 
08231997

Keywords 
betabinomial overdispersion underdispersion count models abortion

Abstract 
Count variables built up from sums of independent and identically
distributed (IID) binary random variables can be easily modeled by
the binomial distribution. But what happens to sums of binary random
variables if they are not IDD? King (1989) and others have presented
the Beta Binomial and Extended Beta Binomial distributions as a way
of handling the overdispersion that results from heterogeneity.
This model seems to work well for some examples such as the
distribution of state by state totals like the number of school
districts banning a book in a given year. Heterogeneity of book
banning rates across states would produce overdispersion
(greater variability than expected from a binomial model).
But another obvious example, the heterogeneity among Senators
in vote counts aggregated by roll call, cannot be directly modeled
by the Beta Binomial models in the same way. In the toxicology
literature, from which political scientists have borrowed the
Beta Binomial models, the heterogeneity observed is across units
(``litters"), not within. Under the most reasonable assumptions,
heterogeneity among Senators in response probabilities either
produces pure Binomial variation in vote counts or contributes
to underdispersion from roll call to roll call. These results
are shown analytically and by simulation. Then a preliminary
analysis of data of this type  repeated votes on abortion in
the Senate from 1974 to 1994  is presented. 

25 
Paper

A Process Control Model of Legislative Productivity: Testing the Effects of Congressional Reform
Gill, Jeff
Thurber, James A.

Uploaded 
08081997

Keywords 
Queueing Theory Software Simulation Congressional Reform Productivity Equilibrium Model Committee Efficiency

Abstract 
We examine the effects of congressional reform on legislative
productivity using a completely new methodology in political science based
on queueing theory and industrial simulation and control software. The
foundation of our analysis is the development of a process control model
of legislative development. The model establishes a status quo
productivity equilibrium based on empirical data from the first
100 days of the $103^{rd}$ House of Representatives, then stresses
the system using the mandated productivity of the first 100 days of
the $104^{th}$ House of Representatives. We compare the agenda based
distribution of bill assignments from the ``Contract with America''
with a uniform assignment and find that requiring a stable legislative
system to greatly increase productivity has substantial effects on
members' allocation of time. In particular, members are likely to
reduce time considering legislation and increasingly rely upon
partisan cues for vote decisions.
The methodology is sufficiently general that it can be applied to
almost any legislative setting. Our application focuses on the
feedback response from an electoral shift, but the methodology can
address any productivity question. Since all legislative bodies
have defined processes by which initiatives flow, the modeling and
simulating of these processes can illuminate efficiencies and
inefficiencies. Queueing theory addresses the prevalent and
generalizable scenario in which demand for legislative outcomes
exceeds the shortterm capacity of a legislative system. 

26 
Paper

Pattern Recognition of International Crises using Hidden Markov Models
Schrodt, Philip A.

Uploaded 
06301997

Keywords 
hidden Markov models event data early warning international crisis sequence analysis Middle East WEIS BCOW

Abstract 
Event data are one of the most widely used indicators in quantitative
international relations research. To date, most of the models using event data
have constructed numerical indicators based on the characteristics of the events
measured in isolation and then aggregated. An alternative approach is to use
quantitative pattern recognition techniques to compare an existing sequence of
behaviors to a set of similar historical cases. This has much in common with
human reasoning by historical analogy while providing the advantages of
systematic and replicable analysis possible using machinecoded event data and
statistical models.
This chapter uses "hidden Markov models" Ñ a recently developed sequence
comparison technique widely used in computational speech recognition Ñ to
measure similarities among international crises. The models are first estimated
using the Behavioral Correlates of War data set of historical crises, then
applied to an event data set covering political behavior in the contemporary
Middle East for the period April 1979 through February 1997.
A splitsample test of the hidden Markov models perfectly differentiates crises
involving war from those not involving war in the cases used to estimate the
models. The models also provide a high level of discrimination in a set of
test cases not used in the estimated, and most of the erroneouslyclassified
cases have plausible distinguishing features. The difference between the war
and nonwar models also correlates significantly with a scaled measure of
conflict in the contemporary Middle East. This suggests that hidden Markov
models could be used to develop conflict measures based on event similarities
to historical conflicts rather than on aggregated event scores. 

27 
Paper

A Simulated Maximum Likelihood application to the 1988 Democratic Primary
Lawrence, Eric D.

Uploaded 
03281997

Keywords 
simulated maximum likelihood multinomial probit vote choice models

Abstract 
The multinomial probit model has some appealing
advantages over models that do not allow for
correlated errors, such as multinomial logit and
conditional logit. With a few exceptions, however,
multinomial probit models have not been estimated
for vote choice models because of the computational
costs inherent in evaluating high dimensional integrals.
This paper explains one recently developed approach,
simulated maximum likelihood combined with the GHK simulator,
that makes it feasible to accurately estimate multinomial
probit models. The method is demonstrated on a model of
the 1988 Democratic Super Tuesday primary. 

28 
Paper

Treatment Spillover Effects Across Survey Experiments
Lee, Daniel
Transue, John
Aldrich, John

Uploaded 
04052005

Keywords 
survey experiments experiments survey methods

Abstract 
Embedding experiments within surveys has reinvigorated survey research in general and especially in political science. These designs use random assignment to create true experiments within (typically nationally) representative sample surveys. Thus, they combine the internal validity of experiments with the external validity of national surveys. We investigate whether experimental treatments spill over and effect later experiments in an unintended manner. Using the 1991 Race and Politics survey, we find evidence of experimental spillover. Specifically we find that experiments at the beginning of a survey influence later experiments. We also find (much less) evidence of adjacent experiments affecting subsequent experiments. The paper concludes with a discussion of designs for future research that could aid our understanding of experimental spillover. 

29 
Paper

Unemployment and Violence in Northern Ireland: a missing data model for ecological inference
Honaker, James

Uploaded 
07192005

Keywords 
Multiple Imputation Ecological Inference Count Data Political Violence

Abstract 
Contrary to the body of literature in political violence, and the
rhetoric of many parties of the conflict, timeseries models of ``the
troubles'' in Northern Ireland by White (1993) and Thompson (1989) have
found no evidence that economic conditions effect the intensity, sources
or direction of violence. I show that several methodological flaws
exist in previous models. They fail to address the discrete, count
nature of the data, the contagion present from aggregation over time,
pooling issues from different types of violence, and the over dispersal
of deaths. However, the key problem, acknowledged even by the authors
themselves, is that all measures of unemployment aggregate Protestant
and Catholic unemployment rates into one single measure. Using a model
that combines methods of Multiple Imputation to recover missing data
(King Honaker Joseph Scheve 2001) and the literature of models for
Ecological Inference problems (especially King 1997) I estimate the
disaggregated unemployment rates by religion from the available data.
Unemployment is shown to be a leading cause of the violence by
Republican factions in Northern Ireland. 

30 
Paper

Democracy as a Latent Variable
Treier, Shawn
Jackman, Simon

Uploaded 
07162003

Keywords 
democracy Polity measurement latent variables Bayesian statistics itemresponse model ordinal data latent class analysis democratic peace Markov chain Monte Carlo

Abstract 
Measurement is critical to the social scientific enterprise. Many key concepts in socialscientific theories are not observed
directly, and researchers rely on assumptions (tacitly or explicitly, via formal measurement models) to operationalize these concepts in empirical work. In this paper we apply formal, statistical measurement models to the Polity indicators of democracy and autocracy, used widely in studies of international relations. In so doing, we make explicit the hitherto implicit assumptions underlying scales built
using the Polity indicators. We discuss two models: one in which democracy is operationalized as a latent continuous variable, and another in which democracy is operationalized as a latent class. Our modeling approaches allow us to assess the measurement error in the resulting measure of democracy. We show that this measurement error is considerable, and has substantive
consequences when using a measure of democracy as an independent variable in crossnational statistical analysis. Our analysis suggests that skepticism as to the precision of the Polity democracy scale is wellfounded, and that many researchers have been overly sanguine about the properties of the Polity democracy scale in applied statistical work. 

31 
Paper

A StateSpace Approach to Economic Popularity Functions
Pickup, Mark

Uploaded 
07112006

Abstract 
Economic popularity functions are central to the debate over whether voters use evaluations of the economy in their decision to support their government or not. This is of particular importance to the key democratic principle of electoral accountability that parties in power should and are held accountable for the outcomes of their actions and policies through the electoral process. Given the evidence from many nations that the economy is an issue of importance to the electorate, which they believe the government has control over, the inconsistent findings with regards to the impact of the economy on party popularity has made conclusive evaluations of the principle of electoral accountability elusive. This study demonstrates that the difficulty lies in a series of methodological flaws found in current approaches to developing popularity functions. Most analysts using public opinion timeseries data have not applied the necessary methods to take into account the problems which such data can pose – problems such as complex error structures, shifting and compound nonstationary dynamics and noisy data. Accordingly, this study explicates a statespace Bayesian approach that addresses these methodological issues. In doing so, it outlines a technique that may be applied to a wide range of public opinion dynamic modelling issues. 

32 
Paper

Designing and Analyzing Randomized Experiments
Horiuchi, Yusaku
Imai, Kosuke
Taniguchi, Naoko

Uploaded 
07052005

Keywords 
Bayesian inference causal inference noncompliance nonresponse randomized block design

Abstract 
In this paper, we demonstrate how to effectively design and analyze randomized experiments, which are becoming increasingly common in political science research. Randomized experiments provide researchers with an opportunity to obtain unbiased estimates of causal effects because the randomization of treatment guarantees that the treatment and control groups are on average equal in both observed and unobserved characteristics. Even in randomized experiments, however, complications can arise. In political science experiments, researchers often cannot force subjects to comply with treatment assignment or to provide the information necessary for the estimation of causal effects. Building on the recent statistical literature, we show how to make statistical adjustments for these noncompliance and nonresponse problems when analyzing randomized experiments. We also demonstrate how to design randomized experiments so that the potential impact of such complications is minimized. 

33 
Paper

Bayesian and Likelihood Inference for 2 x 2 Ecological Tables: An Incomplete Data Approach
Imai, Kosuke
Lu, Ying
Strauss, Aaron

Uploaded 
12162006

Keywords 
Coarse data Contextual effects
Data augmentation EM algorithm Missing information principle
Nonparametric Bayesian Modeling.

Abstract 
Ecological inference is a statistical problem where aggregatelevel data are used to make inferences about individuallevel behavior. Recent years have witnessed resurgent interest in ecological inference among political methodologists and statisticians. In this paper, we conduct a theoretical and empirical study of Bayesian and likelihood inference for 2 x 2 ecological tables by applying the general statistical framework of incomplete data. We first show that the ecological inference problem can be decomposed into three factors: distributional effects which address the possible misspecification of parametric modeling assumptions about the unknown distribution of missing data, contextual effects which represent the possible correlation between missing data and observed variables, and aggregation effects which are directly related to the loss of information caused by data aggregation. We then examine how these three factors affect inference and offer new statistical methods to address each of them. To deal with distributional effects, we propose a nonparametric Bayesian model based on a Dirichlet process prior which relaxes common parametric assumptions. We also specify the statistical adjustments necessary to account for contextual effects. Finally, while little can be done to cope with aggregation effects, we offer a method to quantify the magnitude of such effects in order to formally assess its severity. We use simulated and real data sets to empirically investigate the consequences of these three factors and to evaluate the performance of our proposed methods. C code, along with an easytouse R interface, is publicly available for implementing our proposed methods. 

34 
Paper

Modeling Foreign Direct Investment as a Longitudinal Social Network
Jensen, Nathan
Martin, Andrew
Westveld, Anton

Uploaded 
07132007

Keywords 
foreign direct investment social network data longitudinal data hierarchical modeling mixture modeling Bayesian inference.

Abstract 
An extensive literature in international and comparative political economy has focused on the how the mobility of capital affects the ability of governments to tax and regulate firms. The conventional wisdom holds that governments are in competition with each other to attract foreign direct investment (FDI). Nationstates observe the fiscal and regulatory decisions of competitor governments, and are forced to either respond with policy changes or risk losing foreign direct investment, along with the politically salient jobs that come with these investments. The political economy of FDI suggests a network of investments with complicated dependencies.
We propose an empirical strategy for modeling investment patterns in 24 advanced industrialized countries from 19852000. Using bilateral FDI data we estimate how increases in flows of FDI affect the flows of FDI in other countries. Our statistical model is based on the methodology developed by Westveld & Hoff (2007). The model allows the temporal examination of each notion's activity level in investing, attractiveness to investors, and reciprocity between pairs of nations. We extend the model by treating the reported inflow and outflow data as independent replicates of the true value and allowing for a mixture model for the fixed effects portion of the network model. Using a fully Bayesian approach, we also impute missing data within the MCMC algorithm used to fit the model. 

35 
Paper

Misunderstandings among Experimentalists and Observationalists about Causal Inference
Imai, Kosuke
King, Gary
Stuart, Elizabeth

Uploaded 
09162007

Keywords 
matching blocking causal inference experimental design observational studies average treatment effects covariate balance field experiments survey experiments

Abstract 
We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fallacies of causal inference in experimental and observational research. These issues concern some of the most basic advantages and disadvantages of each basic research design. Problems include improper use of hypothesis tests for covariate balance between the treated and control groups, and the consequences of using randomization, blocking before randomization, and matching after treatment assignment to achieve covariate balance. Applied researchers in a wide range of scientific disciplines seem to fall prey to one or more of these fallacies, and as a result make suboptimal design or analysis choices. To clarify these points, we derive a new fourpart decomposition of the key estimation errors in making causal inferences. We then show how this decomposition can help scholars from different experimental and observational research traditions better understand each other's inferential problems and attempted solutions.
(This paper is forthcoming in the Journal of the Royal Statistical Society, but we have some time for revisions and would value any comments anyone might have. This is a revised and much more general version of an earlier paper, "The Balance Test Fallacy in Causal Inference".) 

37 
Paper

Research Opportunities  The 2009/10 British Election Study
Clarke, Harold
Sanders, David
Stewart, Marianne
Whiteley, Paul

Uploaded 
07072008

Keywords 
electons experiments inperson internet public opinion

Abstract 
The 2009/10 British Election Study (BES) will include significant research opportunities for students of voting, elections and public opinion. The BES will have three major components: (a) inperson prepost election surveys; (b) rolling campaign internet panel survey (RCPS); (c) 48 interelection monthly continuous monitoring surveys (CMS) with annual panel components. Each CMS survey will offer researchers opportunities to include question batteries including experiments. Participation is free and data release is very fast. Proposals for research modules reviewed by BES Advisory Board and P.I.s. Proposals also entertained for research modules on core and RCPS components. 

38 
Paper

Understanding Wordscores
Lowe, Will

Uploaded 
04252007

Keywords 
content analysis wordscores ideal point item response theory

Abstract 
Wordscores is a widelyused procedure for inferring policy positions, or scores, for new documents on the basis of scores for words derived from documents with known scores. It is computationally straightforward, requires no distributional assumptions, but has unresolved practical and theoretical problems: In applications, estimated document scores are on the wrong scale and Wordscores does not specify a statistical model so it is unclear what assumptions the method makes about political text or how to tell whether they fit particular applications. The first part of the paper demonstrates that badly scaled document score estimates reflect deeper problems with the method. The second part shows how to understand Wordscores as an approximation to correspondence analysis which itself approximates a statistical ideal point model for words. Problems with the method are identified with the conditions under which these layers of approximation fail to ensure consistent and unbiased estimation of the parameters of the ideal point model. 

39 
Paper

Bayesian Combination of State Polls and Election Forecasts
Lock, Kari
Gelman, Andrew

Uploaded 
09212008

Keywords 
election prediction preelection polls Bayesian updating shrinkage estimation

Abstract 
In February of 2008, SurveyUSA polled 600 people in each state and asked who they would vote for in either headtohead matchup: Obama vs. McCain, and Clinton vs. McCain. Here we integrate these polls with prior information; how each state voted in comparison to the national outcome in the 2004 election. We use Bayesian methods to merge prior and poll data, weighting each by its respective information. The variance for our poll data incorporates both sampling variability and variability due to time before the election, estimated using preelection poll data from the 2000 and 2004 elections. The variance for our prior data is estimated using the results of the past nine presidential elections. The union of prior and poll data results in a posterior distribution predicting how each state will vote, in turn giving us posterior intervals for both the popular and electoral vote outcomes of the 2008 presidential election. Lastly, these posterior distributions are updated with the most recent poll data as of August, 2008. 

40 
Paper

Measuring the Effects of Voter Confidence on Political Participation
Levin, Ines
Alvarez, R. Michael

Uploaded 
06222009

Keywords 
voter confidence turnout participation mexico matching causal effects

Abstract 
In this paper we study the causal effect of voter confidence on participation decisions in the 2006 Mexican Election. Previous research has shown that voter confidence was a relevant factor in explaining participation during the years of the PRI hegemony. An open question is whether this relationship is still significant after the democratic transition taking place in the years 19972000. Moreover, in the previous literature, this problem was studied in a regression framework. In this article we argue that, since voter confidence and participation decisions are affected by similar covariates, a regression approach may lead to results which are too model dependent, and do not account for the heterogeneity of effects across voters. To solve this problem, we use matching methods, and find that voter confidence has considerable effects on participation decisions, but substantially different in magnitude from those found using the usual regression approach. 

41 
Paper

Competing Solutions to the PrincipalAgent Model
Haptonstahl, Stephen

Uploaded 
07232009

Keywords 
bargaining principal agent risk aversion fairness quantal response equilibrium strategic statistical model random utility experiment

Abstract 
PrincipalAgent (PA) theory has been used for over three decades to model the relationship between an informationadvantaged Agent and a Principal able to issue a contract ultimatum. For its common implementation as a game, the subgameperfect Nash equilibrium is reasonably simple but generally wrong in predicting experimental or observational data. This paper implements PA theory theoretically and statistically as two kinds of strategic statistical model, then develops methods for testing competing behavioral hypotheses. I show that subgameperfect Nash equilibrium, risk aversion/affinity, distributive justice/fairness theories, agent error, and random utility can be observationally distinct and how they might be distinguished statistically. 

42 
Paper

New Empirical Strategies to Model the Government
Formation Process
Glasgow, Garrett
Golder, Matt
Golder, Sona

Uploaded 
07152010

Keywords 
discrete choice mixed logit IIA random coefficients government formation

Abstract 
Over the past decade, a "standard approach" to the quantitative study of government formation has developed. This approach involves the use of a conditional (CL) logit model to examine government choice with the government formation opportunity as the unit of analysis. In this paper, we reconsider this approach and
make three methodological contributions. First, we demonstrate that the existing procedure used to test for the independence of irrelevant alternatives (IIA) is ï¬‚awed and severely biased against ï¬nding IIA violations.
Our new testing procedure reveals that many government alternatives share unobserved attributes, thereby violating the IIA assumption and making the CL model inappropriate. Second, we employ a mixed logit with random coefficients that allows us to take account of unobserved heterogeneity and IIA violations. Third, we return to a question that originally motivated this literature, namely, what determines the likelihood that
a particular party enters government? Although scholars have generally abandoned this question due to perceived methodological limitations in our ability to address it, we demonstrate that calculating probabilities
for parties entering ofï¬ce rather than governments is straightforward in a mixed logit framework. 

44 
Paper

How Robust Standard Errors Expose Methodological Problems They Do Not Fix
King, Gary
Roberts, Margaret

Uploaded 
07132012

Keywords 
robust standard errors clustered standard errors heteroskedasticityconsistent standard errors

Abstract 
"Robust standard errors'' are used in a vast array of scholarship across all fields of empirical political science and most other social science disciplines. The popularity of this procedure stems from the fact that estimators of certain quantities in some models can be consistently estimated even under particular types of misspecification; and although classical standard errors are inconsistent in these situations, robust standard errors can sometimes be consistent. However, in applications where misspecification is bad enough to make classical and robust standard errors diverge, assuming that misspecification is nevertheless not so bad as to bias everything else requires considerable optimism. And even if the optimism is warranted, we show that settling for a misspecified model (even with robust standard errors) can be a big mistake, in that all but a few quantities of interest will be impossible to estimate (or simulate) from the model without bias. We suggest a different practice: Recognize that differences between robust and classical standard errors are like canaries in the coal mine, providing clear indications that your model is misspecified and your inferences are likely biased. At that point, it is often straightforward to use some of the numerous and venerable model checking diagnostics to locate the source of the problem, and then modern approaches to choosing a better model. With a variety of real examples, we demonstrate that following these procedures can drastically reduce biases, improve statistical inferences, and change substantive conclusions. 

45 
Paper

Conservative Vote Probabilities: An Easier Method for the Analysis of Roll Call Data
Fowler, Anthony
Hall, Andrew B.

Uploaded 
08082012

Keywords 
Roll Call Ideology Congress Supreme Court State Legislatures Nonparametric

Abstract 
We propose a new rollcall scaling method based on OLS which is easier to implement and understand than previous methods and also produces directly interpretable estimates. This measure, Conservative Vote Probability (CVP), indicates the probability that an individual legislator votes "conservatively" relative to the median legislator. CVP is a flexible nonparametric statistical technique that requires no complicated assumptions but still produces legislator scalings that correlate with previous roll call methods at extremely high levels. In this paper we introduce the methodology behind CVP and offer several substantive examples to demonstrate its e efficacy as an easier, more accessible alternative to previous roll call methods. 

46 
Paper

The fault in our stars: Measuring and correcting significance bias in Political Science
Esarey, Justin
Wu, Ahra

Uploaded 
01162014

Keywords 
significance hypothesis test regression

Abstract 
Prior research finds that statistically significant results are overrepresented in scientific publications. If significant results are consistently favored in the review process, published results will systematically overstate the magnitude of their findings. Worse yet, the typical twotailed statistical significance test with \alpha=0.05 does little to prevent the proliferation of false positives in the literature. In this paper, we systematically measure the impact of these two forms of significance bias on published research in quantitative political science. We estimate that 35% or more of published results exaggerate their substantive significance to a meaningful degree, with an average upward bias of 9%20%. Additionally, 15%35% of published results are at elevated risk of being false positives. Most importantly, we evaluate a variety of new and existing methodological strategies to correct both forms of significance bias. We conclude that a smaller \alpha threshold combined with conservative Bayesian priors is an effective remedy. 

47 
Paper

The Perils of the All Cause Model
Keele, Luke
Stevenson, Randy

Uploaded 
12082014

Keywords 
causal inference regression DAG

Abstract 
One of the most common identification strategies in political science is selection on observables. Under this strategy, analysts assume that they observed enough covariates to make treatment status asif random. Adjustments are then made for observed confounders through statistical methods such as regression or matching. Under adjustment methods such as matching or inverse probability weighting, coefficients for control variables are treated as nuisance parameters and are not directly estimated. This is in direct contrast to regression approaches where estimated parameters are observed for all covariates. Analysts often find it tempting to give a causal interpretation to all the parameters in such regression models, which is not possible under the controls as nuisance parameter approach. In this paper, we illustrate the dangers of treating all the parameters in a regression model as causal parameters. Using Directed Acyclic Graphs, we show how even if some effects are identified in a regression model, many estimated parameters do not represent causal effects or may be direct effects. The general recommendation is for analysts to attempt to identify a single effect and limit interpretation of models to that effect. 

48 
Paper

Shaken, Not Stirred: Evidence on Ballot Order Effects from the California Alphabet Lottery, 1978  2002
Ho, Daniel E.
Imai, Kosuke

Uploaded 
02022004

Keywords 
ballots elections causal inference natural experiment randomization fisher test partisan cue

Abstract 
We analyze a natural experiment to answer the longstanding question of
whether the name order of candidates on ballots affects election outcomes.
Since 1975, California law has mandated randomizing the ballot order with a
lottery, where alphabet letters would be shaken vigorously and selected
from a container. Previous studies, relying overwhelmingly on nonrandomized
data, have yielded conflicting results about whether ballot order effects
even exist. Using improved statistical methods, our analysis of statewide
elections from 1978 to 2002 reveals that in general elections ballot order
has a significant impact only on minor party candidates and candidates
for nonpartisan offices. In primaries, however, being listed first benefits
everyone. In fact, ballot order might have changed the winner in roughly
nine percent of all primary races examined. These results are largely
consistent with a theory of partisan cuing. We propose that all
electoral jurisdictions randomize ballot order to minimize ballot effects. 

49 
Paper

Empirical Modeling Strategies for Spatial Interdependence: OmittedVariable vs. Simultaneity Biases
Hays, Jude
Franzese, Robert

Uploaded 
07242004

Keywords 
Spatial Lag Models Diffusion Omitted Variable Bias Simultaneity Bias

Abstract 
Scholars recognize that timeseriescrosssection data typically correlate across time and space, yet they tend to model temporal dependence directly while addressing spatial interdependence solely as nuisance to be “corrected” (FGLS) or to which to be “robust” (PCSE). We demonstrate that directly modeling spatial interdependence is methodologically superior, offering efficiency gains and generally helping avoid biased estimates even of “nonspatial” effects. We first specify empirical models representing two modern approaches to comparative and international political economy: (contextconditional) openeconomy comparative politicaleconomy (i.e., common stimuli, varying responses) and international politicaleconomy, which implies interdependence (plus closedeconomy and orthogonalopeneconomy predecessors). Then we evaluate four estimators—nonspatial OLS, spatial OLS, spatial 2SLSIV, and spatial ML—for analyzing such models in spatially interdependent data. Nonspatial OLS suffers from potentially severe omittedvariable bias, tending to inflate estimates of commonstimuli effects especially. Spatial OLS, which specifies interdependence directly via spatial lags, dramatically improves estimates but suffers a simultaneity bias, which can be appreciable under strong interdependence. Spatial 2SLSIV, which instruments for spatial lags of dependent variables with spatial lags of independent variables, yields unbiased and reasonably efficient estimates of both commonstimuli and diffusion effects, when its conditions hold: large samples and fully exogenous instruments. A tradeoff thus arises in practice between biasedbutefficient spatial OLS and consistent (or, at least, lessbiased) butinefficient spatial 2SLSIV. Spatial ML produces good estimates of nonspatial effects under all conditions but is computationally demanding and tends to underestimate the strength of interdependence, appreciably so in smallN samples and when the true diffusionstrength is modest. We also explore the standarderror estimates from these four procedures, finding sizable inaccuracies by each estimator under differing conditions, and PCSE’s do not necessarily reduce these inaccuracies. By an accuracyofreportedstandarderrors criterion, 2SLSIV seems to dominate. Finally, we explore the spatial 2SLSIV estimator under varying patterns of interdependence and endogeneity, finding that its estimates of diffusion strength suffer only when a condition we call crossspatial endogeneity, wherein dependent variables (y’s) in some units cause explanatory variables (x’s) in others, prevails. 

