Curtis S Signorino
Biographic Data
| ID | 1201729 |
|---|---|
| NAME | Curtis S Signorino |
| GIVEN NAMES | Curtis S |
| FAMILY NAME | Signorino |
| SIGNATURE | SIGNORINO C S |
| AFFILIATIONS | University of Rochester |
| VERIFIED | No |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 1740 |
| AUTHOR COUNT | 17 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1993 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 10 |
Detecting and Correcting for Separation in Strategic Choice Models
Separation or “perfect prediction” is a common problem in discrete choice models that, in practice, leads to inflated point estimates and standard errors. Standard statistical packages do not provide clear advice on how to correct these problems. Furthermore, separation can go completely undiagnosed in fitting advanced models that optimize a user-supplied log-likelihood rather than relying on pre-programmed estimation procedures. In this paper, w…
Knowing one’s future preferences: A correlated agent model with Bayesian updating
We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, ρ…
Reply to “Time is Not A Theoretical Variable
We thank Neal Beck for his comments. In general, there is little difference in our theoretical and practical positions. We all agree that in some applications, time dummies can be problematic; controlling for temporal dependence is important for less-biased estimation of the coefficients on our substantive regressors; a smoothed function of time (whether via a cubic polynomial or spline) is a useful way to model temporal dependence in grouped bin…
Discriminating Methods: Tests for Non-Nested Discrete Choice Models
We consider the problem of choosing between rival statistical models that are non-nested in terms of their functional forms. We assess the ability of two tests, one parametric and one distribution-free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, to varying degrees, able to discriminate between strategic and non-strategic discrete choice models. The distribution-free test appears to have great…
Back to the Future: Modeling Time Dependence in Binary Data
Since Beck, Katz, and Tucker (1998), the standard method for modeling time dependence in binary data has been to incorporate time dummies or splined time in logistic regressions. Although we agree with the need for modeling time dependence, we demonstrate that time dummies can induce estimation problems due to separation. Splines do not suffer from these problems. However, the complexity of splines has led substantive researchers (1) to use knot …
Statistical Backwards Induction: A Simple Method for Estimating Recursive Strategic Models
We present a simple method for estimating regressions based on recursive extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors. To illustrate the method, we replicate L…
On Formal Theory and Statistical Methods: A Response to Carrubba, Yuen, and Zorn
The recent article by Carrubba, Yuen, and Zorn (2007) (CYZ) attempts to relate the strategic random utility models in Signorino (1999, 2002, 2003) and in Signorino and Yilmaz (2003) to existing game theory practice and to existing statistical techniques. It contributes to this literature by reminding us that comparative statics analysis can be applied to the equilibria of these models. There are a number of claims in CYZ, however, that require cl…
A Unified Theory and Test of Extended Immediate Deterrence
We present a unified theory and test of extended immediate deterrence—unified in the sense that we employ our theoretical deterrence model as our statistical model in the empirical analysis. The theoretical model is a straightforward formalization of the deterrence logic in Huth (1988) and Huth and Russett (1984), coupled with private information concerning utilities. Our statistical analysis suggests that the attacker and defender's decisions ar…
Structure and Uncertainty in Discrete Choice Models
Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncert…
Strategic Misspecification in Regression Models
Common regression models are often structurally inconsistent with strategic interaction.We demonstrate that this "strategic misspecification" is really an issue of structural (or functional form) misspecification.The misspecification can be equivalently written as a form of omitted variable bias, where the omitted variables are nonlinear terms arising from the players' expected utility calculations and often from data aggregation.We characterize …
Strategy and Selection in International Relations
It is widely recognized that many of the samples we use for statistical analysis in international politics are the result of some selection process. Not surprisingly, selection models are becoming increasingly popular. At the same time, the role of strategic interaction has begun to play a more important role in statistical analyses. However, it has not been clear how statistical strategic models and selection models relate to each other, or what…
Aggregation Among Binary, Count, and Duration Models: Estimating the Same Quantities from Different Levels of Data
Binary, count, and duration data all code discrete events occurring at points in time. Although a single data generation process can produce all 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 used only for cou…
Tau-b or Not Tau-b: Measuring the Similarity of Foreign Policy Positions
The pattern of alliances among states is commonly assumed to reflect the extent to which states have common or conflicting security interests. For the past twenty years, Kendall's τb has been used to measure the similarity of nations' "portfolios" of alliance commitments. Widely employed indicators of systemic polarity, state utility, and state risk propensity all rely on τb. We demonstrate that τb is inappropriate for measuring the similarity of…
Strategic Interaction and the Statistical Analysis of International Conflict
Although strategic interaction is at the heart of most international relations theory, it has largely been missing from much empirical analysis in the field. Typical applications of logit and probit to theories of international conflict generally do not capture the structure of the strategic interdependence implied by those theories. I demonstrate how to derive statistical discrete choice models of international conflict that directly incorporate…
The Generalization in the Generalized Event Count Model, with Comments on Achen, Amato, and Londregan
We use an analogy with the normal distribution and linear regression to demonstrate the need for the Generalized Event Count (GEC) model. We then show how the GEC provides a unified framework within which to understand a diversity of distributions used to model event counts, and how to express the model in one simple equation. Finally, we address the points made by Christopher Achen, Timothy Amato, and John Londregan. Amato's and Londregan's argu…
Simulating International Cooperation under Uncertainty: The Effects of Symmetric and Asymmetric Noise
The repeated prisioner's dilemma is representative of a broad range of situations in international security and trade. This article examines the effects of asymmetric noise on the emergence and maintenance of cooperation under such conditions. The results show that positive and negative asymmetric noise have very different effects on strategy performance. For forgiving strategies, positive noise provides a stimulus out of perpetual defection or u…
A Correction for an Underdispersed Event Count Probability Distribution
We demonstrate that the expected value and variance commonly given for a well-known probability distribution are incorrect. We also provide corrected versions and report changes in a computer program to account for the known practical uses of this distribution.The probability distribution in question, named the continuous parameter binomial (CPB) by King (1989a), has been known for at least six decades. The publications that reported the moments …
Back to the Future: Modeling Time Dependence in Binary Data
Since Beck, Katz, and Tucker (1998), the standard method for modeling time dependence in binary data has been to incorporate time dummies or splined time in logistic regressions. Although we agree with the need for modeling time dependence, we demonstrate that time dummies can induce estimation problems due to separation. Splines do not suffer from these problems. However, the complexity of splines has led substantive researchers (1) to use knot …
Tau-b or Not Tau-b: Measuring the Similarity of Foreign Policy Positions
The pattern of alliances among states is commonly assumed to reflect the extent to which states have common or conflicting security interests. For the past twenty years, Kendall's τb has been used to measure the similarity of nations' "portfolios" of alliance commitments. Widely employed indicators of systemic polarity, state utility, and state risk propensity all rely on τb. We demonstrate that τb is inappropriate for measuring the similarity of…
Strategic Interaction and the Statistical Analysis of International Conflict
Although strategic interaction is at the heart of most international relations theory, it has largely been missing from much empirical analysis in the field. Typical applications of logit and probit to theories of international conflict generally do not capture the structure of the strategic interdependence implied by those theories. I demonstrate how to derive statistical discrete choice models of international conflict that directly incorporate…
Strategic Misspecification in Regression Models
Common regression models are often structurally inconsistent with strategic interaction.We demonstrate that this "strategic misspecification" is really an issue of structural (or functional form) misspecification.The misspecification can be equivalently written as a form of omitted variable bias, where the omitted variables are nonlinear terms arising from the players' expected utility calculations and often from data aggregation.We characterize …
Structure and Uncertainty in Discrete Choice Models
Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncert…
Statistical Backwards Induction: A Simple Method for Estimating Recursive Strategic Models
We present a simple method for estimating regressions based on recursive extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors. To illustrate the method, we replicate L…
A Unified Theory and Test of Extended Immediate Deterrence
We present a unified theory and test of extended immediate deterrence—unified in the sense that we employ our theoretical deterrence model as our statistical model in the empirical analysis. The theoretical model is a straightforward formalization of the deterrence logic in Huth (1988) and Huth and Russett (1984), coupled with private information concerning utilities. Our statistical analysis suggests that the attacker and defender's decisions ar…
Strategy and Selection in International Relations
It is widely recognized that many of the samples we use for statistical analysis in international politics are the result of some selection process. Not surprisingly, selection models are becoming increasingly popular. At the same time, the role of strategic interaction has begun to play a more important role in statistical analyses. However, it has not been clear how statistical strategic models and selection models relate to each other, or what…
Aggregation Among Binary, Count, and Duration Models: Estimating the Same Quantities from Different Levels of Data
Binary, count, and duration data all code discrete events occurring at points in time. Although a single data generation process can produce all 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 used only for cou…
Simulating International Cooperation under Uncertainty: The Effects of Symmetric and Asymmetric Noise
The repeated prisioner's dilemma is representative of a broad range of situations in international security and trade. This article examines the effects of asymmetric noise on the emergence and maintenance of cooperation under such conditions. The results show that positive and negative asymmetric noise have very different effects on strategy performance. For forgiving strategies, positive noise provides a stimulus out of perpetual defection or u…
Knowing one’s future preferences: A correlated agent model with Bayesian updating
We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, ρ…
Discriminating Methods: Tests for Non-Nested Discrete Choice Models
We consider the problem of choosing between rival statistical models that are non-nested in terms of their functional forms. We assess the ability of two tests, one parametric and one distribution-free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, to varying degrees, able to discriminate between strategic and non-strategic discrete choice models. The distribution-free test appears to have great…
On Formal Theory and Statistical Methods: A Response to Carrubba, Yuen, and Zorn
The recent article by Carrubba, Yuen, and Zorn (2007) (CYZ) attempts to relate the strategic random utility models in Signorino (1999, 2002, 2003) and in Signorino and Yilmaz (2003) to existing game theory practice and to existing statistical techniques. It contributes to this literature by reminding us that comparative statics analysis can be applied to the equilibria of these models. There are a number of claims in CYZ, however, that require cl…
The Generalization in the Generalized Event Count Model, with Comments on Achen, Amato, and Londregan
We use an analogy with the normal distribution and linear regression to demonstrate the need for the Generalized Event Count (GEC) model. We then show how the GEC provides a unified framework within which to understand a diversity of distributions used to model event counts, and how to express the model in one simple equation. Finally, we address the points made by Christopher Achen, Timothy Amato, and John Londregan. Amato's and Londregan's argu…
Reply to “Time is Not A Theoretical Variable
We thank Neal Beck for his comments. In general, there is little difference in our theoretical and practical positions. We all agree that in some applications, time dummies can be problematic; controlling for temporal dependence is important for less-biased estimation of the coefficients on our substantive regressors; a smoothed function of time (whether via a cubic polynomial or spline) is a useful way to model temporal dependence in grouped bin…
Detecting and Correcting for Separation in Strategic Choice Models
Separation or “perfect prediction” is a common problem in discrete choice models that, in practice, leads to inflated point estimates and standard errors. Standard statistical packages do not provide clear advice on how to correct these problems. Furthermore, separation can go completely undiagnosed in fitting advanced models that optimize a user-supplied log-likelihood rather than relying on pre-programmed estimation procedures. In this paper, w…
A Correction for an Underdispersed Event Count Probability Distribution
We demonstrate that the expected value and variance commonly given for a well-known probability distribution are incorrect. We also provide corrected versions and report changes in a computer program to account for the known practical uses of this distribution.The probability distribution in question, named the continuous parameter binomial (CPB) by King (1989a), has been known for at least six decades. The publications that reported the moments …
A Correction for an Underdispersed Event Count Probability Distribution
We demonstrate that the expected value and variance commonly given for a well-known probability distribution are incorrect. We also provide corrected versions and report changes in a computer program to account for the known practical uses of this distribution.The probability distribution in question, named the continuous parameter binomial (CPB) by King (1989a), has been known for at least six decades. The publications that reported the moments …
The Generalization in the Generalized Event Count Model, with Comments on Achen, Amato, and Londregan
We use an analogy with the normal distribution and linear regression to demonstrate the need for the Generalized Event Count (GEC) model. We then show how the GEC provides a unified framework within which to understand a diversity of distributions used to model event counts, and how to express the model in one simple equation. Finally, we address the points made by Christopher Achen, Timothy Amato, and John Londregan. Amato's and Londregan's argu…
Simulating International Cooperation under Uncertainty: The Effects of Symmetric and Asymmetric Noise
The repeated prisioner's dilemma is representative of a broad range of situations in international security and trade. This article examines the effects of asymmetric noise on the emergence and maintenance of cooperation under such conditions. The results show that positive and negative asymmetric noise have very different effects on strategy performance. For forgiving strategies, positive noise provides a stimulus out of perpetual defection or u…
Tau-b or Not Tau-b: Measuring the Similarity of Foreign Policy Positions
The pattern of alliances among states is commonly assumed to reflect the extent to which states have common or conflicting security interests. For the past twenty years, Kendall's τb has been used to measure the similarity of nations' "portfolios" of alliance commitments. Widely employed indicators of systemic polarity, state utility, and state risk propensity all rely on τb. We demonstrate that τb is inappropriate for measuring the similarity of…
Strategic Interaction and the Statistical Analysis of International Conflict
Although strategic interaction is at the heart of most international relations theory, it has largely been missing from much empirical analysis in the field. Typical applications of logit and probit to theories of international conflict generally do not capture the structure of the strategic interdependence implied by those theories. I demonstrate how to derive statistical discrete choice models of international conflict that directly incorporate…
Aggregation Among Binary, Count, and Duration Models: Estimating the Same Quantities from Different Levels of Data
Binary, count, and duration data all code discrete events occurring at points in time. Although a single data generation process can produce all 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 used only for cou…
Strategy and Selection in International Relations
It is widely recognized that many of the samples we use for statistical analysis in international politics are the result of some selection process. Not surprisingly, selection models are becoming increasingly popular. At the same time, the role of strategic interaction has begun to play a more important role in statistical analyses. However, it has not been clear how statistical strategic models and selection models relate to each other, or what…
Structure and Uncertainty in Discrete Choice Models
Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncert…
Strategic Misspecification in Regression Models
Common regression models are often structurally inconsistent with strategic interaction.We demonstrate that this "strategic misspecification" is really an issue of structural (or functional form) misspecification.The misspecification can be equivalently written as a form of omitted variable bias, where the omitted variables are nonlinear terms arising from the players' expected utility calculations and often from data aggregation.We characterize …
A Unified Theory and Test of Extended Immediate Deterrence
We present a unified theory and test of extended immediate deterrence—unified in the sense that we employ our theoretical deterrence model as our statistical model in the empirical analysis. The theoretical model is a straightforward formalization of the deterrence logic in Huth (1988) and Huth and Russett (1984), coupled with private information concerning utilities. Our statistical analysis suggests that the attacker and defender's decisions ar…
On Formal Theory and Statistical Methods: A Response to Carrubba, Yuen, and Zorn
The recent article by Carrubba, Yuen, and Zorn (2007) (CYZ) attempts to relate the strategic random utility models in Signorino (1999, 2002, 2003) and in Signorino and Yilmaz (2003) to existing game theory practice and to existing statistical techniques. It contributes to this literature by reminding us that comparative statics analysis can be applied to the equilibria of these models. There are a number of claims in CYZ, however, that require cl…
Statistical Backwards Induction: A Simple Method for Estimating Recursive Strategic Models
We present a simple method for estimating regressions based on recursive extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors. To illustrate the method, we replicate L…
Reply to “Time is Not A Theoretical Variable
We thank Neal Beck for his comments. In general, there is little difference in our theoretical and practical positions. We all agree that in some applications, time dummies can be problematic; controlling for temporal dependence is important for less-biased estimation of the coefficients on our substantive regressors; a smoothed function of time (whether via a cubic polynomial or spline) is a useful way to model temporal dependence in grouped bin…
Discriminating Methods: Tests for Non-Nested Discrete Choice Models
We consider the problem of choosing between rival statistical models that are non-nested in terms of their functional forms. We assess the ability of two tests, one parametric and one distribution-free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, to varying degrees, able to discriminate between strategic and non-strategic discrete choice models. The distribution-free test appears to have great…
Back to the Future: Modeling Time Dependence in Binary Data
Since Beck, Katz, and Tucker (1998), the standard method for modeling time dependence in binary data has been to incorporate time dummies or splined time in logistic regressions. Although we agree with the need for modeling time dependence, we demonstrate that time dummies can induce estimation problems due to separation. Splines do not suffer from these problems. However, the complexity of splines has led substantive researchers (1) to use knot …
Knowing one’s future preferences: A correlated agent model with Bayesian updating
We generalize two classes of statistical sequential incomplete information games: (1) those resembling typical signaling games, in which a single agent represents each player, allowing for information to be revealed about future play; and (2) those in which each player is represented by a set of independent agents, where moves do not reveal private information. The generalized model we develop, the Correlated Agent Model, relies on a parameter, ρ…
Detecting and Correcting for Separation in Strategic Choice Models
Separation or “perfect prediction” is a common problem in discrete choice models that, in practice, leads to inflated point estimates and standard errors. Standard statistical packages do not provide clear advice on how to correct these problems. Furthermore, separation can go completely undiagnosed in fitting advanced models that optimize a user-supplied log-likelihood rather than relying on pre-programmed estimation procedures. In this paper, w…
Computer Science (16 works) · Econometrics (15 works) · Mathematics (13 works) · Statistics (12 works) · Economics (9 works) · Artificial Intelligence (7 works) · Mathematical economics (6 works) · Microeconomics (5 works) · Political Conflict and Governance (5 works) · Political science (5 works)