In recent decades, scholars have increasingly emphasized that variables related to perception and cognitive bias play a significant role in the dynamics of intractable conflicts. In the case of the Israeli-Palestinian conflict in particular, social psychologist Daniel Bar-Tal has emphasized the need for adversarial societies to develop suitable psychological conditions to cope with their conflict situation. However, very little work has focused on explicating just how perceptual biases operate as key mechanisms underpinning the persistence of the conflict. This paper seeks to shed light on the operation of psychological processes, including cognitive consistency, attribution bias, mirror image, and self-categorization, in the Israeli-Palestinian conflict. The paper explicates how these psychological concepts and models are relevant to the study of the conflict, and ultimately argues that existing theories emphasizing domestic political institutions and international factors like external intervention only partially explain the continuation of the Israeli-Palestinian conflict. To fully understand the persistence of the conflict over time, a cognitive approach is crucial.

During a research visit to Israel nearly two years ago, I interviewed leaders of various ethnic conflict resolution groups and the academics who evaluate them. When asked to describe their biggest challenge, all mentioned this puzzle: why doesn't the attitude and behavioral change generated in their conflict resolution groups "stick" with some individualsi They reported that nearly all individuals who completed their programs positively changed their attitudes and behaviors towards the ethnic outgroup, yet after a few months the effect was gone. This paper presents some of the results of the project that grew around that puzzle, with the goal of generating knowledge that will be used to design ethnic conflict resolution interventions with more lasting impact. In particular, it provides initial answers to the following question: What individual-level processes motivate individual acts of interethnic aggression, and how can these processes be alteredl After presenting new data on the widespread occurrence of acts of interethnic aggression between Arab-Israelis and Jewish-Israelis within Israel's pre-1967 borders and the municipality of Jerusalem, the paper builds on theories from scholars in philosophy (Buber, 2000), social psychology (Anderson and Bushman, 2002; Bandura, 1991, 1999; Leyens et al., 2001; Struch and Schwartz, 1989; Bar-Tal, 2007), Middle Eastern Studies (Lustick, 1980; Jamal, 2008a,b), and political science (Fearon and Laitin, 1996; Varshney, 2002)--and on findings from a year of interviews in Israel--to detail a new theory of interethnic aggression. It then presents the results of a test of this theory using original data from two interethnic aggression experiments recently conducted with National Science Foundation (NSF) and Fulbright funds in Israel--a large-n survey experiment and a laboratory aggression experiment--using Arab-Israeli and Jewish-Israeli subjects. The results of these experiments, the first in political science to gather actual individual-level interethnic aggression data, suggest a different approach to individual-level ethnic conflict resolution programs than that currently practiced.

Dramatic historical turning-points reduce social scientists' ability to use past patterns to predict subsequent events. We trace this ability through the study of more than 10,000 Reuters news stories on Israeli-Palestinian interactions from the period 1979 to 2005, which have been systematically coded to provide a rough summary of positive/negative interactions on a daily basis. Using rolling windows, we show that the accuracy of out-of-sample forecasting fluctuates tremendously during this period, and that the errors of these forecasts are particularly prominent just after major events such as the first and second intifadas. Over the months following these dramatic moments, as new routines of interaction develop, forecasting errors decline. These findings are produced consistently regardless of which time-series methods is used: vector autoregression (VAR), autoregressive integrated moving average (ARIMA), and seemingly unrelated regressions (SUREG). This analysis is the first of its kind -- the field of forecasting studies, including other analyses of Israeli-Palestinian interactions, focuses on overall model fit, rather than variation in forecasting errors. We propose that this new approach speaks to the limits of social scientific prediction at moments when existing patterns of behavior have changed so dramatically that people cannot know what comes next. Moments of routine behavior may be quite well predicted by previous behavior, but moments of non-routine behavior may lie beyond the powers of prediction.

The Advocacy Coalition Framework (ACF) is applied to understand and simplify policy creation and change within the dynamics of a policy subsystem. The policy subsystem examined here is the U.S. decision to support the creation of Israel. The ACF is applied to identify the policy core beliefs, coalition members, coalitions and their relative stability within the subsystem from 1922 to 1944. 1922 marks the first U.S. policy on the issue of support for Israel, and 1944 is the last time a resolution concerning the creation of Israel was debated by Congress publicly before 1948. To determine the policy beliefs and coalition membership, qualitative content analysis was conducted of statements made during U.S. Congressional hearings held in 1922 and 1944. These statements were then analyzed using Euclidian distance measures to create clusters of members of coalitions based on their policy core beliefs. Both coalitions and the policy core beliefs were tested for stability over time. The results found that within the policy subsystem the lineup of allies and adversaries was relatively stable over two decades. In addition, the pro-Zionist coalition became dominant over time and had an increase in policy core belief agreement, while the level of agreement in the pro-Arab coalition decreased. This research provides us a new level of analysis of the coalitions that lobbied Congress both in favor of and opposed to the creation of Israel, as well as applying this policy theory for the first time to a historical foreign policy case.

Dramatic historical turning-points reduce social scientists' ability to use past patterns to predict subsequent events. We trace this ability through the study of more than 10,000 Reuters news stories on Israeli-Palestinian interactions from the period 1979 to 2005, which have been systematically coded to provide a rough summary of positive/negative interactions on a daily basis. Using rolling windows, we show that the accuracy of out-of-sample forecasting fluctuates tremendously during this period, and that the errors of these forecasts are particularly prominent just after major events such as the first and second intifadas. Over the months following these dramatic moments, as new routines of interaction develop, forecasting errors decline. These findings are produced consistently regardless of which time-series methods is used: vector autoregression (VAR), autoregressive integrated moving average (ARIMA), and seemingly unrelated regressions (SUREG). This analysis is the first of its kind -- the field of forecasting studies, including other analyses of Israeli-Palestinian interactions, focuses on overall model fit, rather than variation in forecasting errors. We propose that this new approach speaks to the limits of social scientific prediction at moments when existing patterns of behavior have changed so dramatically that people cannot know what comes next. Moments of routine behavior may be quite well predicted by previous behavior, but moments of non-routine behavior may lie beyond the powers of prediction.