Atin Basuchoudhary

ON ETHNIC CONFLICT AND THE ORIGINS OF TRANSNATIONAL TERRORISM

Using the ITERATE dataset, we explore the origins of transnational terrorist activity, from 1982 through 1997, in 118 countries. We model terrorism, not as a function of a nation’s ethnic, religious or linguistic fractionalization, but as an independent measure of perceived ethnic tensions. When we control for institutional quality, evidence that political rights and civil liberties mitigate the terrorism‐producing effects of ethnic tensions exists only since 1990. Economic freedoms, on the other hand, robustly reduce the number of terrorist attacks originating in ethnically tense societies.

A Decision Analysis Approach to Solving the Signaling Game

Decision analysis has traditionally been applied to choices under uncertainty involving a single decision maker. Game theory has been applied to solving games of strategic interaction between two or more players. Building upon recent work of van Binsbergen and Marx (van Binsbergen, J. H., L. M. Marx. 2007. Exploring relations between decision analysis and game theory. Decision Anal. 4(1) 32--40), this paper defines a modified decision-theoretic approach to solving games of strategic interaction between two players. Using this method, the choices of the two players are modeled with separate decision trees comprised entirely of chance nodes. Optimal policies are reflected in the probabilities in the decision trees of each player. In many cases, the Nash equilibrium strategy for each player can be obtained by rolling back the opponents decision tree. Results are demonstrated for the multistage signaling game, which is difficult to model using decision nodes to represent strategies, as in the approach of van Binsbergen and Marx.

Civilization and the Evolution of Short Sighted Agents

We model an assurance game played within a population with two types of individuals -- short-sighted and foresighted. Foresighted people have a lower discount rate than short sighted people. These phenotypes interact with each other. We define the persistent interaction of foresighted people with other foresighted people as a critical element of civilization while the interaction of short sighted people with other short sighted people as critical to the failure of civilization. We show that whether the short sighted phenotype will be an evolutionary stable strategy (and thus lead to the collapse of civilization) depends on the initial proportion of short sighted people relative to people with foresight as well as their relative discount rates. Further we explore some comparative static results that connect the probability of the game continuing and the relative size of the two discount rates to the likelihood that civilization will collapse.

Price discrimination and resale: A classroom experiment

The authors present a classroom experiment designed to illustrate key concepts of third-degree price discrimination. By participating as buyers and sellers, students actively learn (1) how group pricing differs from uniform pricing, (2) how resale between buyers limits a sellers ability to price discriminate, and (3) how preventing price discrimination might reduce welfare. The exercise challenges sellers to set optimal prices against unknown demand curves by using a concrete story of pharmaceutical pricing to American and Mexican consumers. By working through profit calculations, students arrive at the optimal seller prices in three different settings: uniform pricing, price discrimination to two groups, and price discrimination to two groups who can resell to each other. The experimental design encourages students to converge reliably to the theoretical predictions. Classroom discussion can focus on real-world examples of price discrimination and on regulatory policy questions in industrial organization and international trade.

The evolution of revolution: Is splintering inevitable?

We use an evolutionary model to study splintering within rebel groups. We assume that rebels possess cultural traits that encourage cooperation, defection (splintering), or a trigger behavior like Tit-For-Tat. We characterize the dynamic process by which rebels’ discount rates determine whether splintering will occur in the rebel population even when cooperation is otherwise efficient. The results suggest that political action by governments that make rebels impatient also increases the likelihood of rebel group splintering. This may be counterproductive from a government’s point of view. Our article closes a gap in the literature by providing a theoretical model for how rebel groups form. Policies that affect the patience of rebels and change the cultural context within rebel groups influence the likelihood of rebel group splintering. This article’s contribution to the literature is twofold. First, it applies an established modeling approach to understand how even otherwise cohesive rebellions can splinter as a consequence of exogenous shocks that change rebels’ time horizons. Second, we highlight how cultural context can influence this splintering process.

Are People Sometimes Too Honest? Increasing, Decreasing, and Negative Returns to Honesty

We show that sender honesty can hurt receivers in simple signaling games. The receiver faces a trade-off between its ability to work with senders and the quality of information it can get and use from them. Our example also contradicts recent work suggesting that returns to honesty should be increasing. Positive, increasing returns are restored in our model if the receiver can precommit.

Reversal of fortune: the politics and economics of the superconducting supercollider *

Congress approved the superconducting supercollider (SSC), but later cut all funding after construction for the project had begun. We claim that this reversal was due, in part, to a problem of time inconsistency. Representatives from states in contention to receive the project had an incentive to support it early in the process. Once Texas was chosen as the SSC site, the other contender states had a greatly diminished incentive to continue to support it. Our empirical results show that the probability of switching from ‘for’ to ‘against’ the project is significantly higher for representatives from the former contender states.

Predicting a Country’s Growth: A First Look

In this chapter, we run different algorithm techniques to identify the algorithms that best predict growth. We show how machine learning can be used to validate different growth models. We suggest that validated algorithms enhance the confidence academics should place on any given theoretical growth model. We then show how machine learning can help researchers understand what kinds of concepts may make theoretical growth models more complete.

Predicting Recessions: What We Learn from Widening the Goalposts

In this chapter, we move our focus from economic growth to trying to predict a related target—economic recessions. We continue to use the “usual suspect” growth variables to check whether these variables are better at predicting recessions. We show how prediction performance of algorithms differs widely depending on the type of prediction criteria. We can, however, identify some of the most salient predictors of recessions. These suggest that fiscal policy may generally be better at combating recessions. Moreover, these predictors have non-linear effects on the likelihood of recessions which suggests that there may be no silver bullet for combating recessions. Last, the sorts of variables that influence economic growth also influence the likelihood of a recession. This suggest that economic growth probably should not be studied separately from recessions.

Why This Book

In this chapter, we lay out our plan for the book and the argument for the advantages of machine learning. ML algorithms use out of sample validation to identify which variables matter most for economic growth and recessions without making any heroic assumptions about the underlying distribution of the variables. Thus, it avoids problems of endogeneity. It also helps with the missing data problem by imputing missing data with validated algorithms. However, most of all, these algorithms can eliminate variables that are unlikely to be causal. Policy makers can therefore get a sense of the most important policy levers to change the path of growth.