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Farmers versus Financiers: Sectoral Logrolling and the Political Economy of Overvaluation
Unformatted Document Text:  Farmers versus Financiers: Sectoral Logrolling and the Political Economy of Overvaluation ∗ David A. Steinberg Department of Political Science Northwestern University ## email not listed ## Abstract: The goal of this paper is to explain why overvalued currencies are so common in developing countries. Overvaluation is a puzzling outcome: it contradicts the common assumption that states want to maximize net exports; and it has harmful economic effects, such as low growth and financial crises. The sectoral logrolling theory developed in the paper argues that overvaluation is common because pivotal actors benefit from the side-effects of overvaluation, such as currency stability and high government spending. Logrolling creates support for overvaluation among actors that care little about currency valuation. By contrast, the pro-undervaluation coalition cannot succeed politically because they lack the resources to attract supporters. The theory predicts that undervaluation is likely only when advocates of undervaluation are politically influential and formal political institutions prevent logrolling from taking place. I also hypothesize that political institutions affect the extent to which overvaluation coincides with fixed exchange rates. The statistical tests, based on a panel data set of developing countries, support these hypotheses.  Prepared for delivery at the 2006 Annual Meeting of the American Political Science Association, August 30th-September 3, 2006. Copyright by the American Political Science Association. A previous version of this paper was presented at the 64 th Midwest Political Science Association conference, Chicago, Illinois, April 20-23, 2006. This research was funded by a doctoral fellowship from the Social Sciences and Humanities Research Council of Canada. I am indebted to those who supplied me with their datasets. For helpful comments, I thank Sebastian Karcher, James Mahoney, Angela O’Mahony, Louis Pauly, Michael Pisa, Reuel Rogers, and Ben Ross Schneider. Sean Gailmard, Victor Shih and Hendrik Spruyt deserve special thanks for detailed feedback and guidance

Authors: Steinberg, David.
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Farmers versus Financiers: Sectoral Logrolling and the
Political Economy of Overvaluation
David A. Steinberg
Department of Political Science
Northwestern University
Abstract: The goal of this paper is to explain why overvalued currencies are so common
in developing countries. Overvaluation is a puzzling outcome: it contradicts the common
assumption that states want to maximize net exports; and it has harmful economic effects,
such as low growth and financial crises. The sectoral logrolling theory developed in the
paper argues that overvaluation is common because pivotal actors benefit from the side-
effects of overvaluation, such as currency stability and high government spending.
Logrolling creates support for overvaluation among actors that care little about currency
valuation. By contrast, the pro-undervaluation coalition cannot succeed politically
because they lack the resources to attract supporters. The theory predicts that
undervaluation is likely only when advocates of undervaluation are politically influential
and formal political institutions prevent logrolling from taking place. I also hypothesize
that political institutions affect the extent to which overvaluation coincides with fixed
exchange rates. The statistical tests, based on a panel data set of developing countries,
support these hypotheses.
Prepared for delivery at the 2006 Annual Meeting of the American Political Science Association, August
30th-September 3, 2006. Copyright by the American Political Science Association. A previous version of
this paper was presented at the 64
th
Midwest Political Science Association conference, Chicago, Illinois,
April 20-23, 2006. This research was funded by a doctoral fellowship from the Social Sciences and
Humanities Research Council of Canada. I am indebted to those who supplied me with their datasets. For
helpful comments, I thank Sebastian Karcher, James Mahoney, Angela O’Mahony, Louis Pauly, Michael
Pisa, Reuel Rogers, and Ben Ross Schneider. Sean Gailmard, Victor Shih and Hendrik Spruyt deserve
special thanks for detailed feedback and guidance


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