model in the first stage, and we rely on the same set of instruments for all types of interventions. The second stage uses the estimated probabilities.

Our instruments draw from different strands of literature. First, we exploit ideas according to which bailouts occur because of doubts about the accuracy with which investors can assess the value of bank assets. Second, we rely on arguments claiming that the electoral cycle and the political environment play a role for the decision to bail out banks. Third, we use a characteristic of the institutional environment.

Flannery, Kwan, and Nimalendran (2013) highlight interventions into distressed banking systems are founded on the belief that markets are unable to differentiate between sound and unsound institutions during crises. This spike in information asymmetries motivates bailout programs such as the TARP. To capture opacity, we focus on asset composition. Flannery et al. (2013) propose a bank‘s loan and security portfolio composition are informative about opacity. We therefore home in on different loan categories, scaled by net loans. Loans are separated into residential mortgage loans, other consumer and retail loans, corporate and commercial loans, and other loans. While residential mortgage loans and consumer and retail loans are standardized and should reduce opacity, corporate and commercial loans are difficult to value. We expect them to increase opacity and correlate positively with interventions. The remaining lending categories are grouped together as other loans. For security portfolio composition, we focus on available for sales and held to maturity securities, scaled by total securities. While the former are marked at fair value and should reduce opacity and the likelihood of interventions, the latter are reported at amortized cost, and make the balance sheet more opaque. Brown and Dinc (2005) show most bailouts occur 7-12 months after elections, whereas the period before an election reduces the likelihood of interventions. Two instruments capture the electoral cycle. The first one is a dummy that takes on the value of one in the year a parliamentary election takes place, and the second one provides information about the time (in years) since the last parliamentary election.<sup>21</sup> Both variables should correlate negatively with interventions.<sup>22</sup> A further instrument provides information about the orientation of the largest government party. We use a dummy that takes on the value of one if the largest government party has a right-wing orientation. Governments led by such parties focus on market-oriented policies to increase their chances of re-election (Bortolotti and Faccio (2009). Moreover, their partisan orientation impacts bailout propensities. While left-wing governments are keen to intervene into the economy to preserve jobs, right-wing governments tend to oppose such actions (Garrett and Lange (1991)). Our last instrument is an index about prompt

> 21 We collect this information from _Parties and Elections in Europe_ , the _Center on Democratic Performance (Election results archive)_ , and from _Electionresources.org_ The website sources are <u>http://www.parties-andelections.de/index.html, http://cdp.binghamton.edu/era/countries/, and http://electionresources.org/data/index_en.html.</u>

> 22 Duchin and Sosyura (2012b) document an important role of political connections for bank bailouts. They show that politically connected banks are more likely to be recapitalized under the TARP.

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