do markets punish left governments?

Do Markets Punish Left Governments?

Thomas Sattler London School of Economics and Political Science

The political economy literature finds that stock markets drop after left-wing and increase after right-wing electoralvictories. This study shows that the size of this reaction strongly depends on the political constraints that theincoming government faces. When constraints are high, the discretion of governments to implement their preferredpolicies is low, which implies that election outcomes are less relevant for financial investors. The analysis of anoriginal dataset of stock market reactions to 205 elections since the 1950s confirms this conjecture. Stocks dropconsiderably after the election of a left government and increase after the election of a right government, but only inlow-constraints countries. These partisan effects on stocks are highly persistent and even become stronger over timewhen additional information about the composition of the incoming government becomes available. However, theeffects of elections on stocks fully disappear when political constraints are high.

Research on politics and financial marketsshows that financial investors closely watchpolitical developments and respond to polit-

ical information (e.g., Bernhard and Leblang 2006;Goktepe and Satyanath, Forthcoming). A fair numberof studies in this area examines the effects of electionson stock markets. They find that stock markets oftenpunish incoming left governments and drop signifi-cantly after a left-wing electoral victory. Similarly, theywelcome right governments with a positive, upwardreaction in stock prices. This is because the probabilityof policies that are harmful for returns on investmentsincreases under left governments, while right gov-ernments are more likely to choose policies that arebeneficial for financial returns (e.g., Bechtel 2009;Herron 2000; Leblang and Mukherjee 2005).1

Many examples illustrate this pattern. One ofthem is the French presidential election on May 10,1981, when the socialist Francxois Mitterrand wonagainst the conservative incumbent Valerie Giscardd’Estaing. During the first trading day after theelection, the French CAC index dropped by 13.8%,and it fell by another 10.2% over the next three days.However, there are also plenty of examples when stocksresponded very little to the election outcome. After the

Belgian national election on November 8, 1981, only afew month after the election of Mitterrand, the BrusselsGeneral index hardly moved. It varied by less than1% for weeks after the election that was won by acoalition under the leadership of the conservativeWilfried Martens. This difference is noteworthy con-sidering that the two elections were about equally closeand both new governments were positioned fairlydistant from the political center.2

Why do financial markets react differently to theelection of similarly extreme governments in differentcountries? This study shows that the financial effectsof elections depend on the institutional framework ofa country and the political constraints arising fromthose. Institutions constrain policy makers’ ability toalter existing policies and to implement their mostpreferred choices (Henisz, 2004). Stock market par-ticipants anticipate this when evaluating election out-comes and take it into account when making theirinvestment decisions. Markets are aware that the sys-temic risk emanating from a left government is smallwhen this government has to accommodate a largerange of actors with diverse political views. Vice versa,the benefits from a right government are limited insuch circumstances. Investors thus are less concerned

The Journal of Politics, Vol. 75, No. 2, April 2013, Pp. 343–356 doi:10.1017/S0022381613000054

� Southern Political Science Association, 2013 ISSN 0022-3816

1An online appendix for this article is available at www.journals.cambridge.org/jop. It contains descriptive statistics, a description of themethodology, and supplemental analyses. Data and supporting materials necessary to reproduce the numerical results in the article willbe made available at www.thomassattler.org on publication of this article.

2Mitterrand won 52% of the votes. The new Belgian government received only 48% of the votes and 53% of the seats in parliament.Both governments have roughly the same distance to the mean on the ideology scale in my dataset, although in different directions.

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with elections when political constraints are high im-plying that the financial effects of elections decrease.

The analysis of an original dataset of stockmarket responses to 205 elections in OECD countriessince the 1950s confirms this. The results show thatstocks drop after the election of a left governmentand increase after the election of a right government,but only in countries with a low degree of politicalconstraints. These partisan effects on stocks diminishwhen political constraints increase, and they fullydisappear when the government faces a high degreeof political constraints. There is some indication thatstocks drop less after left victories than they increaseafter right victories, but this asymmetry is not statis-tically significant for many situations. Stock marketresponses to elections are highly persistent and consid-erably increase over time when additional informationabout the composition of the incoming governmentbecomes available.

The study contributes to the existing research inthe following ways. First, it combines research onpolitical institutions and financial markets followingBernhard and Leblang (2006). But unlike this research,which mostly examines the impact of institutions onthe volatility of stock markets through predictabilityof elections and government composition, I focus onthe impact of election outcomes on the direction ofmarket responses, and how this effect is mediated byinstitutions. Second, it extends the common single-election or single-country studies of politics and finan-cial markets that dominate current research (Bechtel,2009; Herron, 2000; Leblang and Mukherjee, 2005;Snowberg, Wolfers and Zitzewitz, 2007a, 2007b).3 Whilethese analyses yield detailed insights, they should becomplemented with a broader cross-country and his-torical analysis. Such a comparative design is necessarynot only to analyze the mediating effect of institutionsand constraints, but also to examine how the degree ofgovernment extremism and the strength of stock marketresponses are related. To measure the degree of govern-ment extremism, this study uses a continuous indicatorof ideology that is more nuanced than the previouslyused measures. Finally, the study examines the im-plications of investor risk aversion on the connectionbetween elections and stocks.

The results have several implications for the po-litical economy of financial markets. First, institutionsare essential to ‘price politics’ (Bernhard and Leblang,2006), i.e., to assess the financial consequences of polit-ical processes. Assessments that exclusively rely on well-

chosen elections in countries and periods with relativelyfew constraints, like the United Kingdom or the UnitedStates, lead to strong conclusions about the generalconnection between politics and financial markets.My results suggest that, in certain instances, politics isnot of primary importance to financial investors, notbecause they anticipated the election result, but becausethe election has minor consequences for returns oninvestments. Second, the results imply that the financialconsequences of democratic political processes differconsiderably across countries. In some countries, elec-toral outcomes lead to a redirection of capital from thedomestic stock market into other forms of investmentor into other countries when investors expect a lessfavorable policy environment. In other countries, thesame political processes lead to little redirection ofinvestments away from domestic stocks.

Stocks and Politics

Elections and Financial Market Behavior

In the most general terms, stock prices represent theaggregate expectations of market participants about thefuture performance of firms. An increase (decrease) in afirm’s stock price reflects the expectation that futuredividends will raise (fall), which in turn depends on thefirm’s future profitability. Besides the firm-specific char-acteristics, the expected profitability of a firm to a con-siderable extent depends on government policies. Highercorporate taxes, for instance, reduce the share of incomethat can be reinvested or distributed as dividends. Greaterlabor rights limit firms’ abilities to offset employees whenthey have excess capacities, and so on. Changes in stockprices after political events therefore indicate shifts inexpectations about future policy choices.4

Research on partisan economic policymaking yieldsimplications about how financial investors can formexpectations about future government policies. Theclassic literature suggests that left governments pursuepolicies that are harmful for capital owners (Hibbs1977). Although newer research has shown that leftgovernments often successfully manage the economy,(Boix 1998; Garrett 1998), financial investors may stillbe less enthusiastic about left governments because thethreat of unfavorable policy reversals is greater under

3Exceptions are Campello (2007) and Bernhard and Leblang(2006).

4For the argument of this article, stock prices simply reflectexpectations about policies and their potential real economiceffects at a later stage, but real economic activity occurs outsidethe model.

344 thomas sattler

these governments even if they announce and imple-ment market friendly policies at the beginning of theirincumbencies (Bechtel 2009). Right parties generallyrepresent constituencies who value stability and lowvariance policies. They also have greater ties to busi-nesses, which prefer stable and orthodox economicpolicies. Left governments representing lower-incomegroups and having fewer connections to the economicelite can more easily reverse market friendly policieswhen such actions promise political benefits.5

When the probability of adverse policies increases,expected returns throughout an upcoming legislativeterm decrease. Stocks then should drop after a leftelectoral victory when adverse policy reversals becomemore likely.6 Vice versa, they should increase when theprobability of stable, market-friendly policies increasesafter a right victory. The literature has found evidencefor this hypothesis for elections in selected countries,notably the U.S., the UK and Germany (Bechtel 2009;Herron 2000; Leblang and Mukherjee 2004, 2005;Snowberg, Wolfers and Zitzewitz 2007a, 2007b).

With few exceptions (Bernhard and Leblang 2006,chap. 3 and 4; Campello 2007), these studies are re-stricted to one or few election(s) in one country. Thiscommonly used single-election design, however, missesan important part of the variation. It does not allowus to estimate how much more stocks respond to elec-tions when incoming governments are more extremelypositioned in the policy space, which requires a com-parative analysis like the one presented below. Existingstudies only capture the financial effects of an election,given the specific positions of the two particular politicalparties or blocs.

H1 (Partisanship): Domestic stock prices drop whena left government wins the election, and they increasewhen a right government wins the election. Moreover,the stock market response (in any direction) is larger,the greater the distance between the political centerand the position of the incoming government.

Previous research yields more refined predictions howstocks may respond to elections (Pantzalis, Stangeland,

and Turtle 2000). Specifically, risk aversion impliesthat stock markets may respond asymmetrically to leftand right governments. To develop the argument, it isuseful to distinguish between two different challengesthat investors face. The first, which was discussed above,arises from the necessity to assess future policies, giventhat a particular government wins the election. Thesecond arises from the difficulty to assess which type ofgovernment will be formed after the election, given theexpected policies during this government’s incumbency.This problem is greatest for close elections, when bothparties or blocs have roughly equal chances to win. Buteven if one side is more popular, elections are rarelyperfectly predictable, and both sides retain a nontrivialchance of winning.

The uncertainty surrounding elections is furtherincreased by coalition politics, which makes it moredifficult for investors to predict the composition offuture governments, which will ultimately choose therelevant policies. While it is conceivable in manyinstances which parties will form a coalition, this ismore difficult to foresee in others (Laver and Shepsle1996). When parties do not form pre-election alliancesor none of these alliances wins a majority, a new coa-lition needs to be negotiated after an election. For thisanalysis, coalition politics therefore matters foremostbecause it makes it difficult for investors to predict thecomposition of the new government. Consistent withthis argumentation, Bernhard and Leblang (2006,chaps. 3 and 4) show that financial investors find itdifficult to predict government composition in manyinstances.7

These forms of electoral uncertainties may notonly affect the volatility, but also the mean behaviorof stock markets. The reason is that risk averse in-vestors set stock prices below the expected value of astock when electoral uncertainty prevails before theelection. Risk aversion implies that an investor prefers aless risky asset to a more risky one even if the expectedvalue of the less risky alternative is lower. Demand forstocks then decreases when electoral uncertainty in-creases pushing the price levels of stocks below theirexpected values (Brown, Harlow, and Tinic 1988).8

Once the election outcomes become known, financialinvestors adjust their portfolios, and price levels on

5Governments respond strongly to shifts in popular support byadjusting economic policies (Sattler, Brandt, and Freeman, 2010;Sattler, Freeman, and Brandt, 2008). This gives rise to policy riskreflecting the difficulties of economic actors to predict which ofthe options in its set of feasible policies the government willchoose (Fowler, 2006). While all parties can be associated withpolicy risk, the probability of a shift towards adverse policies islarger for left parties (Santa-Clara and Valkanov, 2003).

6The ability of investors to hedge against political risk may haveincreased over time, but the empirical findings on the financialeffects of politics show that investors cannot fully safeguardagainst such risk. I address potential variation over time in theempirical analysis.

7For this analysis, I assume that overall government compositionis what matters to investors and not the control of specificcabinet posts, like the finance ministry.

8The expected value of a stock is the weighted average of the post-election price given that the left party wins and the post-electionprice given that the right party wins. The weights are the pre-electionprobabilities that each party wins the election.

do markets punish left governments? 345

average increase, as Pantzalis, Stangeland, and Turtle(2000) show for elections in 33 countries since the1970s.9

Extending this argument implies that stocks re-spond asymmetrically to left and right victories. Whenpre-election stock prices are set below their expectedvalue as discussed in the previous paragraph, the dif-ference between pre-election price and the price that isrealized after a left victory is smaller than the differencebetween the pre-election price and the price after a rightvictory. To see why, suppose that the relevant parties orblocs have equal chances of winning the election. Theexpected value of stocks before the election then is theaverage of post-election prices after a left victory andpost-election prices after a right victory. A pre-electionprice below this expected value means that the pre-election price is closer to the post-election price after aleft victory than to the post-election price after a rightvictory.

H2 (Asymmetry): Domestic stock prices drop lessafter a left government victory than they increaseafter an equivalent right government victory.

Political Constraints, Policy Change, andStock Markets

The previous discussion of elections and stock marketsonly takes into account the restrictions that govern-ment parties face from their constituencies, but not thedifferences in political constraints that arise from thepolitical environment. But political systems and con-stellations can impose considerable restrictions on partygovernments and limit their discretion to implementtheir preferred policies (Alt 1985). And while left andright governments face varying demands and restric-tions from their constituencies, political and institu-tional constraints should be the same for both types ofgovernments, which mediates the effect of governmentpartisanship on stocks.

Investors’ policy expectations should vary consid-erably across countries and also over time becausepolitical constraints may be greater in some situationsthan in others, and constraints ultimately affect policyoutput. The exact degree of political constraints andthus the possibility of sudden policy changes dependson the combination of the institutional setting andpolitical constellations. The institutional setting deter-mines how many different actors are involved in the

decision-making process and can veto a policy proposal(Tsebelis 2002). One example are bicameral parliamen-tary systems, where majorities in two chambers mustsupport a proposal before it passes the legislative pro-cess. When the opposition party dominates one of thetwo chambers, the central government will find it dif-ficult to pass a policy proposal, at least in its originalform. The number of veto players is also larger forminority governments, in coalition governments andwhen the central bank is independent. Minority gov-ernments require the support of additional parties inthe parliament to pass a policy proposal. In coalitiongovernments, any government party is a potentialveto player, because any of them can block a policyproposal if the majority depends on its votes.

With greater political constraints, variation in pol-icy output decreases considerably. It has been shownthat governments can reset their tax rates more easilywhen the number of veto players is smaller (Hallerbergand Basinger 1998). Henisz (2004) extends this evi-dence to a broader range of fiscal policy indicators, in-cluding different types of expenditures, transfers andtaxes. Variation in these policy indicators is substan-tially smaller when policy makers face greater politicalconstraints. It is plausible that the relationship betweenconstraints and policy variation not only applies tothe fiscal policies analyzed in these studies, but also toa broader range of other relevant policy fields, likeregulatory policy. There is also evidence that policystability has important effects on investment decisions(Henisz 2002). Although these findings refer to morelong-term investments, like infrastructure, we can expectthat political constraints also affect short-term financialinvestments.

Financial investors should take political constraintsand their consequences for policymaking into accountbecause the constraints indicate to what extent theyshould expect (positive or negative) policy changes inthe future (Breen and McMenamin, Forthcoming;Mosley and Singer 2008). If investors can be confidentthat the range of policies from which the governmentcan choose is seriously restricted, the government’spreferences and intentions become less relevant. Infact, it is plausible that investors find it less challengingto assess the degree of political constraints that a gov-ernment faces than to evaluate the exact policy posi-tions and true intentions of an incoming government.Unlike the true intentions of a new government, theworkings of political systems can be observed directlyand should be well known from past, experiences,allowing investors to form fairly precise expectationsabout the constraints in a particular situation. Thestock market response to an election outcome then

9Pantzalis, Stangeland and Turtle (2000) ignore the content of theinformation that an election reveals to investors and do notdistinguish between election outcomes, i.e., whether a left or rightgovernment is elected.

346 thomas sattler

should decrease, the greater the political constraints ofa government because policies are less likely to changein a high-constraints country than in a low-constraintscountry.

Combining the insights on partisanship and stockmarket responses from the previous section and thoseabout political constraints in this section, we can con-clude that political constraints should mediate theimpact of left and right governments on stocks. Thepossibility of an adverse policy choice by a left govern-ment is smaller when political constraints are large.Stocks therefore should drop less after a left govern-ment victory in a high-constraints country than in alow-constraints country. Similarly, the benefits of aright government compared to a left government dimin-ishes when political constraints on the government in-crease. Stocks therefore should increase less after a rightparty victory in an election in a high-constraints countrythan in a low-constraints country.

H3 (Constraints): The effect of elections on stockprices is conditional on political constraints. Stockprices fall less after the election of a left government,the greater the political constraints that the govern-ment faces. Vice versa, stock prices increase less afterthe election of a right government, when politicalconstraints increase.

Empirical Design

The empirical analysis is based on an event study(Campbell, Lo, and MacKinley 1997, chap. 4), whichcompares actual financial market behavior after anelection to the expected behavior if the election hadnot happened. The difference between the expectedand the actual behavior is the abnormal return. Theabnormal returns after an election are cumulated overfive trading days to compute the cumulative abnormalreturn (CAR), which provides an estimate of the impactof the election on financial market behavior and whichis the dependent variable for the analysis below. A de-scription how the CARs are computed is in the onlineappendix.

An important issue is the anticipation of electionresults by financial investors. If stock market partic-ipants have a good sense of what the election resultwill be, pre-election stock prices already reflect thisinformation and stock prices respond less to the actualelection outcome. This problem becomes less severewhen the number of elections is high, like in this study,because underreactions after anticipated election out-comes and overreactions after surprise results should

balance each other. But since measurement error in-creases, the results are biased downwards even if over-and underreactions cancel each other out (Snowberg,Wolfers, and Zitzewitz 2008, 7-8). This means that theestimations yield conservative results because theyunderestimate the effect of elections on stocks.

To establish greater confidence in the results, Iconduct multiple additional analyses. First, predict-ability of the election outcomes further decreases bycoalition politics and the difficulty of investors toanticipate which political parties will form the gov-ernment in many instances. This implies that stockmarkets should continue to respond after the electionuntil the exact composition of the new government isknown. Examinations of longer event windows sup-port this: the response of stock markets increases upto 30 trading days after an election, which reflects themedian government formation time in the dataset.

Second, and more importantly, I split the sampleinto elections that were close and ones that were notclose.10 The idea is that in close elections, the assign-ment of partisanship is as good as random in theneighborhood of the threshold of a political party orbloc winning or losing the election. The results of thisprocedure confirm the expectation that the estimatedeffects using close elections are significantly strongercompared to the analysis with both close and noncloseelections. In addition and as expected, the results fornonclose elections show no meaningful impact ofelections on stocks.11

Countries and Data

The analysis covers 205 parliamentary elections inOECD countries for which the relevant data areavailable. The analysis starts in the 1950s, but dailystock-index series are only available for later periodsin many countries. As a basic rule, the broadest andlongest available stock index is used. When differentstock indices had to be used for the same country,tests show that the different indices behave in verysimilar ways during periods for which they overlap,and the CARs from the different indices are almostexactly identical.

10I define close elections as those with a margin of victory of lessthan 10%, which is the case for 134 observations.

11The results for nonclose elections are in the online appendix.Unfortunately, it is not possible to use prediction market data as ameasure of closeness of elections (Snowberg, Wolfers, and Zitzewitz,2008) because such data is only available for very few elections. Thesmall number of elections that could be studied would not allow meto draw reliable conclusions about the intervening effect of con-straints, which requires a comparative design.


Data on elections are from the ComparativeManifesto Project (Budge et al. 2001). Six electionsin the dataset took place in the 1950s, and 65 are from1960 to 1979, and the rest since 1980. To measuregovernment ideology, I use a left-right index from theComparative Manifesto Project. This index is based onprespecified issue categories that are defined to be ‘left’or ‘right.’ To locate party positions, themes and state-ments in the party manifestos were assigned to thepredefined issue categories according the ManifestoProject’s coding scheme. Government ideology is com-puted by weighting the positions of all governmentparties on the left-right index according to the parties’relative strength in the cabinet.12 This yields a contin-uous indicator that not only captures left or right ide-ology, but also how extreme the government positionsare in any direction.

To measure political constraints, I rely on a com-prehensive indicator by Henisz (2002) that captures avariety of checks in a political system. It reflects theoverall ability of policy makers to implement theirmost preferred policy and takes into account vetoplayers, the structure of and preference heterogeneitywithin the legislature, and the role of governmentbranches. It is the most sophisticated indicator avail-able and therefore best reflects the large amount ofinformation that financial markets tend to rely on.

Control variables include a country’s degree of dejure capital account openness (Quinn 1997, 541–47);the size of the market as represented by GDP; andeconomic circumstances as measured by economicgrowth (both from Heston, Summers, and Aten 2011).Additional analyses cover a wider range of potentiallyimportant constraints and control variables, includingdummies for minority and multi-party governments(Budge et al. 2001), an index of central bank indepen-dence (Cukierman, Webb, and Neyapti 1992), the defacto exchange rate regime (Reinhart and Rogoff 2004)and investment flows over GDP (Lane and Milesi-Ferretti 2006). The results for these additional analysesare in the online appendix. For the ideology measure,higher numbers indicate more left-wing governments.For constraints and openness variables, higher valuesindicate greater constraints or openness, respectively.To simplify the interpretation of the interaction terms,ideology is recoded to vary between 0 and 100, the

constraints index varies between 0 and 10, and thecontrol variables are centered at their means. Summarystatistics for the variables are in the online appendix.

Empirical Specification and Expectations

The dependent variable in the empirical model is theCAR, which captures both the direction and the mag-nitude of the stock market response to an election. Thekey independent variables are government ideologyand political constraints. Government ideology deter-mines in which direction stocks move after an election,i.e., whether they move up- or downwards. Constraintsmediate how strongly stocks drop or increase given aparticular election outcome, which requires an inter-action term between ideology and constraints.

Just like political constraints, the control variableshave a mediating effect on the impact of ideology onstocks, which means that they must also be interactedwith ideology. This is the case because openness, marketsize, and economic circumstances alone do not deter-mine if stocks fall or rise after an election. Instead, thesecontrol variables mediate how strongly stocks move up-or downwards given the outcome of the election. As anexample, greater market size does not lead to a morepositive or negative financial response to an electionbecause market size does not contain any positive ornegative news and is also known before the election.However, markets may respond more positively to aright and more negatively to a left government, thelarger the economy is. The same applies to the othercontrol variables. Suppose that we have k controlvariables, then the empirical specification is

CARi ¼ b0 þ b1Ideologyi þ b2Constraintsi

þ b3Ideologyi � Constraintsi

þ +k

j¼1

�bjþ3Controlj;i

þ bjþkþ3Ideologyi � Controlj;i

�þ ei ð1Þ

A high number of control variables and therefore in-teraction terms substantially complicates the model.To keep it as simple as possible, I only include thosecontrols that turn out to be the most relevant ones inthe additional analyses described in the online appen-dix. Since the dependent variable is based on estimates,the coefficients in (1) are estimated using feasible GLSas proposed by Lewis and Linzer (2005).

We can now translate the hypotheses from the the-oretical discussion into expectations about the estima-tion results. Hypothesis 1, the Partisanship Hypothesis,implies that the constant in equation (1), b0, shouldbe positive because, ignoring the interactions for the

12Alternatively, one could consider which party holds ministerialposts that are relevant for the economy, but this approach wouldrequire that we assume that the other government parties do nothave a say in economic matters, which is implausible. For thecurrent analysis, I therefore stick to the standard approach,assuming that the relative size of parties reflects their relativepower in government.

348 thomas sattler

moment, it shows how stock markets respond to theelection of a right-wing government (Ideologyi 5 0).The coefficient on ideology, b1, should be negativebecause stocks drop more/increase less the more left-wing the government is. Hypothesis 2, the AsymmetryHypothesis, implies that the positive CAR after a rightvictory is greater than the absolute value of the negativeCAR after an equivalent left victory. Assuming that thePartisanship Hypothesis holds and predicted CARs arepositive (negative) after a right (left) victory, this meansthat CARRight . 2CARLeft. This can be tested usinga standard hypothesis test.

Hypothesis 3, the Constraints Hypothesis, impliesthat, besides the positive constant and the negativecoefficient on ideology in (1), the coefficient on theconstraints variable, b2, should be negative because itindicates how growing constraints diminish the pos-itive market response to a conservative government.The coefficient on the corresponding interactionterm, b3, should be positive because the negativeeffect of left-wing governments becomes more pos-itive as constraints increase. Table 1 summarizes theseexpectations.

Results

Table 2 presents the estimation results from equation(1) or components thereof. Prior analyses show thatthe relevant control variables are financial openness,GDP and economic growth, which means that k 5 3.To simplify the interpretation, I first present modelswith one or no control variable before I move to theestimations with all variables and interactions.

The first column reports the results from a simplespecification using only government ideology asregressor. The estimates show that stock returns areexpected to increase by 1.8% when a fully right gov-ernment wins the election, i.e., when ideology takesthe value 0. When we move from a fully right to afully left government, i.e., when ideology increasesfrom 0 to 100, the expected CARs drop by 3.6 per-centage points, which implies that stock returns

decrease by 1.7% after the election of a fully leftgovernment. For a center government, i.e., for an ide-ology value of 50, the expected response is negligible(0.06%). These first results confirm the PartisanshipHypothesis (H1) and also suggest that stock marketsmove more strongly up or down, the more extremethe incoming government is.

The results in the second and third columns in-clude the political-constraints variable and its inter-action with ideology. All coefficients and the constantshow the expected signs. CARs are expected to bepositive when the new government is conservative, butthey decrease and eventually become negative, themore left the government is. The negative coefficienton the constraints variable implies that the positiveeffect of right governments decreases with greater con-straints. The positive coefficient on the interactionmeans that the negative effect of more left governmentsdecreases with greater constraints. In other words, thepartisan effects on stocks become smaller when polit-ical constraints increase. As expected, the estimatedimpact of election outcomes is considerably strongerwhen only close elections are analyzed (third column).These results confirm the Constraints Hypothesis (H3).

Additional analyses reinforce these basic results.The estimates in the fourth column are based on allelections, but I use an indicator that only considersparties’ positions with respect to economic issues.The results are even stronger, but this more specificindicator is less reliable than the general ideologymeasure.13 I therefore use the latter for my furtheranalyses. The specifications including the control vari-ables and their interactions with government ideologyin the remaining columns yield the same results andconfirm the Partisanship and Constraints Hypotheses.The coefficients on the controls and their interactionsimply that more financial openness and greater eco-nomic growth reduce the effect of ideology on stocks,while a higher GDP level magnifies this effect.

To simplify the interpretation of the conditionaleffect of ideology on stocks, I present marginal effectsand predicted CARs for different values of ideologyand constraints. Since the control variables are alsointeracted with ideology, the predicted effects dependon the values assigned to the controls. This meansthat the control variables must be fixed at pre-specifiedvalues to compute the predictions. To get a better ideahow the results vary with different values of the con-trols, I set the control variables not only at their means,

TABLE 1 Expected Estimation Results byHypothesis

Hypothesis Expectation

H1 (Partisanship) b0 , 0; b1 , 0H2 (Asymmetry) CARRight . 2CARLeft

H3 (Constraints) b0 , 0; b1 , 0; b2 , 0; b3 . 0

13The issue-specific Comparative Manifesto indices rely on only afew categories, some of which are not covered by many partyprograms.


TABLE 2 Party Effects on Stock Markets (CAR)

Simple BasicBasic /

Close ElectionsEconomicIdeology Control 1 Control 2 Control 3 Full

Full / CloseElections

Ideology -0.036**(0.016)

-0.090**(0.040)

-0.200**(0.089)

-0.099**(0.043)

-0.090**(0.040)

-0.079**(0.031)

-0.082**(0.034)

-0.243***(0.079)

Constraints -0.676*(0.368)

-1.457*(0.820)

-2.927**(1.178)

-0.746*(0.385)

-0.611(0.398)

-0.616*(0.329)

-0.654*(0.343)

-1.813**(0.685)

Ideology*Constraints 0.011(0.008)

0.028(0.017)

0.012(0.008)

0.009(0.008)

0.008(0.006)

0.009(0.006)

0.037**(0.015)

Orthodoxy -0.184***(0.063)

Orthodoxy*Constraints 0.031**(0.013)

Openness -0.286(0.267)

-0.844***(0.295)

-1.124**(0.443)

Ideology*Openness 0.001(0.005)

0.012**(0.006)

0.016(0.009)

GDP 0.259(0.824)

0.911(1.066)

0.962(1.262)

Ideology*GDP -0.014(0.014)

-0.023(0.018)

-0.032(0.022)

Growth -0.816*(0.397)

-0.941**(0.372)

-0.924*(0.511)

Ideology*Growth 0.014**(0.007)

0.015**(0.007)

0.012(0.009)

Constant 1.861**(0.852)

5.389**(1.967)

10.521**(4.287)

17.363***(6.041)

5.744**(2.121)

5.330**(1.935)

5.145***(1.763)

5.192**(2.042)

12.428***(3.745)

F 5.22 3.94 3.34 4.65 9.86 4.94 3.71 22.65 7.66Prob . F 0.033 0.022 0.040 0.012 0.000 0.004 0.015 0.000 0.000R2 0.02 0.03 0.07 0.03 0.04 0.04 0.05 0.09 0.18N 205 205 134 205 205 205 205 205 134

Note: Coefficients are estimated using the FGLS procedure by Lewis and Linzer (2005). Standard errors are in parentheses. Errors cluster on countries. *** p , 0.01, ** p , 0.05, * p , 0.1.

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le

r

which is often used as a standard in the literature, butalso at one standard deviation from their means, whichis often used as a standard change in the literature.14

This is particularly important for the predicted valuesin Figure 2 and the asymmetry tests in Table 3.

Figure 1 shows the marginal effect of the ideologyvariable on CARs as political constraints increase.15

The graph shows how the market response changeswhen a more left-wing government is elected, fordifferent degrees of political constraints. The negativestarting point of the marginal-effects curve meansthat stock markets drop in response to the electionof a more left leaning government. The upward shiftin the curve implies that the impact of governmentideology approaches zero when political constraintsincrease. For this specification, the effect becomes sta-tistically insignificant at a value of ca. 7 on the con-straints scale. This roughly corresponds to a constraintslevel in Denmark or Finland. When constraints increasefurther, the impact of ideology fully disappears. Suchhigh levels of constraints correspond to countries likeBelgium or Switzerland.

Figure 2 presents the predicted CARs for allcombinations of ideology and constraints. The border

of the plane declining from the top towards the bottomleft illustrates how the predicted CARs decrease from alarge positive value for right governments to a largenegative value for left governments when constraintsare zero. The plane’s border that declines from the topto the right shows that the positive CARs for rightgovernments decrease to almost zero when constraintsincrease. The plane’s border that rises from the bottomleft to the right shows that the negative CARs for leftgovernments increase to slightly above zero when con-straints increase. The flat border on the right illustratesthat the CARs are very close to zero for all governmentswhen constraints are at the maximum.

The minimum and maximum predicted CARs atthe edges of the plane are large, but they more or lesscorrespond to the minimum and maximum CARs inthe dataset. Moreover, they represent extreme valuesfor rare situations with extremely positioned govern-ments facing no political constraints.16 The predictedCARs for more moderate combinations of ideologyand constraints correspond to market responses thatwe often observe in practice. For an incoming gov-ernment with an ideology value of 20, the expectedstock market response is 5.7% (95% confidenceinterval: 2.8%; 8.7%) holding the level of constraints

FIGURE 1 Effect of a One-Unit Increase inIdeology as Political and FinancialConstraints Increase

FIGURE 2 Predicted CARs for all Combinationsof Constraints and Ideology

14Openness and growth variables are set at one standard devia-tion below the mean because more openness and growth reducethe effect of ideology on stocks. GDP, which has a positive,intervening effect, is set at one standard deviation above themean.

15The graph is based on estimation results in the last column ofTable 2. It reflects the first derivative of equation (1) with respectto ideology for different levels of constraints with controls set atone standard deviation from the mean. The graphs for differentvalues of the control variables are in the online appendix.

16Most ideology values lie between 20 and 80. Examples ofgovernments with values below 20 are the British governmentsunder Thatcher. The British government under Wilson after 1974and the Finnish and Swedish governments in the early 1970s havevalues above 80.


at the mean (5.53). The expected CAR for an ideologyvalue of 80 is –3.6% [–6.7%; –0.5%]. When ideologyincreases from 30 to 70, holding constraints at onestandard deviation below the mean (3.5), the expectedCAR changes from 5.6% [3.2%; 8.1%] to –3.5%[–6.2%; –0.8%].

The results show some, albeit weak, support forthe Asymmetry Hypothesis (H2) postulating themarkets increase more after a right electoral victorythan they decrease after a left victory. For zero po-litical constraints, the asymmetry, i.e., the differencein the magnitude of the stock market response, is(18.8% – 16.8% 5) 2%.17 But the essential questionis whether these differences are statistically significant,which I examine using a t-test. The null hypothesisunderlying the testing procedure states that the size ofthe CARs after left and right victories are the same, orequivalently, that the asymmetry is zero. The alternativehypothesis, which reflects the Asymmetry Hypothesis,states that the size of the positive CAR after a rightvictory is greater than the size of the negative CAR aftera left victory. The two governments that are comparedmust be equally ‘‘extreme,’’ i.e., positioned equally farfrom the center of the policy space. Formally, thismeans that

H0 : CARRight ¼ �CARLeft ð2ÞHa : CARRight > �CARLeft ð3Þ

Table 3 shows the test results for different levels ofpolitical constraints (in the columns) and differentvalues of the control variables (in the rows). The firstrow of the two blocks in the table shows the esti-mated size of the asymmetry between left and rightgovernments. The asymmetry should be positive, butnegative values can occur if the response to a rightgovernment is smaller than the response to a leftgovernment. The second row in each block presentsthe results of the hypothesis test. The p-values in-dicate the probability of rejecting the null hypothesis(of no asymmetry) although it is true. To accept thealternative, that stock markets respond asymmetricallyto left and right governments, p-values must be small.

The results show that asymmetries generally existfor low levels of constraints, especially when the controlvariables are set one standard deviation from the means(lower block). When controls are set at the mean, weonly see a notable asymmetry for the estimates based onall elections for very low levels of constraints. Largerasymmetries when controls are set one standard devia-tion from the mean are plausible because the partisaneffects on stocks and the associated asymmetries shouldbe larger for these situations. Similarly, asymmetriesshould be small or nonexistent for high constraintslevels as we see it in the table because partisan effects

TABLE 3 Tests of Asymmetry in Predicted Stock Market Responses to Left and Right Governments

Controls setat . . . Analysis

Level ofPolitical Constraints

Min.Constraints

LowConstraints

MeanConstraints

HighConstraints

Max.Constraints

. . . mean All electionsAsymmetry 2.19 0.65 -0.05 -0.74 n.a.p-value 0.20 0.28 0.53 0.85 n.a.

Close electionsAsymmetry 0.20 0.31 0.36 n.a. n.a.p-value 0.47 0.39 0.29 n.a. n.a.

. . . one standard All electionsdeviation from mean Asymmetry 3.86 2.32 1.62 0.93 -0.18

p-value 0.09 0.09 0.14 0.29 0.53Close elections

Asymmetry 2.02 2.12 2.17 2.22 n.a.p-value 0.26 0.13 0.11 0.14 n.a.

Note: Asymmetry is the estimated difference in the size of the stock market response to a left and right government,

i.e., Asymmetry ¼ dCARRight � dCARLeft. The p-values indicate the level of statistical significance of this asymmetry. Low and highconstraints are one standard deviation below and above the mean, respectively. Estimates for ‘‘All elections’’ (‘‘Close elections’’) arebased on the results in the second last (last) column of Table 2.

17This example is based on the difference between fully left and rightgovernments, but the difference is the same for all pairs of equiv-alent left and right governments for a given level of constraints.

352 thomas sattler

generally should disappear when constraints are high.Despite some sizable asymmetries, the p-values indicatethat we can accept the Asymmetry Hypothesis only forvery few cases at conventional significance levels. Theestimated asymmetries are statistically significant at the10% level only for two situations in the lower half ofthe table. In other words, there is some, however weak,evidence in favor of hypothesis H2.18

To examine how persistent the effect of electionson stocks is, and how sensitive the results are to thespecification of the event window, I reestimate themodels using CARs computed for event windows ofup to 50 trading days after an election. Figure 3 plotsthe marginal effects of ideology for different eventwindows. The political-constraints variable is set atthe mean, which corresponds to a value of 5.53.19

The figure shows that the financial effects of elec-tions are highly persistent and that the results are notan artifact of a particular event-window definition.The marginal effect is consistently negative and the 95%confidence interval does not include zero for windowsup to 40 days. The magnitude of the effect more thandoubles during the first 20 trading days (four weeks)and remains roughly constant after that. This is plau-sible because it often takes a few weeks until it is fullyclear which parties will form the new government.

Stocks continue to respond to electoral processesuntil the government formation process is finished(Bernhard and Leblang, 2006). Comparing the timeduring which stocks continue to respond with themean and median government formation times inthe dataset confirms this. The average formation timeis 34 days (4.8 weeks), while stocks continue to reactto elections for about four weeks after the election.The median formation time is only 25 days (3.6 weeks),which is also very close to the four-week horizon duringwhich stocks continue to react.20

It is also possible that stock market patternsunrelated to elections produce the results shown above.To address this question, I use a ‘‘placebo’’ analysiswhich repeats the empirical analysis for randomlychosen nonelection days. If the results of my studyare caused by elections, stocks should not be system-atically associated with government preferences andinstitutions during nonelection periods. To examinethis conjecture, I draw 1000 random samples of non-election days of the same size as my election dataset,which means that each sample covers 205 observations.Each sample is drawn from the set of days on which noelection took place in the 22 countries that I analyze.21

For the placebo analysis, I reestimate equation(1) and compute the marginal effect of ideology fordifferent combinations of values for constraints andthe control variables using each of the 1000 samples.The combination of values are the same as for theasymmetry tests: constraints are set at the minimum,low, mean, high and maximum constraints levels; con-trols are set at the mean and one standard deviationfrom the mean. The placebo results in Table 4 presentthe median marginal effects from the 1000 randomsamples. The numbers in brackets are the five and 95percentiles. For reference, I also present the equivalentestimates from the main analysis (based the results inthe second last and last column of Table 2).22

FIGURE 3 The Persistence of Partisan Effects onStocks over Time

18For some high constraints situations, the predicted CARs showthe incorrect sign, i.e., the predicted response to a left (right)government is positive (negative). These are labeled ‘‘n.a.’’because they violate a fundamental assumption of the testingprocedure. These violations are not problematic because theyonly concern predicted CARs that are extremely close to zero andnot statistically significant anyway.

19The marginal effect for the five-day window in Figure 3corresponds to the effect in Figure 1, where the constraintsvariable on the x-axis takes the value 5.53. This effect is -0.156.

20The duration of government formation is measured as the numberof days from the election day until the inauguration day. Thediscrepancy between the mean and the median indicates that in someinstances, the formation process took much longer (e.g., Austria in1999). Such long government formation periods are unusual.Government formation duration at the 90th percentile is 67 days.

21The underlying set of days covers all days that do not fall into anelection period and for which CARs can be computed. To computethe CARs, a stock index must be available for a sufficiently longperiod of time before and after the potential date. I exclude 100 daysbefore and 50 days after an actual election to ensure that electionsdo not confound the results of the estimation or event windows.Using this procedure, the random samples can be drawn from188,527 possible days in the 22 countries.

22The marginal effects for ‘‘close elections’’ in the lower paneltherefore correspond to the values presented in Figure 1.


The results show that stock market behaviorduring nonelection periods is fundamentally differentfrom stock behavior after elections. The median mar-ginal effects from the placebo regressions are almostexactly zero for all specifications indicating thatstocks are not systematically associated with govern-ment preferences during nonelection periods. Thevariation in these effects is also very small. For lowand mean constraints levels, the effects at the fivepercentile do not even come close to those from themain analysis. This not only holds for the estimatesfrom close elections, but also for the those from allelections. Even the maximum marginal effects fromthe placebo analysis (not in the table) are smaller inmagnitude than those from the main analysis. Whenconstraints increase to higher levels, the partisan effectson stocks disappear and the marginal effects approachthose from the placebo analysis. In other words, theresults from the placebo and the main analyses differmassively for situations when they should, and they donot differ for those situations when they should not.

Conclusion

This study examines how financial markets respondto electoral outcomes. It confirms previous findingsthat stocks drop after the elections of a left governmentand increase after the election of a right government.In addition, it shows that stocks react more strongly,

the more extreme the new government is. However,this partisan effect on stocks is strongly mediated bypolitical institutions and political constellations thatdetermine the degree of constraints that the new gov-ernment faces. When political constraints increase, theresponse of stock markets to election outcomes de-creases and fully disappears for high levels of politicalconstraints. There is only weak evidence for the hypoth-esis that stocks increase more after a right victory thanthey decrease after an equivalent left victory.

An important implication that follows from thesefindings is that politics continues to matter for financialmarkets, even after economies have become highly opento financial flows. The analysis of elections and financialmarkets therefore provides an important contributionto the effort to gauge the ‘‘price of politics.’’ Nonethe-less, a complete assessment of the economic consequen-ces of elections means that we also need to examine theimpact of electorally induced financial reallocations onreal variables, like employment, production and in-come. The use of simultaneous equation models alongthe lines of Bernhard and Leblang (2006, chap. 8) is apromising research trajectory in this context, but thisexisting application only examines the interactionbetween the polity and the financial sector and neglectsthe real economy. Adding variables representing the realsector to a model of this kind would provide betterestimates of the economic effects of politics.

Another avenue for research is the disaggregationof economic and political processes. The scope of this

TABLE 4 Comparison of Estimated Marginal Effects from Main and Placebo Analyses

Controls setat . . . Analysis

Level ofPolitical Constraints

Min.Constraints

LowConstraints

MeanConstraints

HighConstraints

Max.Constraints

. . . mean Main analysis– All elections -0.082 -0.048 -0.032 -0.016 0.008– Close elections -0.247 -0.108 -0.045 0.018 0.118

Placebo analysis 0.001 0.001 0.001 0.001 0.002[-0.069;

0.071][-0.026;

0.027][-0.016;

0.019][-0.028;

0.030][-0.057;

0.059]. . . one standard Main analysis

deviation from mean – All elections -0.183 -0.148 -0.133 -0.117 -0.092– Close elections -0.357 -0.218 -0.155 -0.092 0.008

Placebo Analysis 0.002 0.003 0.003 0.004 0.004[-0.081;

0.093][-0.056;

0.066][-0.052;

0.061][-0.058;

0.067][-0.076;

0.082]

Note: Table shows the marginal effects of ideology for different constraints levels. Low and high constraints are one standard deviationbelow and above the mean, respectively. Results for the main analyses are based on estimation results in Table 2. ‘‘All elections’’ (‘‘Closeelections’’) refers to the results in the second last (last) column of the Table. The results for the placebo analysis show the medianmarginal effect computed from 1,000 random samples of nonelection days. The numbers in brackets are the five and 95 percentiles.

354 thomas sattler

study does not allow for distinctions between differ-ent sectors and firms. Yet, firms can benefit or sufferfrom the policy agenda of a government, e.g., whendemand shifts towards or away from their productsin response to new economic incentives set by policymakers (see, e.g., Bechtel and Fuss, 2010; McGillivray,2003). The literatures on partisan politics and busi-ness lobbying yield predictions that can be used topresent a more nuanced picture about the financialwinners and losers of elections.

Similarly, governments are not homogenous en-tities, but coalition partners can have fairly divergingpolitical views. Changing political majorities may matterless if, in a series of governments, the same party alwaysholds the Finance Ministry. More generally, financialinvestors should be well informed about intracoalitionpolitics and take these processes into account. New re-search in this area shows how portfolio allocation affectspublic policies and therefore how it should matter forfinancial investments (Herzog, 2011; Hubscher, 2012).

Acknowledgments

I thank Michael Bechtel, Cristina Bodea, Jos Elkink,Alex Herzog, Basak Kus, Nathan Monroe, GabrieleSpilker, Johannes Urpelainen, Anne Wren, the editorsof The Journal of Politics, and three anonymousreviewers for their comments.

References

Alt, James. 1985. ‘‘Political Parties, World Demand, andUnemployment: Domestic and International Sources ofEconomic Activity.’’ American Political Science Review 79(4): 1016–40.

Bechtel, Michael. 2009. ‘‘The Political Sources of SystematicInvestment Risk: Lessons from a Consensus Democracy.’’Journal of Politics 71 (2): 667–77.

Bechtel, Michael, and Roland Fuss. 2010. ‘‘Capitalizing onPartisan Politics? The Political Economy of Sector-SpecificRedistribution in Germany.’’ Journal of Money, Credit, andBanking 42 (2–3): 203–35.

Bernhard, William T., and David Leblang. 2006. DemocraticProcesses and Financial Markets: Pricing Politics. Cambridge:Cambridge University Press.

Boix, Carles. 1998. Political Parties, Growth, and Equality:Conservative and Social Democratic Strategies in the WorldEconomy. Cambridge: Cambridge University Press.

Breen, Michael, and Iain McMenamin. Forthcoming. ‘‘PoliticalInstitutions, Credible Commitment, and Debt in AdvancedEconomies.’’ International Studies Quarterly.

Brown, Keith C., W. V. Harlow, and Seha M. Tinic. 1988. ‘‘RiskAversion, Uncertain Information, and Market Efficiency.’’Journal of Financial Economics 22 (2): 355–85.

Budge, Ian, Hans-Dieter Klingemann, Andrea Volkens, JudithBara, and Eric Tanenbaum. 2001. Mapping Policy Preferences:

Estimates for Parties, Electors and Governments 1945-1998.Oxford, UK: Oxford University Press.

Campbell, John Y., Andrew W. Lo and A. Craig MacKinley. 1997.The Econometrics of Financial Markets. Princeton, NJ: PrincetonUniversity Press.

Campello, Daniela. 2007. ‘‘Do Markets Vote? A SystematicAnalysis of Portfolio Investors’ Response to National Elections.’’Princeton University. Unpublished manuscript.

Cukierman, Alex, Steven B. Webb, and Bilin Neyapti. 1992.‘‘Measuring Central Bank Independence and its Effect onPolicy Outcomes.’’ The World Bank Economic Review 6 (3):353–98.

Fowler, James H. 2006. ‘‘Elections and Markets: The Effect ofPartisanship, Policy Risk, and Electoral Margins on theEconomy.’’ Journal of Politics 68 (1): 89–103.

Garrett, Geoffrey. 1998. Partisan Politics in the Gobal Economy.Cambridge: Cambridge University Press.

Goktepe, Gokce, and Shanker Satyanath. Forthcoming. ‘‘TheEconomic Value of Military Connections in Turkey.’’ PublicChoice.

Hallerberg, Mark, and Scott Basinger. 1998. ‘‘Internationalizationand Changes in Tax Policy in OECD Countries: The Impor-tance of Domestic Veto Players.’’ Comparative Political Studies31 (3): 321–52.

Henisz, Witold J. 2002. ‘‘The Institutional Environment forInfrastructure Investment.’’ Industrial and Corporate Change11 (2): 355–89.

Henisz, Witold J. 2004. ‘‘Political Institutions and PolicyVolatility.’’ Economics and Politics 16 (1): 1–27.

Herron, Michael C. 2000. ‘‘Estimating the Economic Impact ofPolitical Party Competition in the 1992 British Election.’’American Journal of Political Science 44 (2): 320–31.

Herzog, Alexander. 2011. ‘‘Cabinet Composition and MinisterialBargaining: How the Portfolio Allocation of GovernmentsAffects Public Policy.’’ Paper presented at the annual meetingof the American Political Science Association, Seattle.

Heston, Alan, Robert Summers, and Bettina Aten. 2011. ‘‘PennWorld Table Version 7.’’ Center for International Compar-isons, University of Pennsylvania.

Hibbs, Douglas. 1977. ‘‘Political Parties and MacroeconomicPolicy.’’ American Political Science Review 71 (4): 1467–87.

Hubscher, Evelyne. 2012. ‘‘Hijacked Governments: The Impact ofMinor Parties on Public Policies.’’ Paper presented at theannual meeting of the 20th International Conference ofEuropeanists, Boston.

Lane, Philip R., and Gian Maria Milesi-Ferretti. 2006. ‘‘TheExternal Wealth of Nations Mark II: Revised and ExtendedEstimates of Foreign Assets and Liabilities, 1970-2004.’’ IMFWorking Paper WP/06/69.

Laver, Michael, and Kenneth A. Shepsle. 1996. Making and Break-ing Governments: Cabinets and Legislatures in ParliamentaryDemocracies. Cambridge: Cambridge University Press.

Leblang, David, and Bumba Mukherjee. 2004. ‘‘PresidentialElections and the Stock Markets: Comparing Markov-Switch-ing and Fractionally Integrated GARCH Models of StockVolatility.’’ Political Analysis 12 (3): 296–322.

Leblang, David, and Bumba Mukherjee. 2005. ‘‘GovernmentPartisanship, Elections, and the Stock Market: ExaminingAmerican and British Stock Returns, 1930-2000.’’ AmericanJournal of Political Science 49 (4): 780–802.

Lewis, Jeffrey B., and Drew A. Linzer. 2005. ‘‘Estimating RegressionModels in Which the Dependent Variable is Based on Estimates.’’Political Analysis 13 (4): 345–64.


McGillivray, Fiona. 2003. ‘‘Redistributive Politics and Stock PriceDispersion.’’ British Journal of Political Science 33 (3): 367–95.

Mosley, Layna, and David A. Singer. 2008. ‘‘Taking StockSeriously: Equity-Market Performance, Government Policy,and Financial Globalization.’’ International Studies Quarterly52 (2): 405–25.

Pantzalis, Christos, David A. Stangeland, and Harry J. Turtle.2000. ‘‘Political Elections and the Resolution of Uncertainty:The International Evidence.’’ Journal of Banking and Finance24: 1575–604.

Quinn, Dennis. 1997. ‘‘The Correlates of Change in InternationalFinancial Regulation.’’ American Journal of Political Science 91(3): 531–51.

Reinhart, Carmen M., and Kenneth Rogoff. 2004. ‘‘The ModernHistory of Exchange Rate Arrangements: A Reinterpretation.’’Quarterly Journal of Economics 119 (1): 1–48.

Santa-Clara, Pedro, and Rossen Valkanov. 2003. ‘‘The Presiden-tial Puzzle: Political Cycles and the Stock Market.’’ Journal ofFinance 58 (5): 1841–72.

Sattler, Thomas, John R. Freeman, and Patrick T. Brandt. 2008.‘‘Political Accountability and the Room to Maneuver: ASearch for a Causal Chain.’’ Comparative Political Studies 41(9): 1212–38.

Sattler, Thomas, Patrick T. Brandt, and John R. Freeman. 2010.‘‘Democratic Accountability in Open Economies.’’ QuarterlyJournal of Political Science 5 (1): 71–97.

Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. 2007a.‘‘Partisan Impacts on the Economy: Evidence from PredictionMarkets and Close Elections.’’ Quarterly Journal of Economics122 (2): 807–29.

Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. 2007b. ‘‘PartyInfluence in Congress and the Economy.’’ Quarterly Journal ofPolitical Science 2: 277–86.

Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. 2008. ‘‘HowPrediction Markets Can Save Event Studies.’’ CaliforniaInstitute of Technology. Unpublished manuscript.

Tsebelis, George. 2002. Veto Players: How Political InstitutionsWork. Princeton, NJ: Princeton University Press.

Thomas Sattler is a Lecturer in InternationalPolitical Economy at the London School ofEconomics and Political Science, LondonWC2A2AE, United Kingdom.

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do markets punish left governments?

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