Term Length and Political Performance

Ernesto Dal Bó Martín A. Rossi

June 10, 2010

Abstract

We evaluate the e¤ects of a fundamental lever of constitutional design: the duration of o¢ ce terms. We present a simple model grounded in interviews with legislators highlighting opposing forces. We exploit two natural experiments in the Argentine congress (where term lengths were assigned randomly) to ascertain which forces are empirically dominant. Results for an index as well as separate measures of legislative performance show that longer terms enhance performance. In addition, shorter terms appear to worsen performance not due to campaign distractions but due to an investment logic: when returns to e¤ort are not immediate, longer terms yield a higher chance of capturing those returns. Job stability may dilute accountability (as in classic theories of electoral discipline–Barro 1973, Ferejohn 1986) but when e¤ort embodies an investment some stability may strengthen incentives. JEL Classi…cation: H1 Keywords: Term length, political incentives, legislatures.

Ernesto Dal Bó, University of California at Berkeley and NBER, [email protected]; Martín A. Rossi, Universidad de San Andrés, [email protected]. Rossi acknowledges …nancial support through grant PICT 2007-787. We thank Pedro Dal Bó, Erik Eyster, Claudio Ferraz, Je¤ry Frieden, Sebastián Galiani, Martín Gonzalez-Eiras, Neil Malhotra, Ted Miguel, Ernesto Schargrodsky, Ken Shepsle, Mariano Tommasi, and participants at various seminars and conferences for valuable comments and suggestions. We are deeply grateful to legislators Patricia Bullrich, Héctor Maya, Mario Negri, Aldo Neri, Jesús Rodríguez, and Jorge Young who provided expert advice on the functioning of the Argentine Congress. Juan Escobar, Esteban Petruzzello, Orie Shelef, and Gabriel Zourak provided excellent research assistance.

1 1 Introduction

A fundamental question in constitutional design is how long o¢ cials should serve before they can be replaced. One advantage to keeping terms short is that more frequent accountability should allow tighter control over political agents. This notion is formalized in the classic papers by Barro (1973) and Ferejohn (1986) on electoral discipline. In their models, shorter o¢ ce terms lead to less shirking (see Barro 1973, p. 30, for the explicit argument). But a high frequency of elections may discourage e¤ort when rewards are not immediate and may also distract o¢ cials from their work. What force dominates the incentives facing real life politicians? We present a simple model highlighting how longer terms have ambiguous e¤ects on legislative e¤ort, and try to identify the forces that are empirically dominant by exploiting two natural experiments in the Argentine legislature. The …rst instance involves the Argentine House of Representatives in 1983, when 254 House members where randomly assigned to two and four year terms; the second instance involves the Argentine Senate in 2001, where a constitutional reform prompted the random allocation of 71 senators to terms lasting two, four, and six years. The empirical investigation of the e¤ects of term length faces several identi…cation chal- lenges. Consider for example the substantial cross-country variation in the length of legislative terms (see Table 1). This variation, one may think, could help identify the e¤ects of term length on legislative performance. However, the length of terms might have been endogenously selected in response to di¤erent incentive trade-o¤s, hindering identi…cation. An alternative approach would be to focus on a single legislature with staggered terms and compare the behavior of legislators facing reelection at di¤erent points in the future. Amacher and Boyes (1978) followed this approach focusing on the 93rd Congress of the United States. They found that senators closer to reelection voted more in line with House representatives (who presumably proxy for constituency interests). Kalt and Zupan (1990) studied the e¤ects of election proximity for senators in the 95th Congress without …nding a strong e¤ect. Thomas (1985) tracked the voting pattern of senators in their third versus their sixth year between 1959 and 1976, …nding a moderating tendency of election proximity.

2 Lott and Davis (1992) provide further references in this area. Their discussion emphasizes how most of the papers attempting to identify the e¤ects of electoral proximity focused on voting patterns and su¤ered from measurement and speci…cation problems.1 Closer to our focus on shirking, Lott (1987) estimated a negative association between retirement (itself an endogenous variable) and the frequency of voting. Some of the main problems in the existing literature relate to endogeneity as well as confounding the e¤ect of a shrinking term length with time e¤ects, tenure e¤ects, or cohort e¤ects.2 The ideal setting would allow to observe legislators elected at the exact same time, who di¤er only in the term length they are assigned. Our design o¤ers precisely that possibility and avoids the aforementioned identi…cation problems. We …rst analyze the case of the House of Representatives in 1983, for which we have more observations and more measures of performance–in our view, the measures we use capture primarily an e¤ort/shirking dimension of performance. The allocation of two and four year terms was done through a well documented random assignment. We compare the level of legislative performance of the two year legislators to that of their four year counterparts. We do this for the …rst two years of legislative activity, while both groups worked side by side. We follow Kling, Liebman and Katz (2007) in that we …rst study overall e¤ects by aggregating various performance measures into an index of legislative performance. We next study the e¤ect of term lengths on the six individual measures of performance that we obtained: attendance to ‡oor sessions, participation in ‡oor debates (measured by number of speeches), committee activity (attendance to committee sessions and participation in the production of committee bills), the number of bills each member introduced, and how many

1 Lott and Davis reexamine data for United States senators and …nd that the proximity of elections does not signi…cantly a¤ect voting behavior in the United States Senate. The general consensus in the profession since then has converged on the idea that voting patterns in the Congress of the United States are largely independent from electoral pressure (see Poole and Rosenthal 1997 and Lee, Moretti, and Butler 2004). 2 In an interesting paper Crain and Tollison (1977) consider governorships as investment projects and compare campaign expenditures across races for two versus four year positions. They …nd that expenditures are larger when campaigning for a four year governorship than along two consecutive campaigns for two year governorships. The main potential confounding factors here are state e¤ects, and the possibility that di¤erent term lengths may attract di¤erent candidates and di¤erent campaign contributions.

3 of these were approved.3 We …nd a signi…cant e¤ect of a longer term on the performance index as well as on four of the six metrics of performance. Our study of the Senate in 2001 shows a similar pattern. According to our theoretical model incentives to perform get stronger in a shorter term as the “carrot”of reelection lies closer in time (an accountability e¤ect). But the model also highlights two forces operating in the opposite direction. First, if campaigning commitments clash with legislative duties, a shorter term may lower legislative e¤ort (a campaigning ef- fect). Second, if legislative e¤ort yields rewards that accrue over time, a shorter term lowers expectations of reaping those rewards, again discouraging e¤ort (a payback horizon e¤ect). The empirical …ndings suggest that the accountability e¤ect is overriden by the campaigning or the payback horizon e¤ects (or both). The size of the e¤ects is substantial. For example, longer terms increase bill submissions by senators by almost 50%, and they almost double the number of bills by representatives that get approved. Longer terms might be a cost- e¤ective way to promote legislative productivity: Ferraz and Finan (2008) estimate that a 20% increase in wages to local Brazilian legislators increases the number of bills submitted by 25% and the number of bills approved by 22%. Our next step is to determine whether the data can further substantiate the presence of the campaigning and/or the payback horizon e¤ects. We …rst compare the performance of senators who were dealt four versus six year terms, while restricting attention to the …rst two years of their terms, when campaigning commitments are absent. We …nd that the senators in the six year track display stronger performance, suggesting that legislators care about the payback horizon. Could campaigning be a force behind the results in the House? An implication of our model, and a prediction by legislators we interviewed, is that if campaigning drives the e¤ects of term length, then these e¤ects should be stronger among legislators representing geographically remote districts. Those legislators face more of a con‡ict between campaigning and legislating. We fail to …nd evidence of such a pattern.

3 Some of these measures have been used in the context of American politics. For example, Schiller (1995) uses the number of bills sponsored by a legislator to measure performance and …nds among other things that senior senators sponsor more bills than junior ones. Similar results are reported in Hamm, Harmel, and Thompson (1983) for a few state legislatures in the United States.

4 Can we …nd additional evidence of a payback horizon e¤ect in the House? Our model predicts that if payback horizon is the relevant channel, legislators who are electorally safer care less about term length than legislators at risk. The data support this prediction, suggesting that payback horizon e¤ects play a role in the House as well. Our last empirical exercise shows that the e¤ects of term length do not seem to vary with experience. Our results underscore the fact that the advantages of more frequent accountability may be dominated by other forces, such as a need for job stability, at least when terms are short enough. This would occur whenever returns to e¤ort accrue over time, so that e¤ort resembles an investment and a longer guaranteed tenure allows further payback. The legislators we interviewed rated this explanation highlighting an investment logic as highly plausible. We analyzed two di¤erent natural experiments involving two di¤erent chambers at two di¤erent points in time, …nding similar patterns and partly addressing issues of external validity. But much remains to be done to understand comprehensively the e¤ects of term length. Longer terms may eventually back…re, or have di¤erent e¤ects in di¤erent countries. But recent work in a very di¤erent context corroborates our …ndings. Titiunik’s (2008) analysis of state legislatures in Arkansas and Texas where randomizations took place tends to …nd stronger performance by legislators receiving longer terms. The structure of the paper is as follows. In Section 2 we present a simple theoretical model to frame the empirical investigation of the e¤ects of term length. In Section 3 we describe the natural experiment in the House and present the data. In Section 4 we lay out the econometric approach and report the main results from the House. In that section we also discuss threats to identi…cation and robustness. In Section 5 we present data and additional evidence from the Senate. In Section 6 we investigate possible mechanisms behind the e¤ects of term length. Section 7 concludes.

2 The model

As mentioned earlier, the classic works by Barro (1973) and Ferejohn (1986) yield a picture where more frequent elections induce less shirking (see also Schultz 2008 for a model on term length where politicians have private information and set policy under electoral pressure).

5 We postulate a very simple model of legislative e¤ort that is better suited to match the structure of our data and captures other e¤ects. Legislators choose legislative e¤ort e upfront in their term. They must also deploy campaigning e¤ort. There is a basic campaigning e¤ort that all legislators exert, even when they are not up for reelection, simply because they must collaborate with the party e¤ort of behalf of those who face reelection. That basic level is normalized to zero. In addition, legislators facing reelection at the end of a period may face an extra campaign e¤ort outlay c early in that period. Here 0; 1 ; so when = 0 campaigning is purely a team e¤ort, and 2 f g when = 1 those facing reelection meet extra campaign commitments. The commitment c > 0 is assumed exogenous for simplicity, and (in keeping with the legislative sources we interviewed) the campaigning e¤ort depends on the distance 0 between the capital and the legislator’sdistrict. A legislator’s probability of reelection P (e; ) depends on e¤ort e exerted in the term, and an electoral safety shifter . We will typically obviate this latter argument to save on notation. P (e) satis…es dP 0; d2P 0; dP > 0. We impose a technical condition de de2 d d3P requiring that de3 not be too high to avoid uninteresting e¤ects stemming from changes in dP the degree of concavity; also we remain agnostic about the sign of the cross-partial ded and to simplify matters we will assume it is zero (this is not necessary for our results but yields a cleaner analysis). Short Term legislators (ST) face reelection after one period, and Long Term legislators (LT) face reelection after two periods. After the …rst reelection both types of legislator have two period terms (matching our House study) so their prospects contingent on being reelected are identical and have value V .4 Our exposition abstracts from dynamic programming aspects to focus on …rst period e¤ort choices. Each unit of legislative e¤ort yields a stream of unitary returns beginning in the current period in the form of recognition, policy achievements, or legacy. If H = 0 we say the payback horizon is short because e¤ort yields only a unit return in the current period. If H = 1; we say the horizon is long because the stream of returns lasts for two periods (the stream under this long horizon can be made arbitrarily long at some extra notational burden). ST

4 It is easy to show that c low enough yields V > 0, which should hold for legislators to run.

6 legislators have objective,

e (e + c)2 + P (e)(eH + V ) ;

where (e + c)2 is the cost of overall e¤ort in period 1, while LT legislators have objective,

e e2 + eH (c)2 + 2P (e) V:

Writing the …rst order conditions and rearranging we get the following expressions im- plicitly characterizing the …rst term e¤ort levels of ST and LT legislators,5

1 + P eST H + dP V + eST H eST = deST c; (1) 2 1 + H + 2 dP V eLT = deLT : (2) 2

An interior solution (if it exists) is given by the intersection of a 45 degree line (the left hand side) and a function with positive intercept (the right hand side) that cuts the 45 degree line ST 6 ST 1 dP (e ) from above. From (1) and (2), if = 0 and H = 0 e¤ort levels are e = 2 + 2 de V 2 dP (eLT ) and eLT = 1 + V from which eST > eLT for any (0; 1), proving, 2 2 de 2

Proposition 1 If campaigning is a team e¤ort ( = 0), legislative e¤ort yields instantaneous returns only (H = 0), and the more distant future is discounted more heavily ( (0; 1)), then 2 eST > eLT , i.e., short term legislators exert more legislative e¤ort than long term legislators.

The intuition for this result is that if legislative e¤ort yields no future policy returns and campaign commitments are the same for all legislators, a more distant reelection carrot translates into a lower incentive to exert legislative e¤ort today. This “accountability” e¤ect of election proximity requires that the future be taken into account ( > 0) and that more distant dates be discounted more strongly ( < 1). The role of discounting relates this e¤ect,

2 5 The second order conditions for a maximum are, respectively, 2+ d p (V + eH)+2 dP H < 0 and deST 2 deST 2 d2P dP 2 + 2 V < 0: Both are satis…ed if H = 0 under P 00 < 0. If H = 1, it is required that not be too deLT de large. 6 dP (e) Given V > 0, the Inada condition lime 0 = guarantees a solution with positive e¤ort. ! de 1

7 with di¤erences in the precise mechanism at work, to the accountability pressure highlighted in the Barro and Ferejohn papers. But the comparison of e¤ort levels eST and eLT is ambiguous in general if > 0 and/or H > 0. Under some conditions the accountability e¤ect can be dominated by a campaigning and/or a payback horizon e¤ect. In particular,

Proposition 2 a) If = 1 (short term legislators face more campaigning), and the marginal e¤ect of legislative e¤ort on reelection chances is low enough or the discount factor is low enough, then long term legislators exert more e¤ort than short term legislators. b) If H = 1 (the payback horizon is long), reelection is less than fully certain and the marginal e¤ect of legislative e¤ort on reelection chances is low enough, then long term legislators exert more e¤ort than short term legislators.

H(1 P (eST ))+2 dP V dP (V +eST H) deLT deST Proof. The e¤ort di¤erential is e = 2 + c. If the H(1 P (eST )) dP marginal reelection return to e¤ort de approaches zero, we get e = 2 + c, which is positive if either > 0 or H > 0 (and P < 1). To complete the proof for part

dP a), note that if de is not small a discount factor close enough to zero still ensures that the campaigning e¤ect c dominates. This proposition tells us that two di¤erent forces may make long term legislators exert more legislative e¤ort despite a discounted reelection motive. First, short term legislators are busier campaigning during the …rst period–the campaigning e¤ect. Second, these legislators have a shorter guaranteed time during which to reap returns to their e¤ort–the payback horizon e¤ect. Whether any of these e¤ects can overcome the accountability e¤ect is an empirical question. Both the campaigning and the payback horizon channels were deemed plausible by the legislators we interviewed. It is worth mentioning that the tradeo¤ char- acterized by the model has wider applicability. The length of review periods will in most organizations alter the pressure to perform, but also a¤ect in‡uence activities and investment in organization-speci…c projects.

8 3 Natural experiment and data

3.1 The natural experiment in the Argentine House of Represen- tatives

Argentina is a federal republic consisting of twenty four legislative districts: twenty three provinces and an autonomous federal district. The National Congress has two chambers, the Chamber of Deputies (i.e., the House of Representatives) and the Senate.7 At the time of the return to democracy in December 1983, all 254 deputies were elected at the same time, starting their terms on December 10, 1983. The Argentine Constitution stipulates four year terms, no term limits, and the renewal of half the House every two years. In order to stagger the renewal half of the representatives elected in 1983 got two year terms. The allocation of two and four year terms was done through random assignment. The procedure for the random allocation of terms, set by the Comisión de Labor Parla- mentaria (the equivalent of the Rules committee in the United States) involved dividing the representatives into two groups of equal size, Group 1 and Group 2. Each party-province delegation apportioned an equal number of its members to each group (see Table 2).8 During a public session on January 20 of 1984, the Secretario Parlamentario performed a lottery draw, which gave legislators in Group 1 a four year term and legislators in Group 2 a two year term.9 The party-province delegations did not know which group would get assigned the long term when apportioning legislators to groups 1 and 2. One could be concerned that if delegations systematically assigned the better legislators to one particular group then the assignment of term lengths would not be e¤ectively exogenous. But behind a veil of ignorance there would be no reason for risk averse legislators to introduce any imbalance, so we do

7 For descriptions of the Argentine Congress see Molinelli, Palanza, and Sin (1999) and Jones et al. (2007). 8 The two representatives from Tierra del Fuego (the smallest district) were allocated to the same group. In the case that a party had an odd number of representatives from one province the imbalance was corrected with the analogous surplus from another province where the party also had an odd number of representatives. 9 Since the return to democracy in 1983 the two dominant political parties in Argentina have been the Unión Cívica Radical (UCR, or Radical party) and the Partido Justicialista (PJ, or Peronist party). In the period under analysis the majority party was the Unión Cívica Radical.

9 not see this aspect of the design as problematic. In fact, and as shown in Table 3, there are no statistically signi…cant di¤erences in observables across the two groups of legislators according to a di¤erence in means test, suggesting that the randomization was successful.10 We perform two additional balancing tests: (i) A regression of the probability of being assigned to Group 1 or Group 2 on the set of pre-assignment characteristics reveals these characteristics are not signi…cant predictors of assignment (the F statistic p-value is 0.54); (ii) We run a regression of the index of legislative performance on the set of observable characteristics, compute the predicted performance, and then regress predicted performance on a dummy for drawing the long term. We …nd no signi…cant link between term assignment and the part of performance driven by observable characteristics (the coe¢ cient on the long term dummy is not signi…cant; p-value = 0.14) The results of these tests provide additional assurance that the allocation of terms was random. Moreover, the majority of party-province delegations (75%) did the assignment in a way that was essentially random. They assigned legislators occupying an odd-numbered position in the 1983 electoral party list to one group, and those occupying an even-numbered position to the other. Positions in the ticket (i.e., whether a legislator is close to the top or not) depend largely on the demographics of the province area to which the legislator belongs. A second factor a¤ecting list positions is the perceived popularity of the candidate in her area. Thus, whether a legislator is …rst or tenth in her party list is not random, but whether she falls in an even- or odd-numbered position is. The remaining 25% of the delegations did not follow the odd vs. even slot procedure to assign legislators to groups, but by all observable measures their assignment appears random as well. As will be shown, our …ndings are robust to eliminating these delegations from the sample and to clustering standard errors at the party-province level.

10 One may worry that the aggregate data masks systematic unbalancing within parties that cancels out in the aggregate, and that perhaps one imbalanced party spuriously drives results. We ran balancing tests for the two main parties separately and found no pattern of systematic di¤erence. Only one observable is unbalanced for one party (fraction of lawyers for the Partido Justicialista). As we show later, the e¤ect of term length holds for each separate major party.

10 3.2 Data and measures of performance

Our dataset contains yearly information on individual performance and legislator characteristics for the period February 1984 - December 1985. Of the 254 legislators that started their term in December 1983, three resigned and …ve died before December 1985. Thus the sample includes 492 observations corresponding to 246 legislators for two years. The data we got from the Argentine Congress includes six objective measures of legislative performance by each legislator: ‡oor attendance (as percentage of legislative ‡oor sessions), committee attendance (as percentage of committee sessions), number of committee bills in which the legislator participated (as re‡ected on the committee bills bearing the legislator’s signature), number of times the legislator spoke on the ‡oor on a legislative topic, number of bills introduced by the legislator, and number of those bills that were approved. The legislators we interviewed see these metrics as capturing di¤erent types of legislative e¤ort and as connected with the shirking dimension of legislative performance. They also valued the diversity of measures because legislators cultivate di¤erent pro…les. Some legislators may seek to capture the attention of constituents by introducing bills. Others may care more strongly about policy, so they may introduce fewer bills but focus more on approval or on committee work. Floor attendance will re‡ect general involvement with the daily legislative business.11 Table 4 shows the correlation matrix of the measures we use. Most correlations are weak and in some cases negative. In light of this and the feedback from legislators, we believe the metrics we use, while noisy, do proxy for di¤erent and relevant dimensions of legislative performance.12 In order to draw general conclusions in a context of multiple outcomes, we construct an index of legislative performance that aggregates the six measures described above. To construct the index we follow the procedure used by Kling, Liebman, and Katz (2007). The index is the equally weighted average of z-scores of its components. The z-scores are levels

11 To illustrate how attendance may capture forms of involvement, consider the case of César Jaroslavsky (UCR, Province of Entre Ríos), who was not involved in speci…c committee work nor introduced many bills of his own, but who played a central political role as majority leader. He was present in over 94% of all ‡oor sessions, placing second in the attendance ranking. 12 One indication of relevance may be that these metrics are signi…cant predictors of reelection.

11 standardized by using the mean and standard deviation for the two year legislators. In all cases higher performance measures have higher z-scores. The variable of interest is Four-year term, an indicator variable equal to 1 for legislators assigned to an initial four year term and zero otherwise. The database also includes various legislator characteristics, such as age (as of November 1983), the distance in kilometers from the capital of the legislator’s province to Buenos Aires, and a series of dummy variables equal to 1 when the legislator: is male, is a lawyer, is a …rst time national legislator, holds a university degree, occupies a leadership position (i.e., president of the chamber, chair of a committee, and majority or minority leader), belongs to the majority party, and belongs to a small block (i.e., less than four legislators). Representatives in Argentina are elected through a closed party list at the provincial level and not through a special race for a uninominal legislative district, as in the United States. Under the party list system, the degree of electoral safety depends on how high up in the party ticket a legislator …nds herself. For example, in 1983 the UCR had 19 candidates running for the seats corresponding to the province of Santa Fe. But given the party’svote share and the proportional representation system, only the top 10 members were seated. Those legislators close to the 10th position in the ticket faced risk going forward, given that the party’selectoral strength might erode, and that the legislator’sranking in a future party list depends largely on relatively permanent factors, such as the demographics of the legislator’shome area. We develop a dummy variable (Slackness) to capture electoral safety. We say a legislator is safe if she entered Congress within the top half of her party-province delegation (in our example, in the top 5 slots), in which case Slackness is equal to 1. We say she is relatively at risk otherwise, in which case Slackness is equal to zero.

4 Econometric model and results

Given random assignment, the impact of serving an initial four year term relative to serving an initial two year term can be estimated by using the following regression model:

Yit = + Four year termi + Xi + t + "it (3)

12 where Yit is any of the performance measures under study for legislator i in period t (where t = 1984; 1985, the two years following the assignment), is the parameter of interest, Xi is a matrix of legislator characteristics, t is a time e¤ect, and "it is the error term. Table 5 reports estimates of when the dependent variable is the index of legislative performance.13 Results with and without controls indicate that legislators serving a four year term display better performance than those serving a two year term and that the di¤erence is statistically signi…cant. The size of the estimated e¤ect is a third of a standard deviation of the performance distribution. The size of the e¤ect appears considerable relative to the e¤ects of observable characteristics. For instance, the performance di¤erence between the long and short term legislators is more than one and a half times the e¤ect of a university degree, almost one and a half times the impact of being a legislative leader, and roughly the same as the e¤ect of being in the majority party. This underscores the strength of the term length e¤ect. For example, belonging to the majority party has been estimated to play a sizeable role on legislative e¤ectiveness by Padro-i-Miquel and Snyder (2006). To determine whether the e¤ects are wide-ranging or concentrated on just one or two outcomes, we estimate and report in Table 6 the e¤ects on each separate performance metric. The e¤ect of term length appears quite general: the point estimates are positive for all six metrics and statistically signi…cant for four of the six.14 15 Figure 1 shows box-and-whiskers plots comparing the two groups on each measure of performance, which gives a view of the whole distribution of e¤ects. 13 A typical concern when conducting inference for the estimated parameters of Equation 3 is that the errors for the same legislator might not be independent. To address this concern we cluster standard errors at the legislator level, and we later report a speci…cation using data collapsed by legislator. 14 The variables committee bills, ‡oor speeches, bills introduced, and bills rati…ed take discrete values and are strongly skewed to the right with many observations at zero; thus, ordinary least squares estimation would be inappropriate. For all of these variables we were able to reject the hypothesis that the dispersion parameter is equal to zero according to a likelihood-ratio test, which suggests that the correct speci…cation is a negative binomial model for count data as adopted here. 15 One may conjecture that the years 3 and 4 of four year legislators are similar to the years 1 and 2 of the two year legislators, so the former should display a lower performance in their last two years. This conjecture is true (results available upon request), although it could possibly obey to time e¤ects. Thus, the comparison made in the paper provides the best identi…cation of term length e¤ects.

13 The di¤erences in performance tend to be important in size. Focusing on mean e¤ects in the controlled regressions, we see from Table 6 that getting a longer term appears to signi…cantly increase performance on ‡oor attendance by 3% (relative to the mean of the two year legislators). This is a nontrivial e¤ect; as a point of comparison, Lott (1987) estimated a 6% decrease in voting frequency for retiring legislators. Committee attendance is about 12% higher for long term legislators, and the number of committee bills bearing the legislator’ssignature goes up by 19%. Lastly, ‡oor speaking appears to respond by 13% to a longer term although this result is not signi…cant. The idea that longer terms increase performance also appears to be backed by the measures of “bill production.”The point estimate in column (10) in Table 6 indicates that the number of bills introduced goes up by 20%. This estimate, however, is short of signi…cant with clustered standard errors. When we switch attention from the “volume” measure of bill production to the “legislative e¢ cacy” measure, namely the number of bills that pass, the estimates become strongly signi…cant. The point estimate (see column (12) in Table 6) indicates that moving from a two to a four year term almost doubles the number of bills passed.16 Ferraz and Finan (2008) …nd a 22% increase in bills approved when Brazilian local legislators receive wages 20% higher. Thus, the productivity e¤ect of a two year longer term is commensurate with the e¤ect of nontrivial amounts of money. Overall, our results indicate a strong tendency for longer terms to increase legislative performance. Estimates of the control variables (not shown but available upon request) corroborate the perceptions of the legislators we interviewed and lends credence to their statements. In their view, ‡oor speaking is the metric less directly connected to e¤ort, and should be associated …rst and foremost with belonging to a small block. Indeed, this appears to be the strongest determinant of the frequency of ‡oor speaking. They also indicated that occupying a leadership position and being a good orator would be associated with participating in ‡oor

16 We explore an alternative de…nition of bill production that considers not only the bills a legislator introduced but also those that she endorsed. Under the alternative de…nition the coe¢ cient for bills introduced is similar to the one obtained previously. The coe¢ cient for bills rati…ed is smaller, but the magnitude of the e¤ect is still important (moving to a fouryear term increases the number of bills approved by around 45%). The signi…cance levels remain unchanged for both variables.

14 debates. They were right on this count as well. A leadership position is a strong predictor of ‡oor speaking. We do not have a direct measure of oratory skills, but one would imagine that holding a university degree or being a lawyer is correlated with debating abilities. These variables are indeed strongly related to speech giving.

4.1 Robustness checks

To further address the issue that observations are not independently drawn, we collapse the observations by legislator and then cluster the standard errors at the provincial level. As reported in Table 7, our conclusions remain unchanged. In Table 8 we report additional estimations under a wide range of alternative speci…cations and samples. First, the signi…cance of the term length variable is not a¤ected when we cluster standard errors at the district level, or according to party-district combinations. Sec- ond, our conclusions remain unchanged when we restrict the sample to those party-province delegations that used the even/odd rule to assign legislators into the two groups, and when, in addition, we also exclude the …rst two legislators in the party list (we take this extra step because the di¤erence between occupying an even vs. odd position is generally random but one could argue this may not apply to the top 2 positions in the party list). Third, we run separate regressions for the two main parties in order to explore possible heterogeneity in the e¤ect of term lengths according to political party. Despite the smaller sample size, we still …nd a positive and signi…cant association between term length and legislative performance for legislators of both parties. While the point estimate is larger for Peronists, the di¤erence between the two estimates is not statistically signi…cant. Finally, the value and signi…cance of the coe¢ cient of interest remains unchanged when we exclude from the sample legislators that were leaders or those few who changed leader status during the sample period.17

4.2 Potential concerns

Even when our study relies on a well documented randomization, one can still harbor some potential concerns regarding the exogeneity and nature of the treatment. First, it could

17 We experimented with di¤erent de…nitions of leaderhip and always found similar results.

15 be the case that re-optimizations took place after the random assignment that might have a¤ected performance for reasons other than the change in term length. For example, legislators given a four year term could have obtained better committee assignments. Thus, in the presence of hierarchical re-optimization the conclusion that lengthening terms is a good idea would not follow if such extension were to bene…t all legislators. Our experiment is quite unique in that it is well documented that all committee assignments, leadership positions, and placement along the internal hierarchy of the chamber were decided before the assignment of terms was done. Very few re-allocations are observed after the random assignment, and they appear unrelated to term length.18 The results remain unchanged when we exclude from the sample those legislators that changed status as chamber leaders or moved in or out of the most important committees (see the last column in Table 8). A second story is one where parties may direct resources and responsibilities to the long term legislators, discriminating against the others. While our data cannot directly reject such possibility, three observations are due. One, we will show below that the data matches further predictions of our model, in which term length has e¤ects independent of the share of legislators obtaining the longer term. Two, the main way in which such centralized process could work is by means of a¤ecting positions in the internal hierarchy of the House, which as discussed above, was set before the randomization took place. Three, our interviews failed to substantiate the notion that such centralized processes play a role in the Argentine Congress. The view of legislators is that e¤ort choices are essentially an individual decision.19 A third, and perhaps more important, threat to the interpretation of the treatment is this:

18 Only seven legislators left the most important committees after the random allocation of terms (four two year and three four year legislators). Of the seven substitutes, three legislators ended their term in 1985 and four in 1987. Of all legislators who are considered leaders, only two left their position before December 1985 (one two year and one four year legislator). One of the substitutes ended his term in 1985 and the other in 1987. 19 Our working paper version discusses in detail an additional story where, in an overlapping generations context, senior legislators shirk while newly elected ones work hard (so those in the …rst half of their “long” term outperform others). The bottom line is that such schemes involve a genuine treatment e¤ect that occurs linked to a form of individual investment. As we discuss below, an investment logic appears to play a role according to the data.

16 the outcome of the lottery may directly a¤ect the morale of legislators, boosting the spirits of those who got a four year term, and depressing the rest. In this case, the instrument would not be a¤ecting behavior through its e¤ect on term length, but directly through its “win” or “loss”meaning. According to the literature in experimental psychology (see for instance Amsel, 1992), an implication of the “altered morale” hypothesis is that we should observe that the relative performance of legislators given two year terms lags in the beginning, and quickly recovers as spirits revert to normal. As shown in our working paper, an examination of the performance di¤erential across groups on a monthly basis fails to support the idea that four year legislators do better only in the …rst few months. This suggests an e¤ect linked to hard incentives rather than to the lottery having a¤ected morale.

5 Data and additional evidence from the Senate

As a result of a constitutional reform in 1994, the whole Senate needed to be renewed in 2001, when the body’s 71 senators were elected at the same time to start their terms on December 10.20 The modi…cation of term lengths and renewal rates required that some senators be assigned two year terms, others four year terms, and others six year terms. The allocation was done through a well documented random assignment during a public legislative session on December 12 of 2001. The random assignment was performed at the district (i.e., province) level. All three senators from each province were jointly and randomly placed on a two, four, or six year track. One implication of this design is that we cannot use province dummies, although we can control for distance. Examining the Senate episode is important for external validity reasons. It allows us to focus on a di¤erent chamber at a di¤erent historial juncture. Moreover, senators are more notorious and represent the entire province. This dilutes some of the idiosyncracies of the party-list cum proportional representation system. In keeping with the House experiment where the short term legislators were on a two

20 There were 71 senators (instead of 72) because one of the three seats belonging to the federal district was left vacant until 2003. Like House representatives, senators are eligible for reelection and face no term limits.

17 year track, we will begin by comparing senators in the two year track against the rest; accordingly, we will de…ne the Long term variable as a dummy equal to 1 if the senator got a four or six year term, and zero otherwise. Table 9 exhibits the summary statistics, showing that the predetermined observables are largely balanced. The only one observable that shows a signi…cant di¤erence between the short and long term legislators is distance, which is not an individual but a delegation characteristic. This is not incompatible with chance when measuring nearly ten observables over two di¤erent experiments. Moreover, we ran further balancing tests like with did with the House data. We found no ability of observable characteristics to predict assignment or a component of performance that signi…cantly correlates with assignment. Our dataset for the Senate contains yearly information on legislative performance and legislator characteristics for the two year period starting in December 2001 and ending in December 2003. We could obtain only three objective measures of legislative performance: ‡oor attendance, the number of bills introduced by each legislator, and the number of bills approved. Of the 71 legislators that started their term in December 2001, six resigned before December 2003. Thus the sample includes 130 observations corresponding to 65 legislators for two years. Again, in order to draw general conclusions in a context of multiple outcomes we use an index of legislative performance. In columns (1) and (2) in Table 10 we show results with and without controls showing e¤ects that are about a third larger than those in the House, although in a context of fewer observations the result becomes insigni…cant in the controlled clustered regression.21 Delving into the individual metrics of performance (columns (3)-(5)), we …nd that the change of receiving a longer term over the mean performance of the two year senators is of 2% for ‡oor attendance (an e¤ect similar to that in the House), 49% for the number of bills introduced, and 27% for the number of bills passed. As shown in Table 10, only one of theses di¤erences is signi…cant. However, the di¤erences in all three metrics go in favor of the long term legislators, which is informative. The e¤ect on bills introduced is

21 When we consider three treatments categories (two, four, and six year terms) we …nd that the point estimate of being assigned to a four year term is positive but smaller than the one associated to being assigned to a six year term. In other words, e¤ects appear to get stronger the longer the term assigned.

18 statistically signi…cant and its magnitude is large. To provide an idea of the potential money value of the e¤ect, note that Ferraz and Finan (2008) estimate that a 20% wage raise for local legislators in Brazil increases bills submitted by 25%. Thus e¤ect of extending terms for senators in Argentina appears to be twice that of a 20% increase in wages in Brazil. Overall, the picture from the Senate corroborates the one we obtained from the House.

6 Investigating mechanisms

6.1 Campaigning and payback horizon

Legislators with longer terms appear in average to exert more e¤ort both in the House and the Senate. According to our model in Section 2 this could be due to campaigning keeping short term legislators busier (in terms of the model, = 1) or to legislative e¤orts yielding returns that accrue in the future (in terms of the model, H = 1). To investigate whether any of these forces could be at play, in this section we rely further on our model and our data. Test 1 - Campaigning vs. Payback Horizon - Senate A straightforward test is possible in the context of the Senate. We can compare four vs six year senators during their …rst two years in o¢ ce, when none of them are campaigning. In terms of the model, that amounts to = 0. It follows from Propositions 1 and 2 that for eLT > eST it is necessary that the payback horizon channel be present, i.e., that H = 1. Columns (1) and (2) of Table 11 report estimates obtained by excluding from the sample all senators in the two year track, keeping only those in the four and six year tracks. The Long term variable is now equal to 1 for six year senators and zero for the four year senators. The results favor the view that six year legislators perform better than four year legislators during the …rst two years of their tenures. This suggests that it is not campaigning distractions but a concern with the payback horizon that induces long term legislators to work harder. This test is not feasible in the House given the lack of six year terms. But another test is feasible and we present it immediately below. Test 2 - Campaigning - House The legislators we interviewed indicated that campaigning commitments arrive as the

19 election nears; they also told us that campaigning, which requires presence in the home district, poses a larger con‡ict with legislative performance for legislators from geographically remote districts. Thus, according to the legislators we interviewed, if campaigning distractions drive the e¤ect of term length this e¤ect should be stronger among representatives from distant districts. H(1 P (eST ))+ dP V dP (V +eST H) In our model, the e¤ort di¤erential is eLT eST e = deLT deST + 2 c. The second term of this di¤erential clearly increases with and captures the direct e¤ect described by legislators. Under our assumptions on the function P (e), we can state,

Proposition 3 If campaigning drives term length e¤ects (i.e., if = 1 causes e > 0) then these e¤ects must increase with geographic distance .

Proof. See Appendix. This proposition says that if campaigning drives term length e¤ects an interaction between the Long term dummy and distance should be positive. As reported in column (3) of Table 11, the coe¢ cient of that interaction has the wrong sign and is insigni…cant (p-value: 0:57). We fail to …nd support for the campaigning hypothesis in the House. It seems prima facie counter-intuitive that campaigning, being a time demanding activity, would not appear to di¤erentially damage the short term legislators. One possibility is that campaigning does not really pose a stronger con‡ict with legislation for those representing more remote districts–so the distance-based test is misguided. But legislators appear to be right that campaigning is costlier for representatives from remote districts.22 Another possibility is that, as pointed out by the legislators we interviewed, campaigning in Argentina is to a great extent a team e¤ort at the party level. Legislators that are not running for o¢ ce often campaign alongside those who are, which in the language of our model would yield = 0.

22 For example, ‡oor attendance, to take a metric directly related to physical location, diminishes more in the second year for legislators from remote districts (e.g., 1,500 kilometers away), indicating campaigning takes a statistically detectable toll. But belonging to those more remote districts does not signi…cantly a¤ect the size of the term length e¤ect on ‡oor attendance, suggesting that the term length e¤ect is not driven by campaigning. We thank a referee for suggesting this check.

20 As the House data show that long term legislators exert more e¤ort, and we cannot say that campaigning e¤ects drive that result, it would be desirable to have additional con…rmation of the presence of a payback horizon e¤ect in the House. Test 3 - Payback Horizon - House Not being able to reject the null that = 0, we now investigate the presence of the payback horizon e¤ect by looking at variation in a measure of “electoral safety” . Under the null that = 0 and our assumptions on the function P (e), we can state,

Proposition 4 If the extension of the payback horizon drives term length e¤ects (i.e., if = 0 and H = 1 causes e > 0) then these e¤ects must decrease with electoral safety .

Proof. See Appendix. This proposition captures the intuition that if the payback horizon hypothesis is true legislators who are electorally safer should care less about the term length they get than those at risk. In one extreme, term length does not a¤ect the expected time in o¢ ce of someone whose reelection is guaranteed. In the other extreme, a term length extension of one day increases by one full day the expected tenure of someone who is certain not to be reelected. (Formally, notice the e¤ort di¤erential e contains a term H (1 P ) so the 2 payback horizon matters in inverse proportion to electoral certainty.) Thus, if the payback horizon channel drives our main …ndings, an interaction variable between being safer and getting the longer term should be negative. The variable capturing electoral safety, “Slackness,” was introduced in Section 3. In column (4) of Table 11 we report results indicating that the interaction of the Four year term variable and the electoral safety measure is indeed negative and statistically signi…cant. In other words, the e¤ects of term length are stronger among “at risk”legislators. Moving from the bottom half to the top half of one’sparty-province delegation undoes two-thirds of the e¤ect of being dealt a longer term. These results suggest that the payback horizon plays a role in the term length e¤ects found in the House, and in turn imply that legislative e¤ort contains an investment aspect. We believe the investment logic is plausible given the time structure of legislative activity. The mean time lag since the introduction of a bill to its approval was, in our sample period,

21 of 327 days, even abstracting from the time spent preparing the bill. Also, a legislator will often have to decide whether to spend time absorbing information that will be useful while a policy issue remains current, which may be a few years.23 Alternatively, a legislator may buy an apartment close to the legislature in order to lower her future costs of attending meetings, or shut down her private law …rm to more fully focus her time and attention on legislation. These costs are slow to amortize and legislators with shorter terms may decide not to incur them. In addition, a change from a two to a four year term should signi…cantly a¤ect the e¤ective payback horizon facing Argentine legislators: reelection rates in Argentina have been traditionally low (around 25% for our sample).24

6.2 Does experience matter?

Lastly, we enquire about the nature of the potential investments involved in legislative activity. This is useful from the perspective of the optimal design of terms. One possibility is that investments, once accumulated, render legislators unresponsive to term lengths. This would be the case for instance if longer terms a¤ected performance because they foster learning by doing about general legislative aspects that do not depreciate. Another possibility is that investments depreciate and new investment must be made. If the …rst possibility were true, the investment logic would be relevant early in a legislative career. Then it could be optimal to allow inexperienced legislators a long …rst term in order to incentivize initial investments, while having more senior legislators face shorter terms in order to bene…t from stronger accountability. If the second possibility were true, term lengths could be determined as they are now, without regard to seniority. In order to explore what type of investment predominates, we ask whether the e¤ects of term lengths are stronger for inexperienced senators. We rely on the 2001 Senate data

23 As one legislator put it to us (our translation from the Spanish), “The library of Congress is vast...you can do a ‘doctorate’in here, as some of the committees deal with really complex issues. Obviously, if you are going to be around for longer, you dig in more...” 24 The average reelection rate for the 1983-2001 period was 20% (see Jones, Saiegh, Spiller and Tommasi 2002). The reelection rates for the years 1985 and 1987 were 30% and 22% respectively, and are not statistically di¤erent.

22 because, given the dictatorship in the period 1976-1983, there were only a handful of House members with previous legislative experience in 1983. In columns (5) and (6) of Table 11 we estimate speci…cations including an interaction between the Long term variable (four and six year terms) and Freshman for senators. If once-and-for-all investments are what drive the investment logic, we would expect experienced senators to care less about what term length they get. In other words, we would expect the interaction between Freshman and the Long term variable to be positive and signi…cant. We …nd that interaction to be not signi…cant and to have the incorrect sign in the model with controls. We conclude that investments either depreciate after a few years, or are related to varied and continuing opportunities that are also valuable for experienced legislators. As a result, nothing indicates that term lengths should be determined with regard to seniority, since the bene…ts of longer terms appear to accrue to experienced legislators too.

7 Conclusion

Term length is a fundamental aspect of constitutional design. To the best of our knowledge, this is the …rst investigation that relies on natural experiments to study how term length a¤ects political performance. We frame our empirical investigation with a theoretical model highlighting competing forces. On the one hand, longer terms push the reward of reelection farther into the future (a weakened accountability e¤ect). On the other hand, longer terms may free legislators from campaigning, as well as increase the chance that they will be around to bene…t from their past legislative involvement (the campaigning and payback horizon e¤ects, respectively). Results from two natural experiments in the Argentine House and Senate, where the length of terms was randomized, suggest that the accountability e¤ect is dominated by one or both of the campaigning and payback horizon e¤ects. In this paper we take steps not just to investigate whether term lengths matter and in which direction, but also to gain insight on why they matter. Our data does not allow us to say that campaigning drives results, while supporting the idea that the payback horizon matters to legislators. Our results suggest that even though accountability may be important,

23 in the context we study incentives seem to be strengthened by job stability. While forms of job stability may weaken accountability, some stability in the form of a longer term may strengthen incentives when e¤ort embodies an investment. The issue of term lengths and more generally the bene…ts of job stability should be important not only to politics but to the private sector, where the accumulation of …rm-speci…c human capital is deemed relevant. There is evidence that longer tenures are associated with more productivity (Auer, Berg and Coulibaly 2005) and that lower expected turnover induces forms of e¤ort with an investment component, such as take up of job-speci…c training (Beeson Royalty 1996). Surprisingly, there is a dearth of empirical work at the micro level that can neatly identify the e¤ects of a guaranteed longer tenure on employee incentives, presumably due to the identi…cation di¢ culties that have hindered analogous studies in politics to date. Hopefully our approach can provide a blueprint for studies extending attention to other political settings and labor relations more generally.

8 Appendix

Proof of Proposition 3: Di¤erentiating the …rst order conditions with respect to yields, dP dV dP dV ST +2c LT de de d de de d dV = 2 and = 2 . It is easy to show that < 0, so numer- d 2+ d P (V +eH)+2 dP H d 2 + d P V d de2 de de2 ators are both positive, while denominators are negative from the second order conditions.

deST The numerator in d is larger by 2c, implying that if the denominators are close then an increase in distance reduces e¤ort more strongly among ST than LT legislators, yielding the

deST result. What is needed is that the denominator for d not be a lot higher. It is easy to

show that this is ruled out by our assumption on P 000 (e). Proof of Proposition 4: Di¤erentiating the …rst order conditions with respect to dP (eST ) ST dP dV LT dP dV de de d + d de de d dV yields, = 2 and = 2 . It is easy to show that > 0, d 2+ d P (V +eH)+2 dP H d 2 + d P V d de2 de de2 so both comparative statics are positive and the one for ST legislators has an extra positive dP (eST ) term involving d . Under the same conditions guaranteeing that denominators are close deST deLT de in the proof to Proposition 3 we obtain that d > d implying d < 0.

24 9 References

Amacher, Ryan and William J. Boyes (1978). Cycles in senatorial voting behavior: implica- tions for the optimal frequency of elections, Public Choice 33 (1), 5-13. Amsel, Abram (1992). Frustration theory: An analysis of dispositional learning and memory. Cambridge, UK: Cambridge University Press. Auer, Peter, Berg, Janine, and Ibrahim Coulibaly (2005). Is a Stable Workforce Good for Productivity?, International Labour Review 144(3), 319-343. Barro, Robert (1973). The control of politicians, an economic model, Public Choice 14(1), 19-42. Beeson Royalty, Anne (1996). The E¤ects of Job Turnover on the Training of Men and Women, Industrial and Labor Relations Review 49(3), 506-521. Crain, Mark and Robert D. Tollison (1977). Attenuated property rights and the market for governors, Journal of Law and Economics 20 (1), 205-211. Ferejohn, John (1986). Incumbent performance and electoral control, Public Choice 50, 5-26. Ferraz, Claudio and Frederico Finan (2008). Motivating Politicians: The Impacts of Monetary Incentives on Quality and Performance, IZA Discussion Paper No. 3411 Hamm, Keith, Robert Harmel, and Robert Thompson (1983). Ethnic and partisan mi- norities in two southern state legislatures, Legislative Studies Quarterly 8, 177-189. Jones, Mark, Sebastian Saiegh, Pablo Spiller, and Mariano Tommasi (2002). Amateur Legislators –Professional Politicians: The Consequences of Party-Centered Electoral Rules in a Federal System, American Journal of Political Science 46(3), 656-669. Jones, Mark, Sebastian Saiegh, Pablo Spiller, and Mariano Tommasi (2007). Congress, political careers, and the provincial connection. In Pablo Spiller and Mariano Tommasi (eds.), The institutional foundations of public policy in Argentina, Cambridge University Press. Kalt, Joseph and Mark Zupan (1990). The apparent ideological behavior of legislators: testing for principal-agent slack in political institutions, Journal of Law and Economics 33 (1), 103-131. Kling, Je¤rey, Je¤rey Liebman, and Lawrence Katz (2007). Experimental Analysis of

25 Neigborhood E¤ects, Econometrica 75 (1), 83-119. Lee, David, Enrico Moretti, and Matthew Butler (2004). Do voters a¤ect or elect policies? Evidence from the U.S. House, Quarterly Journal of Economics 119 (3), 807-859. Lott, John R. Jr. (1987). Political cheating, Public Choice 52, 169-186. Lott, John R. Jr. and Michael Davis (1992). A critical review and an extension of the political shirking literature, Public Choice 74, 461-484. Molinelli, Guillermo, Valeria Palanza, and Gisela Sin (1999). Congreso, presidencia y justicia en Argentina. Materiales para su estudio. Buenos Aires: Temas Grupo Editorial. Padró i Miquel, Gerard and James Snyder (2006). Legislative E¤ectiveness and Legisla- tive Careers, Legislative Studies Quarterly 31(3), 347-381. Poole, Keith and Howard Rosenthal (1997). Congress: a political-economic history of roll call voting, Oxford University Press. Schiller, Wendy (1995). Senators as political entrepreneurs: using bill sponsorship to shape legislative agendas, American Journal of Political Science 39, 186-203. Schultz, Christian (2008). Information, polarization and term length in democracy, Jour- nal of Public Economics 92 (5-6), 1078-1091. Thomas, Martin (1985). Election proximity and senatorial roll call voting, American Journal of Political Science 29 (1), 96-111. Titiunik, Rocío (2008). Drawing your senator from a jar: term length and legislative behavior, Mimeo UC Berkeley.

26 Table 1. Duration of terms in selected legislatures Term duration Countries, and states in the United States of America (years) United States House of Representatives US states: Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Massachusetts, 2 Michigan, Minnesota, Missouri, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming 3 Australia, Bhutan, El Salvador, Mexico, Nauru, New Zealand, and Philippines Albania, Andorra, Angola, Armenia, Argentina, Austria, Belgium, Bosnia and Herzegovina, Brazil, Bulgaria, Chad, Chile, Colombia, Costa Rica, Croatia, Denmark, Dominican Republic, Germany, Ghana, Greece, Guatemala, Haiti, Honduras, Hungary, Iran, Iraq, Japan, Jordan, 4 Kazakhstan, Kiribati, Lebanon, Liechtenstein, Lithuania, Macedonia, Madagascar, Mauritius, Moldova, Mongolia, Montenegro, Netherlands, Nigeria, Poland, Portugal, Romania, Russia, Slovakia, Solomon Islands, South Korea, Spain, Syria, Tuvalu, and Vanuatu US states: Alabama, Louisiana, Maryland, Mississippi, Nebraska, and North Dakota Afghanistan, Antigua and Barbuda, Azerbaijan, Bahamas, Bangladesh, Barbados, Benin, Bolivia, Botswana, Burkina Faso, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Central African Republic, China, Comoros, Cuba, Cyprus, Czech Republic, Democratic Republic of the Congo, Djibouti, Dominica, Egypt, Ethiopia, Fiji, France, Gabon, Gambia, Grenada, Guinea, Guyana, India, Ivory Coast, Jamaica, Kyrgyzstan, Laos, Lesotho, 5 Luxembourg, Malawi, Malaysia, Mali, Malta, Mauritania, Monaco, Morocco, Mozambique, Namibia, Nicaragua, Niger, North Korea, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Republic of the Congo, Saint Lucia, Samoa, San Marino, Senegal, Seychelles, Sierra Leone, Singapore, South Africa, Suriname, Tajikistan, Tanzania, Togo, Tunisia, Turkey, United Kingdom, Uruguay, Uzbekistan, Vietnam, Zambia, and Zimbabwe 6 Liberia, Sri Lanka, Sudan, and Yemen Note: when the legislature consists of a lower and an upper house, we consider the lower house.

Table 2. Distribution of legislators by province and political party for the random allocation of terms Group 1 (later assigned a four year term) Group 2 (later assigned a two year term) District Total UCR PJ PI UCD DC AUT MPJ MPN PB Total UCR PJ PI UCD LIB MFP MPN PB Total Capital 25 7 3 - 1 1 - - - - 12 7 4 1 1 - - - - 13 Buenos Aires 70 18 16 1 ------35 19 15 1 - - - - - 35 Catamarca 5 1 1 ------2 1 2 ------3 Córdoba 18 6 3 ------9 5 4 ------9 Corrientes 7 2 1 - - - 1 - - - 4 1 1 - - 1 - - - 3 Chaco 7 1 2 ------3 2 2 ------4 Chubut 5 2 1 ------3 1 1 ------2 Entre Ríos 9 2 2 ------4 3 2 ------5 Formosa 5 1 2 ------3 1 1 ------2 Jujuy 6 1 1 - - - - 1 - - 3 1 2 ------3 La Pampa 5 1 1 ------2 1 1 - - - 1 - - 3 La Rioja 5 1 2 ------3 1 1 ------2 Mendoza 10 3 2 ------5 3 2 ------5 Misiones 7 2 2 ------4 2 1 ------3 Neuquén 5 1 ------1 - 2 1 1 - - - - 1 - 3 Río Negro 5 2 1 ------3 1 1 ------2 Salta 7 2 2 ------4 1 2 ------3 San Juan 6 1 1 ------1 3 1 1 - - - - - 1 3 San Luis 5 1 1 ------2 2 1 ------3 Santa Cruz 5 1 1 ------2 1 2 ------3 Santa Fe 19 5 5 ------10 5 4 ------9 S. del Estero 7 2 2 ------4 1 2 ------3 Tucumán 9 2 3 ------5 2 2 ------4 T. del Fuego 2 ------1 1 ------2 TOTAL 254 65 55 1 1 1 1 1 1 1 127 64 56 2 1 1 1 1 1 127 Notes: UCR is Unión Cívica Radical; PJ is Partido Justicialista; PI is Partido Intransigente; UCD is Unión del Centro Democrático; DC is Democracia Cristiana; AUT is Partido Autonomista; MPJ is Movimiento Popular Jujeño; MFP is Movimiento Federalista Pampeano; MPN is Movimiento Popular Neuquino; PB is Partido Bloquista de San Juan; LIB is Partido Liberal.

Table 3. Summary statistics - House Long track Short track Difference of means Floor attendance (in %) 82.346 79.833 2.513** (0.733) (0.726) (1.032) Committee attendance (in %) 56.507 50.872 5.635** (1.543) (1.552) (2.188) Number of committee bills 47.336 41.397 5.939* (2.366) (2.224) (3.247) Number of floor speeches 5.616 4.339 1.277 (0.561) (0.569) (0.800) Number of bills introduced 6.224 5.496 0.728 (0.655) (0.587) (0.879) Number of bills ratified 0.276 0.128 0.148*** (0.042) (0.025) (0.049) Index of legislative performance 0.205 0 0.205*** (0.038) (0.032) (0.050) Age 50.168 50.868 -0.700 (0.959) (0.926) (1.333) Male 0.944 0.967 -0.023 (0.021) (0.016) (0.026) Freshman 0.944 0.934 0.010 (0.021) (0.023) (0.031) Lawyer 0.368 0.273 0.095 (0.043) (0.041) (0.059) University degree 0.184 0.157 0.027 (0.035) (0.033) (0.048) Leader 0.136 0.083 0.053 (0.031) (0.025) (0.040) Slackness 0.600 0.521 0.079 (0.044) (0.046) (0.063) Majority party 0.504 0.488 0.016 (0.045) (0.046) (0.064) Small block 0.056 0.058 -0.002 (0.021) (0.021) (0.030) Distance 6.598 6.82 -0.220 (0.515) (0.572) (0.769) Note: Standard errors are in parentheses. The long track corresponds to a four year term. The short track corresponds to a two year term. Leader is a dummy variable equal to 1 when the legislator is the president of the chamber, a majority or minority leader, or a committee chair. Freshman is a dummy equal to 1 for Representatives without any previous legislative experience at the national level. Slackness is a dummy equal to 1 if, given the party-province list in the 1983 elections, the legislator placed in the top half of the elected delegation. Small block is a dummy equal to 1 when the legislator belongs to a party holding three or fewer seats. Distance is the distance (in hundreds of kilometers) from the capital of the legislator’s district to Buenos Aires (the seat of the national legislature). The number of observations is 492. *Significant at the 10% level; **Significant at the 5% level; ***Significant at the 1% level, based on a t-test of equality of means.

Table 4. Correlations among measures of legislative performance Floor Committee Committee Floor Bills Bills Attendance attendance bills speeches introduced ratified Floor attendance 1 Committee attendance 0.39 1 Committee bills 0.27 0.49 1 Floor speeches 0.04 -0.09 -0.08 1 Bills introduced -0.02 0.05 0.18 0.04 1 Bills ratified 0.16 0.03 0.07 0.15 0.13 1 Note: correlations computed on raw data observed on yearly basis. Collapsing the data by individual yields similar results. Table 5. The effects of term length on legislative performance Index of legislative performance (1) (2) (3) Four year term 0.205 0.188 0.186 {0.061}*** {0.062}*** {0.063}*** Age 0.0004 0.001 {0.003} {0.003} Male 0.082 -0.004 {0.165} {0.137} Freshman 0.088 0.124 {0.181} {0.172} Lawyer 0.031 0.055 {0.074} {0.073} University degree 0.115 0.117 {0.071}* {0.076} Leader 0.201 0.211 {0.110}* {0.113}* Slackness -0.021 -0.023 {0.058} {0.060} Majority party 0.134 0.128 {0.064}** {0.065}** Small block 0.132 0.140 {0.155} {0.147} Distance -0.006 {0.005} District dummies No No Yes Notes: Standard errors clustered at the legislator level are in braces. All models include a time dummy and are estimated by OLS. The number of observations is 492. *Significant at the 10% level; **Significant at the 5% level; ***Significant at the 1% level.

Table 6. The effects of term length on legislative performance by outcome Floor attendance Committee attendance Committee bills (1) (2) (3) (4) (5) (6) Four year term 2.513 2.548 5.635 6.259 0.133 0.175 {1.076}** {0.956}*** {2.764}** {2.498}*** {0.099} {0.108}* Change 3% 3% 11% 12% 14% 19% Controls No Yes No Yes No Yes Method OLS OLS OLS OLS Negbin Negbin

Floor speeches Bills introduced Bills ratified (7) (8) (9) (10) (11) (12) Four year term 0.263 0.122 0.133 0.184 0.753 0.669 {0.197} {0.172} {0.184} {0.135} {0.256}*** {0.249}*** Change 30% 13% 14% 20% 112% 95% Controls No Yes No Yes No Yes Method Negbin Negbin Negbin Negbin Negbin Negbin Notes: Standard errors clustered at the legislator level are in braces. For OLS models, Change is calculated as 100*Estimate/mean of the respective output for legislators in a two year track. For Negbin (Negative Binomial) models, Change is calculated as 100*[exp(Estimate)-1]. All models include a time dummy. Controls include Age, Male, Freshman, Lawyer, University degree, Leader, Slackness, Majority party, Small block, and the set of district dummies. The number of observations is 492. *Significant at the 10% level; **Significant at the 5% level; ***Significant at the 1% level.

Table 7. Robustness check: data collapsed at the legislator level and standard errors clustered at the district level Index Floor Committee Committee Floor Bills Bills attendance attendance bills speeches introduced ratified (1) (2) (3) (4) (5) (6) (7) Four year term 0.242*** 2.573*** 7.888*** 0.176** 0.123 0.182 0.666** (0.075) (0.926) (2.309) (0.090) (0.200) (0.175) (0.285) Change 3% 16% 19% 13% 20% 95% Controls Yes Yes Yes Yes Yes Yes Yes Method OLS OLS OLS Negbin Negbin Negbin Negbin Notes: Standard errors clustered at the district level are in parentheses. For OLS models, Change is calculated as 100*Estimate/mean of the respective output for legislators in a two year track. For Negbin (Negative Binomial) models, Change is calculated as 100*[exp(Estimate)-1]. Change is not calculated for the Index since this variable is normalized to zero for legislators in a two year track. Controls include Age, Male, Freshman, Lawyer, University degree, Leader, Slackness, Majority party, Small block, and the set of district dummies. The number of observations is 246. **Significant at the 5% level; ***Significant at the 1% level. Table 8. Additional robustness checks Index of legislative performance (1) (2) (3) (4) Four year term 0.186*** 0.186*** 0.156*** 0.255*** [0.055] (0.057) {0.058} {0.068} Controls Yes Yes Yes Yes Observations 492 492 316 168

(5) (6) (7) (8) Four year term 0.157** 0.274** 0.207*** 0.180*** {0.065} {0.121} {0.066} {0.064} Controls Yes Yes Yes Yes Observations 244 220 438 472 Notes: Standard errors clustered at party/district combinations are shown in brackets in column (1). Standard errors clustered at the district level are shown in parentheses in column (2). Standard errors clustered at the legislator level are in braces in columns (3)-(8). Regression (3) includes only those party-province delegations that used the even/odd rule in order to assign legislators into the two groups, whereas regression (4) also excludes the first two legislators in the party list. Regression (5) includes only majority party (Unión Cívica Radical) legislators, whereas regression (6) includes only minority party (Partido Justicialista) legislators. Regression (7) excludes legislators that are leaders, and regression (8) excludes those legislators that change leader status during the sample period. All models include a time dummy and are estimated by OLS. Controls include Age, Male, Freshman, Lawyer, University degree, Leader, Slackness, Majority party, Small block, and the set of district dummies. **Significant at the 5% level; ***Significant at the 1% level. Table 9. Summary statistics - Senate Long track Short track Difference of means Floor attendance (in %) 83.345 80.975 2.3705 (1.267) (2.090) (2.445) Number of bills introduced 33.591 23.476 10.115 (3.134) (2.869) (4.249)** Number of bills ratified 2.318 1.667 0.652 (0.361) (0.294) (0.466) Age 50.750 52.238 -1.488 (1.276) (1.801) (2.207) Male 0.591 0.714 -0.123 (0.075) (0.101) (0.126) Freshman 0.545 0.571 -0.026 (0.076) (0.111) (0.134) Lawyer 0.455 0.333 0.121 (0.076) (0.105) (0.130) University degree 0.273 0.476 -0.203 (0.068) (0.112) (0.131) Leader 0.705 0.619 0.085 (0.070) (0.109) (0.129) Majority party 0.341 0.286 0.055 (0.072) (0.101) (0.124) Small block 0.091 0.190 -0.010 (0.044) (0.088) (0.098) Distance 1284.432 983.715 300.718 (108.178) (71.909) (129.896)** Note: Standard errors are in parentheses. The long track corresponds to four and six year terms. The short track corresponds to a two year term. Leader is a dummy variable equal to 1 when the legislator is the president of the chamber, a majority or minority leader, or a committee chair. Freshman is a dummy equal to 1 for Representatives without any previous legislative experience at the national level. Small block is a dummy equal to 1 when the legislator belongs to a party holding three or fewer seats. Distance is the distance (in hundreds of kilometers) from the capital of the legislator’s district to Buenos Aires (the seat of the national legislature). The number of observations is 130. **Significant at the 5% level, based on a t-test on equality of means.

Table 10. Evidence from the Senate Index of legislative Floor Bills Bills ratified performance attendance introduced (1) (2) (3) (4) (5) Long term 0.353 0.298 1.299 0.402 0.241 {0.192}* {0.231} {2.822} {0.165}*** {0.221} Change 2% 49% 27% Method OLS OLS OLS Negbin Negbin Controls No Yes Yes Yes Yes Notes: Standard errors clustered at the legislator level are in braces. For OLS models, Change is calculated as 100*Estimate/mean of the respective output for legislators in a short track. For Negbin (Negative Binomial) models, Change is calculated as 100*[exp(Estimate)-1]. Change is not calculated for the Index since this variable is normalized to zero for legislators in a short track. All specifications include a time dummy. Controls include Age, Male, Freshman, Lawyer, University degree, Leader, Majority party, Small block, and Distance. The number of observations is 130. *Significant at the 10% level; ***Significant at the 10% level.

Table 11. Tests for the campaigning and the time-horizon hypotheses Index of legislative performance (1) (2) (3) (4) (5) (6) Senate Senate House House Senate Senate Long term 0.449 0.451 0.226 0.300 0.342 0.346 {0.241}* {0.248}* {0.103}** {0.090}*** {0.279} {0.338} Long term x Distance -0.006 {0.010} Long term x Slackness -0.207 {0.127}* Long term x Freshman 0.020 -0.085 {0.387} {0.462} Distance 0.00002 -0.004 0.00008 {0.0002} {0.007} {0.0002} Slackness -0.019 0.080 {0.058} {0.079} Controls No Yes Yes Yes No Yes District dummies No No No Yes No No Observations 88 88 492 492 130 130 Notes: Standard errors clustered at the legislator level are in braces. In regressions (1) and (2), which exclude two year Senators, Long term is a dummy variable equal to 1 for senators in a six year track and zero for senators in a four year track. In regressions (3) and (4) Long term is a dummy equal to 1 for representatives in a four year track and zero otherwise. In regressions (5) and (6) Long term is a dummy equal to 1 for senators in either a four year or a six year track and zero for senators in the two year track. Distance is the distance (in hundreds of kilometers) from the capital of the legislator’s province to Buenos Aires (the seat of Congress). Slackness is a dummy equal to 1 if, given the party-province list in the 1983 election, the legislator is placed in the top half of the elected delegation. Freshman is a dummy equal to 1 for senators without any previous legislative experience at the national level. All models include a time dummy and are estimated by OLS. Additional controls include Age, Male, Freshman, Lawyer, University degree, Leader, Majority party, and Small block. *Significant at the 10% level; **Significant at the 5% level; ***Significant at the 1% level.

Figure 1. Box-and-whiskers plot by type of legislative outcome (4-year vs. 2-year tracks)

2 years 2 years

4 years 4 years

20 40 60 80 100 0 20 40 60 80 100 Floor attendance Committee attendance

2 years 2 years

4 years 4 years

0 50 100 150 200 0 20 40 60 80 Committee bills Floor speeches

2 years 2 years

4 years 4 years

0 20 40 60 80 100 0 1 2 3 4 Bills introduced Bills ratified

2 years

4 years

-2 0 2 4 Index