Socioeconomic Actors, Political Technologies, and Endogenous Institutions: Towards a Framework for the Study of Political Institutionalization

Carlos Scartascini(Inter-American Development Bank)

Mariano Tommasi (Universidad de San Andrés and Inter-American Development Bank)

Laura Trucco(Harvard University)

December 2010

We thank Marcelo Leiras, Christian Ruzzier and Federico Weinschelbaum for valuable conversations on some of the issues addressed in this paper and for useful suggestions.

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Socioeconomic Actors, Political Technologies, and Endogenous Institutions: Towards a Framework for the Study of Political Institutionalization

I. INTRODUCTION....................................................................................................................3

Institutionalization and Political Investments..........................................................................4

The Consequences of Institutionalized Policymaking...............................................................8

II. THE FRAMEWORK..............................................................................................................10

Model 1: Investing in the ability to enforce policy agreements.............................................12

Solving Model 1......................................................................................................................17

III. EXTENSIONS (Investing to control political agents)........................................................23

Institutions and Alternative Political Technologies.................................................................23

Model 2: Investing in institutions or in an alternative political technology............................24

Model 3: Institutions, corruption, and the use of violence....................................................26

IV. CONCLUSIONS................................................................................................................28

REFERENCES...............................................................................................................................30

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I. INTRODUCTION

Countries around the world vary substantially in their policymaking style.1 These differences in

policymaking style relate to some characteristics of the workings of political institutions, and

have a profound impact on the capacity of countries to implement effective public policies.

Previous work has shown that well institutionalized political parties, legislatures with strong

policymaking capabilities, independent judiciaries and well-developed civil service systems

(“the institutionalization of policymaking”, for brevity) are crucial determinants of the capacity

of countries to implement effective public policies. 2

This paper is part of a research agenda that attempts to study the determinants and

consequences of the degree of institutionalization in policymaking. The agenda includes the

development of theoretical models, case studies of the evolution of institutions in some Latin

American countries, and cross-country econometric work. This paper contributes to the first

pillar. The general logic of the agenda consists of analyzing the choice of political strategy that

various socioeconomic and political actors make, and the consequences of such choices for the

evolution of institutions, the quality of policies, and resulting social outcomes.

We develop a series of two-stage models to study such choices and their equilibrium

implications. In the first stage political actors decide whether to invest in formal political

institutions (Congress, parties, the Judiciary, implementation agencies) or to invest in

alternatives that permit to obtain benefits in less institutionalized ways (such as the threat of

violence). In the second stage there is a game in which policies have to be decided under

various different economic and political contexts. Depending on the nature of investments in

the first stage, different outcomes can be enforced in the second stage. The models formalize

in a very stylized manner some of the mechanism that, according to the institutional literature,

lead institutionalized decision-making processes to deliver more efficient outcomes.

Depending on values of parameters (that can be interpreted in terms of economic

structure, formal institutional rules, characteristics of alternative political technologies, etc.)

the models deliver different equilibria characterized by varying degrees of institutionalization.

1 A Google search for a concept such as “Farm Bill” shows a number of individuals wearing

elegant suits bending over law books in some cases such as the U.S., while it shows tractors

blocking roads in other cases such as Argentina. 2 See references below.

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In equilibria characterized by high levels of institutionalization, everybody invests in

institutionalized forms of political participation, intertemporal commitments are well enforced

within political institutions, there is better control of political agents, and better policy

outcomes result. In equilibria characterized by low levels of institutionalization actors invest in

both institutionalized and non-institutionalized political technologies, intertemporal

commitments are enforced imperfectly, politicians extract more rents (there is more

corruption), and worst policy outcomes result. There are strategic complementarities in the

use of alternative political technologies across political equilibria: in some polities we should

observe more corruption, more violence, less institutionalized policymaking, and worst policy

outcomes than in others.

The models allow various comparative statics on the parameters of the economic

problem, of the institutional rules, and of the alternative political technologies available. One

result is that the more complex the economy (the more good economic performance requires

sophisticated institutions to support economic activity), the more likely the equilibrium will

imply full institutionalization. We argue that if one were to embed this finding in a more

dynamic model, this might lead to a pattern of self-reinforcement. More institutionalization

leads to better economic outcomes, over time this enables polities to access more complex

technologies, and these more complex economic technologies lead to further political

institutionalization. On the contrary, low initial levels of institutionalization would leave the

economy stuck with simple technologies, which in equilibrium reinforce the weakness of

institutions.

The rest of this introduction motivates the effects of various political investments on

institutionalization, and the consequences of institutionalized (versus non-institutionalized)

policymaking.

Institutionalization and Political Investments

There are many definitions of institutions. A common one would go as follows. Institutions are

structures and mechanisms of social order and cooperation governing the behavior of a set of

individuals. Institutions are identified with a social purpose and permanence, transcending

individual human lives and intentions, and with the making and enforcing of rules governing

cooperative human behavior. The term institution is commonly applied to customs and

behavior patterns important to a society, as well as to particular formal organizations of

government and public service. (Rhodes, Binder and Rockman, 2006)

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Institutions are supposed to structure human interaction in ways that facilitate the

definition and enforcement of some transactions (Williamson 2000). Institutionalization, in

turn, is a property that some systems of modes of interactions posses, which is associated with

increased formalization and recognition of particular modes of making and enforcing decisions

and transactions.

The notion of institutionalization in the context of political institutions has been

highlighted by important authors in the democratization tradition. Samuel Huntington has

insisted upon the importance of political institutionalization. In his famous article “Political

Development and Political Decay”, Huntington associated political development to political

institutionalization.3 Huntington (1965) proposes a model for evaluating the level of

institutionalization of a political system. Institutionalization, according to Huntington, is one

important measure of the strength of a political organization.

Beyond the broad discussion of institutionalization in Huntington, a few authors have

investigated the institutionalization of specific institutional arenas or subsystems. The single

most studied area in this regard is party system institutionalization, which is considered a

positive trait for a democracy, associated with democratic accountability (Mainwaring and

Scully 1995, Mainwaring 1998, 1999, Jones 2010). Institutionalized party systems help ensure

greater policy consistency because of the role played by parties in political recruitment and the

efforts made by elites to promote and protect the value of the party label (Jones 2010).

Institutionalized political parties are also considered ideal actors to articulate the

intertemporal bargains necessary to induce effective public policies consistently implemented

over time (IADB, 2005). 4

3 Indeed Huntington’s view is consistent with the modeling strategy of Scartascini and

Tommasi (2009) and of this paper, where the alternative to institutionalization can be

interpreted with the use of violence and de facto social power. As Peruzzoti (2004) summarizes

Huntington: “In the absence of mediating institutional mechanisms, social and political forces

confront each other “nakedly”, i.e., their politization is not channeled by institutional

mechanisms but consist of unmediated war of all against all. Violence and de facto social

power fill in the vacuum left by the absence of political institutions.”4The types of concepts traditionally utilized to define and measure party system

institutionalization tend to capture some of the dimensions of institutions and

institutionalization that we emphasize here, such as investments inside those institutions (“do

party organization have structure and resources?”) and beliefs by insiders and other actors

(“do people trust political parties?”) about the relevance of that political organization or

political arena.

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Beyond party system institutionalization, the framework suggested by Huntington was

found useful for understanding the institutionalization of the US House of Representatives by

Polsby (1968). According to Polsby, for a political system to be effective in performing tasks of

authoritative resource allocation, problem solving, conflict settlement, and so on, it must be

institutionalized; organizations must be created and sustained that are specialized to political

activity (Polsby 1968: 144). Polsby develops a number of indicators to assess the

institutionalization of the US House of Representatives, and, on the basis of those indicators,

he concludes that the House has become more institutionalized over time.

Translating many of the elements identified in the literature on party system and

Congressional institutionalization into economic / game theoretic language, we would argue

that institutionalization is the outcome of investments, and that it is associated with particular

sets of beliefs. A number of relevant actors (politicians, interest groups) invest heavily in the

U.S. Congress, and they do so because they believe that is a key arena in U.S. policymaking,

which in turn is confirmed in equilibrium by those investments and the resulting outcomes.

In this paper we focus on the decision of political actors to invest in institutions, and

try to study its determinants and consequences. Making progress on these issues requires

answering the questions of what does it mean to invest in political institutions, and of who

invests in political institutions. Investing in political institutions implies devoting various

resources such as time and money in order to increase the future capacity of achieving some

objectives in the context of those institutions. It includes investing in increasing the capacity to

participate in technical policy discussion. It implies sacrificing something in the short term

(including short term political advantages), in exchange for strengthening the power of some

arenas that could benefit “the investor” in the future. Such investments are undertaken by

politicians and by real socioeconomic actors. Legislators as those described in the literature on

the U.S. Congress by Weingast and Marshall (1988) and by Gilligan and Khrebiel (1987 and

1990) invest in the institutionalization of Congressional committees by acquiring expertise and

by surrendering political power in other arenas. Presidents in Latin American countries invest

in institutions whenever they do not undertake strategies that push to the limit their short

term payoff in order to build good will and strength in institutions such as Congress or the

Judiciary (of course, they disinvest in institutions when they do the opposite).

In the modeling strategy of this paper, it is more natural to think in terms of

investments being undertaken by socioeconomic groups, such as businesses or unions. For

instance, alternative choices of political strategies by business actors are associated with

different effects over the future workings of institutions. Business actors can invest directly in

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strengthening state capacity; they can form encompassing business associations that

participate in institutionalized corporatist arrangements; they can invest in strengthening

political parties that represent their interests, via increasing their electoral chances through

advertising or other resources, or via technical input through associated think tanks; they can

invest in the reelection or technical capacities of some legislators that represent their

interests; they can invest at more or less disaggregated levels to influence sectorial policies;

they can invest in developing the skills or contacts necessary to bribe politicians for favorable

policies; and they might even invest in technologies that allow them to physically or legally

threaten politicians that do not follow their requests (Dalbó et al, 2006). Clearly, different

strategies have different implications for the capabilities of policymaking institutions. Similarly,

unionized workers can invest in having their interests represented by institutionalized parties,

or they can picket in the streets pushing for favorable policies, and so on.5

An investment in political institutions improves the player’s capabilities to acquire

political power and/ or to influence policy through institutionalized channels. Some of these

investments have institutional externalities or strategic complementarities, in the sense that

investments by some actors strengthen institutions for the benefit of all players and,

furthermore, increase the marginal payoff of investment by other actors.6 These features are

captured in a simplified manner in the set up presented in parts II and III below.

The Consequences of Institutionalized Policymaking

Institutionalized policymaking leads to more effective public policies and, through that, to

better welfare outcomes. Previous work has shown that relevant economic and social

outcomes depend on a number of characteristics of the actual implementation of policies,

5 Citizens or social groups could also invest or fail to invest in institutionalization, for instance

by mobilizing in defense of some institutions such as Judicial independence or Central Bank

independence when they are threatened by abusive actions of the Executive, as it is often the

case in Latin America. Clearly such responses suffer from informational and from collective

action problems (Fearon 2009).6 This is analogous to situations in the realm of private contracting. The value of one party’s

signature of a contract is a 100% dependent upon whether the other party is also signing or

not. As explained below, these externalities might relate to issues of collective or community

enforcement, as those analyzed in the literature on institutions as equilibria (Greif 2006,

Chapter 10).

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such as their stability, their capacity to adjust to changing circumstances, their enforcement,

etc. Countries able to generate policies with such attributes reap the benefits of specific policy

initiatives more than others. If the policies adopted do not have such attributes – no matter

how good they look on paper – they are unlikely to achieve good development outcomes. In

turn, those desirable policy characteristics are the outcome of policy making processes

undertaken in the context of strongly institutionalized policy making institutions, including

institutionalized political parties, legislatures with strong policymaking capabilities,

independent judiciaries, and well developed civil services.7

Well institutionalized parties, especially if they have national / programmatic

orientations tend to be consistent and credible long term players. A system with a not-too-

large number of institutionalized parties (or coalitions) is more likely to generate inter-

temporal cooperation, and to lead to the emergence of consensual sustained policy stances on

crucial issues (Políticas de Estado). Legislatures are the ideal arenas for the striking of efficient

policy bargains. Policies tend to be better when legislatures develop policymaking capacities

and constructively engage in national policymaking, rather than when they simply adopt a

subservient role, rubber-stamping the wishes of the executive (or blindly opposing in a non-

constructive manner). A well functioning and independent judiciary can be a facilitator of

exchanges, fostering bargains among political actors by providing enforcement that binds

them to their commitments, and by ensuring that none of the players oversteps its

boundaries. A strong and technically competent civil service can contribute to the quality of

public policies by making policies more stable, and by enhancing the overall quality of

implementation. Several indicators of such institutional capabilities have been developed for a

number of Latin American countries (IDB 2005, Stein and Tommasi 2007) and also for a larger

international sample (Scartascini, Stein and Tommasi 2008 and 2009), and they have been

found to matter for the quality of policy outcomes. Figure 1 summarizes some of those results

by plotting an index of the quality of public policies against an aggregate indicator of

institutional capabilities.

<insert Figure 1>

There are various reasons why more institutionalized collective-decision making and

implementation arenas tend to generate better policies and better outcomes. Investing in

technologies that increase the strength and capabilities in the institutionalized game (such as

hiring PhDs in public policy) or in technologies that increase strength and capabilities in

7 IADB 2005, Stein and Tommasi 2007, Scartascini, Stein and Tommasi 2008 and 2009.

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alternative arenas (such as buying weapons), are likely to have a different impact on the

strength and productivity of formal institutions, as well as on the quality of the output the

polity generates. More institutionalized policymaking arenas provide a better structure for the

exchange of information and for the agreement and enforcement of intertemporal

cooperation. According to Pierson (2004: 17) “political institutions can serve to coordinate the

behavior and expectations of decentralized actors (Carey 2000) and to facilitate bargaining by

creating monitoring bodies, issue linkages, and mechanisms for making credible commitments

(Kehoane 1984, Weingast 2002)”.

We proceed now to present a set of very simplified model that capture in a blunt

manner some of the logic of investments, institutionalization and policy outcomes described

above. The way we model political investments captures, in a stylized two-stage model, the

facts that : (1) past choices constrain current strategies (an actor that has not made any

investments in playing the institutionalized game, will not be very effective in that game); (2)

further investments in political institutions increase each actor’s chances of obtaining

favorable outcomes from institutionalized arenas; and (3) these political investments involve

externalities and strategic complementarities: the more others have invested there, the more

valuable my own political investment.

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II. THE FRAMEWORK

The paper presents a series of models in order to explore the determinants and consequences

of the degree of investment in the institutionalization of policymaking undertaken by

socioeconomic/political actors. For brevity of exposition and analytical simplicity we focus on

the case with two players, who represent economic sectors that constitute themselves as

political actors.

In each of the models there are two stages. This set up captures in a simplified manner

the nature of political investments in institutionalization, allowing exploring its determinants

and consequences. In the first stage players choose political investments. In principle, actors

could do three sorts of things: invest in institutionalized policymaking capabilities, invest in

developing strength in alternative ways of influencing policymaking (such as picketing or

violence), or they could not undertake any of these activities and just “exit”. In the first model,

developed below, the choice is just between investing in institutions or not, so that the

alternative is captured as an opportunity cost. In models 2 and 3, presented later in the paper,

the choice is between investing in institutions and investing in alternative political

technologies. In model 2 these alternatives are symmetric across players, and are best thought

of as road blockades or some form of threatening violent action. In model 3, some players

have access to the previous technology while other players have access to a technology that

gives them privileged corrupt access to the formal policymaking process.

In the second stage, for given amounts of political investments, a game of

policymaking takes place in the context of specific institutional environments and specific

modes of influence from alternative arenas to formal political institutions. Each of the

formulations attempts to capture some of the mechanisms by which institutions affect the

nature of policymaking. Drawing from insights in the literature on institutional economics and

political economy, the models emphasize different microfoundations for the effects of

institutionalization on the quality of policymaking.

The table below summarizes and compares the first and second stage of each of the

models.

Stage 1Political Investment Choice

Stage 2Institutional Issue

Model 1 Invest in institution Opportunity Cost

Enforcement of policy agreement (economic shocks

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and political opportunism)

Model 2 Invest in institution Invest in (symmetric) APT

o road blockade

Political Agency Problem

Model 3 Invest in institution Invest in (asymmetric)

APTo Road blockadeo Bribes

Political Agency Problem

Each of the models attempts to formalize some of the mechanisms by which

institutionalized decision-making delivers more efficient outcomes. Model 1 emphasizes the

ability to enforce intertemporal commitments, while models 2 and 3 emphasize the ability to

monitor State agents in charge of policy definition and implementation.8

In model 1, more institutionalized policymaking allows for a better chance of enforcing

intertemporal agreements leading to public policies that are better able to accommodate

changing technological and economic circumstances. In models 2 and 3, the idea is that in

order to decide and implement effective public policies over time, it is necessary to delegate

policymaking to some agents, and more institutionalized policymaking processes allow for

better control of the agents (through checks and balances and the like).9

With respect to alternative political technologies (APTs) both models 1 and 2 allow the

different players a symmetric access to the same APT. Model 3 allows different actors to have

8 The intuition behind these situations can be conveyed by an example familiar to economists.

Monetary policy is an area where there is substantial agreement that there are some good for

delegating its implementation to an independent agency (the Central Bank). Delegating to an

independent and technically capable agency removes the possibility of political opportunism

from the sitting government from the table, without sacrificing the ability of policymakers to

adjust to economic shocks. There no magic bullet to create the perfectly able, independent

and accountable Central Bank, but it is clear that technical and political resources can be

invested to increase or to decrease such capabilities. In model 1 we focus on the ability to

make policy responsive but not opportunistic. In models 2 and 3 we focus on agency issues.9 On the role of check and balances in increasing accountability, see Persson, Roland and

Tabellini (1997) and O Donnell (1998).

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asymmetric access to different APTs.10 A possible interpretation of these two APTs is that of

the rich (or privileged business groups or unions) having privileged corrupt access to formal

decision making, while the poor (the unemployed, informal workers, etc) having access to

street violence, road blockades, and the like.

In all cases, the solution to the second-stage game can be summarized as a value

function for each of the players, which is a function of the political investments of all players in

the first stage. The “parameters” of each of these value functions summarize relevant

information of the institutional and economic set-up of the second stage model. The first stage

of the game consists of all players simultaneously choosing their political investments,

foreseeing the way the game will transpire in the second stage as a function of those political

investments. We then solve for the Nash Equilibrium to that first-stage game. The nature of

the solution to this game allows to perform comparative static analysis of the effects of various

parameters of the second stage game (institutional rules, economic technologies, power

distributions) on the investment choices of the first stage (and hence on the degree of

institutionalization of policymaking and various substantive outcomes relating to it).

We proceed now to present and solve model 1. Part II presents a synthetic heuristic for

models 2, and 3, since a good part of the logic of the three models is the same.

Model 1: Investing in the ability to enforce policy agreements

There are two players,i=A , B. We present the game by describing first the investment

decision of stage 1 and its implications, and then the policy problem (the economy and the

policy technologies) in stage 2.

Stage one: Investing in institutions

In the first stage, agents choose their strategy of political investments. Each player has one

unit of political “energy” to invest in one of two alternatives: political institutions to which

they devote investment a i, and an alternative to which they devote 1−ai. For brevity of

notation, in this two-player set up, we will denote the institutional investments of players A

and B (a A and aB) as a and b respectively. Also, in this initial set up, the alternative will be just

an opportunity cost captured by the functions C ( a ) and C (b ), with C '>0, C ' '>0, and

C ' (0 )<c. So that A chooses institutional investment a∈ [0,1 ], while B chooses institutional

10 That set-up is a variant of the modeling strategy used in Trucco (2009).

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investment b∈ [0,1 ]. These investments will have an impact on the second stage through

their effect on the probability of three politico-institutional events μE, μA, and μB, to be

explained below. In a nutshell, investing in institutions increases individual chances within

institutionalized policymaking, and it increases the probability of enforcement of policy

agreements.11

Stage two: Policymaking

We present a static version of richer dynamic policymaking environments that have been

analyzed in more detail in other work (see references below). Such simplification is

compensated by enriching those environments by endogeneizing institutional capabilities (in

stage 1). The specification captures in a stark manner a policymaking environment in which

different policy issues are on the table at different points in time, under changing contextual

circumstances, and involving different distributional effects across different actors.

Almost any interesting policy problem has simultaneously efficiency effects and

distributional effects. For example, in moments of macroeconomic distress, everybody has an

interest in some form of fiscal stabilization, but different stabilization packages have different

distributive implications (Alesina and Drazen, 1991).

Additionally, policies are contingent responses to underlying states of the world. They

have to adjust adequately to a number of changing circumstances. Any particular policy has

different efficiency and distributional consequences depending upon a number of

circumstances that vary over time and space. New circumstances in international markets,

policy decisions in other countries, technological changes, diseases, natural disasters, and

social and demographic changes are events that present new demands on public policy. In

every important policy decision that has to be taken at any point in time, the mapping from

policy to the welfare of each relevant actor will depend on that “state of nature”.

The model captures in a simple manner the fact that policy choices have effects on

efficiency and on distribution, and that those effects are conditional on the state of the world.

Any policy in the real world has effects on aggregate efficiency, which we capture by its effects

on the total size of “the pie”, that is, of total output X . Also, any policy has distributive

implications, which we capture by the share of the pie si going to each player. (Remember

11 As mentioned above, one example of institutionalization leading to policymaking contingent on

economic shocks (but hopefully not on political opportunism) consists on creating and strengthening

independent central banks.

On example of such policy institutionalization which is familiar to economists is that of independent

central banks.

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that we are interpreting the players as economic sectors, so that we will use the terms

“player” and “sector” interchangeably).12 The payoff to each of the two players A andB equals

U i=si X , where siis the share of total output received by each sector after policy intervention

(for brevity, then, the vector of shares will be the policy vector), and X is total output. (We

are omitting issues relating to risk aversion, which could be easily incorporated). Total output

is affected by policy, so that it is a function of the policy vector ⟨ s A, , sB ⟩. It also depends on the

realization of an economic shock θ. We adopt a specific functional form for these

dependencies, a specific functional form for X ( sA , sB ,θ ), as follows:13

X=[1+ (1−θ ) γ ] f ( sA )+ [1+θ γ ] f ( sB ), (1)

where

f () can be interpreted as a production function, depending upon the share of the pie

distributed to each player/sector, with f '>0, f ' '<0. In this initial formulation we assume

that sA+sB=1, so that we simplify the notation letting sA=s and sB=1−s,

γ>1 is a productivity parameter, and

θ is an indicator function that takes value 0 when sector A is more productive and value 1

when sector B is more productive. This captures the stochastic and varying nature of the

state of the economy, as well as the fact that the effects of policy on total output and on

the welfare of each of the players depends upon that state. 14

12 We are also assuming that these actors are perfectly represented by their agents within

political institutions. Models 2 and 3 consider political agency problems.

13 Ignoring shocks, the function would be X=f ( sA )+ f ( sB ). This is just one easy-to-manipulate

(symmetric) form of the more general X=X ( sA , sB ).14 Think for instance of some social insurance policy. Everybody is interested (ex ante) in having

an efficient system that provides resources to those affected by negative shocks, but the ex

post implementation involves redistribution from other players towards those affected by the

shocks. The same logic would apply in a system of subsidies to economic activities that, given

some circumstances might generate positive externalities: everybody has some interest in

subsidizing those sectors to some extent, but the interest is greater within the sector than

outside the sector.

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At the beginning of stage 2, the players have the possibility of signing a “contract”, an

agreement over future policies, as a function of the later realization of the state of the world.

As private contracting, political contracting is plagued with enforcement problems. Contracts

are necessarily incomplete, and particular aspects of particular agreements are more or less

likely to be enforced given available institutional technologies. This is easier to see in terms of

private contracting, where features of the broader institutional environment such as the

quality of the judiciary would affect the likelihood of enforcing contracts of varying degrees of

richness and texture (Williamson 1991). Previous investments undertaken by various actors

would, then, endow a given polity with stronger or weaker institutional environments.

The complex issues connected to the enforcement of (the necessarily incomplete)

policy contracts will be captured in a stark manner, similar to the way in which various authors

in the contract literature have modeled related phenomena. In our set up, the greater the

amount of investments in institutionalization, the higher the probability that a complete

contract can be enforced, and the lower the probability that the ex post decision will be

undertaken opportunistically by whoever happens to have more ex post power. This way of

modeling institutional investments as affecting the probability of better enforcement of

contracts is analogous to the way in which Laffont (2005, p. 106) models a regulatory problem,

in which the expenses incurred in setting up an efficient enforcement mechanism affect the

probability that the regulator is able to impose the implementation of the agreed-upon

contract.

Timing:

To summarize and complete the description of the game, we present the timing, which is as

follows:

Players simultaneously choose a and b.

A policy contract or policy agreement sE (θ ) is signed, as function of the later realization of

economic shocks θ. (We specify the bargaining protocol of that moment below).

The state θ realizes. θ has distribution q (θ ) . In the specific example presented in this

paper θ takes value 0 with probability q=12 , and value 1 with probability 1−q=1

2 .15

15 It is easy to see in expression (1) that θ=0 means that it is more efficient to choose a policy

that is more favorable to A, while that θ=1 means that it is more efficient to choose a policy

that is more favorable to B.

15

A politico-institutional random variable μ realizes, determining one of three outcomes:

– with probability pE,μ=μE, and players will be able to enforce the previous policy

agreement 16

– with probability pA, μ=μ A, and A has political power, which means that he gets to

choose policy

– with probability pB, μ=μB, and B has political power and chooses policy,

with pE+ pA+ pB=1. These probabilities will depend on the nature of political investments.

The benefits of investing in institutions comes from increasing your chances of achieving ex

post de jure political power (private benefit), as well as the improvement in the capacity to

enforce efficient policy agreements (public benefit). The latter is reflected in pE (a ,b )

increasing in both arguments, and the former in pA (a ,b ) increasing in a and decreasing in b,

and in pB (a ,b ) increasing in b and decreasing in a.17 Furthermore, pabE =pba

E >0, which captures

the strategic complementarities of investing in institutions we described above.18

Policy is decided. In this simple formulation, policy choice will consist on picking a share s

for A, with the complementary share (1−s) going to sector B.

This policymaking environment is a reduced form version of more complex environments (as

those in Alesina 1988, Dixit et al 2000, Spiller and Tommasi 2003 and 2007, and Scartascini et

al 2010b), with the addition of the endogeneity of institutional capabilities. As in Alesina 1988

and Dixit et al 2000, political power changes over time in a stochastic manner, and those who

16 We will see below that the policy agreement will coincide with the utilitarian first best.17 The probability functions are symmetric, smooth, and have monotonic curvature.18 The complementarity among different players’ institutional investments is not necessarily a

fact of life that is present everywhere, but we believe is a relevant case, and the one we focus

on in this paper. This complementarity is clearly present in various exchange environments,

private and public. We already mentioned the almost trivial example from private contracting

(i.e., contracting under the shadow of some exogenous state enforcement technology) that is

signing a contract: the value of one party’s signature depends 100% on whether the other

party is signing. More relevant in general and in particular for political environments without

external enforcement, the contract enforcement institutions analyzed in the work of Avner

Greif and others (collected for instance in Greif 2006b) are examples in which institutions such

as community enforcement permitted cross-enforcement across transactions in a way that

further investments in institutions by other traders increased the value of each trader’s own

investments.

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have more power at any given point in time can induce policies more favorable to them. Those

policies, in turn might be more or less efficient, in terms of adjusting more or less adequately

to the state of the world θ. Spiller and Tommasi (2003 and 2007) and Scartascini et al (2010b)

show that in a repeated game version of a similar set up, players might be able to implement

more cooperative equilibria in which economic policy adjusts to shocks in an efficient manner

independently of who is in power. The model above constitutes a simplified version of that

scenario, in which the rich dynamics of policymaking cooperation (or lack thereof) in a

stochastic environment is compressed into the expected utilities of a two-stage game under

risk neutrality, and where intertemporal cooperation is perfectly enforced with some

probability, while each of the players has discretionary power ex post with some other

probabilities. The probabilities of occurrence of the different ex post bargaining scenarios

depend upon stage-one investments in political institutions by the different actors.

Solving Model 1

Let X ( s , θ )=[1+(1−θ ) γ ] f ( s )+ [1+θ γ ] f (1−s ). We solve the model by backward induction.

At the moment of policy choice, with θ known, there are three possibilities depending on the

realization of μ. Either A gets to choose, in which case he will maximize sX (s , θ ), or B gets to

choose, in which case he will maximize (1−s ) X ( s , θ ), or the previous policy agreement will be

automatically implemented. The exact policy agreement chosen at the beginning of the

second stage will depend on the bargaining protocol at that moment, which we have left

unspecified. For brevity of exposition, imagine that the bargaining protocol is such that the

outcome is equivalent to what the standard social planner of economic textbooks would

choose, giving equal weights to each of the players in his social welfare function; that is, it will

maximize sX (s , θ )+(1−s ) X (s , θ ) for every possible θ, which is equivalent to maximizing total

output. Let sE (θ ) denote the policy agreement, which turns out, then, to be equal to s¿ (θ ), the

first best; and let sA (θ ) and sB (θ ) denote the ex post choices of A and B respectively.

The policy choice can be expressed generically as choosing s for every θ in order to

maximize

{w ( μ ) s+ [1−w ( μ ) ] (1−s ) } X ( s , θ ),

where w ( μ ) is the ex post political weight of player A, which depends on the realization of μ:

17

w ( μ )={0 when μ=μB

12

when μ=μE

1 when μ=μA

The solution to that maximization leads to the expression

(2w−1 ) X ( s , θ )+[ ws+(1−w ) (1−s ) X s (s ,θ ) ]=0,

where X s ( s , θ )=d X (s ,θ )ds

.

It is easy to see that this leads to

sA (θ )>sE (θ )=s¿ (θ )>sB (θ ),

and that for any μ, s is decreasing in θ. That is, in all politico-institutional cases the allocation

responds to the economic shock θ in the right direction, giving more to A when it is more

efficient to give more to A; but the allocation is biased towards whoever has more political

power ex post, inducing a welfare loss in expected value with respect to the first best

contract.19 One important result, then, is that more institutionalized environments, here

captured by a higher pE, lead to higher welfare. (More on this below)

Coming back to the investment decisions of the first stage, we focusing on player A for

concreteness. A chooses a to maximize a value function that summarizes the play of the game

in the second stage, taking B’s choice of b as given. This value function can be written as:20

V A (a ,b )=Eθ[∑μpμ (a , b ) sμ (θ ) X ( sμ (θ ) ,θ )]−C (a ).

This expression can be rewritten as

V A (a , b )=pE ( a , b ) yE+ pA ( a ,b ) y A+pB (a ,b ) yB−C (a ), (2)

where y μis the expected payoff of player A when the politico-institutional state is μ, so that,

for instance

y E=q s¿ (0 ) X (s¿ (0 ) ,0 )+(1−q ) s¿ (1 ) X (s¿ (1 ) ,1 ).

A similar expression is maximized by B:

19 This loss of expected welfare is a one-period reduced form equivalent for the loss of welfare

that would occur in a richer intertermporal model (such as that in Spiller and Tommasi 2007,

chapter 2).20 In a slight abuse of notation we use pμ to generically denote pE, pA, and pB; sμ to denote

generically sE, sA, and sB; and so forth.

18

V B ( a ,b )=pE (a , b ) zE+ pA (a ,b ) z A+ pB (a , b ) zB−C (b ). (3)

Letting the derivatives of (2) and (3) with respect to a and b respectively be V aA and V b

B, we

can define two pseudo-reaction functions a (b ) and b (a ) as the respective solutions to

V aA ( a ( b ) ,b )=0 (4)

and

V bB ( a , b (a ) )=0. (5)

We call these “pseudo-reaction functions” because the actual choices of a and b are

constrained to be in [0,1] and in some cases the optimal choice will be a corner, so that the

first order conditions will not be satisfied with equality. Equations (4) and (5), together with

the constraints a∈ [0,1 ] and b∈ [0,1 ] define a system which summarizes the possible

equilibria of the investment game. One important thing to notice is that, given all the

symmetry assumptions embedded in this version of the model, these functions are symmetric,

so that a (ξ )=b (ξ ), for all ξ∈ [0,1 ].It is convenient to describe the equilibria to this game by visual recourse to a unit

square in the space of a and b. The nature of the possible equilibria con be ascertained by

paying special attention to the corners a (0 )and a (1 ), which by symmetry are equal to b (0 ) and

b (1 ). It is easy to verify that natural conditions on the payoff functions (in particular on the

pμ(a ,b) and C (a) functions) imply that a (0 )>0 and b (0 )>0.21 This means that the y-

intercept of the reaction functions is positive: if the other player is not investing at all in

institutions, it pays for me to invest some positive+ amount. It is also easy to verify that the

possible equilibria can, then, be ascertained in the unit square diagram, by focusing on the

other corners, a (1 ) and b (1 ), and on the curvature of the reaction functions. Excluding the

quite unlikely possibility of multiple changes of second derivative in the pseudo-reaction

functions, the results can be summarized in the following proposition:

Proposition 1:

Under the assumptions specified above:

1. If a (1 )<1, then there is a unique (stable) equilibrium with a=b∈ (0,1 ).

2. If a (1 ) ≥1 and a (b) is not too convex, then there is a unique (stable) equilibrium

with a=b=1.

21 The condition is paE (0,0 ) y¿+ pa

A (0,0 ) y A+ paB (0,0 ) y B−C ' (a )>0.

19

3. If a (1 ) ≥1 and a (b) is convex enough then there are two stable equilibria:

an equilibrium with a=b=1

an equilibrium with a=b∈ (0,1 )

(and an unstable equilibrium in between) .

The intuition of the proof, available upon request, can be glimpsed by looking at Figure 2,

which depicts these situations graphically.

<insert Figure 2 here>

Following Scartascini and Tommasi (2009), we refer to the equilibrium in which both

players invest fully in the formal institution, as a High Institutionalization Equilibrium (HIE), and

at the cases in which equilibrium investments are less than one as Low Institutionalization

Equilibria (LIE). The model, then, generates situations in which there is unique equilibrium with

less than full institutionalization, situations in which there is a unique equilibrium with high

levels of institutionalization, and there are also situations in which there is multiplicity of

equilibria, with the different equilibria characterized by different levels of institutionalization.

In the HIE, the institutional technology is exploited to its fullest extent, and the

probability of enforcing first best policy choices is maximized. On the contrary, in the LIE, the

ex post opportunism of exploiting temporary political power is more frequent, and for that

reason expected welfare is lower. Interpreted in a more intertemporal context (as the one

developed in Spiller and Tommasi, 2007 and Scartascini et al 2010), such an environment

would generate more policy volatility, with policy responding too much to temporary political

power, and not adjusting so well to economic shocks.

One interesting feature of the model is the possibility of multiple equilibria. Even

though here obtained in a simple static context, multiplicity of equilibria is an inherent feature

of intertemporal institutional models, and it is the theoretical foundation of the notion of

institutions as equilibria (Greif 2006, Calvert 1995 and 1995b, Aoki 2001), a notion that fits

very well with our emphasis on institutions as the outcome of equilibrium investment choices,

which in turn depend on the beliefs about the actions and beliefs of others. This result enables

us to think about cases of countries which are not so different structurally, yet they present

highly dissimilar patterns of institutionalization and of policymaking over time. On the basis of

this (possible) multiplicity result is that we want to develop the empirical exploration of the

dynamics of institutionalization of political institutions across Latin American countries. (In

ongoing work we are attempting to characterize comparatively the degree of

institutionalization of Congress in Chile and Argentina, and we are trying to disentangle

20

possible structural determinants from path dependent and self-reinforcing temporal

dynamics).

Comparative statics:

From this characterization of equilibria to the model under different parameter (and functional

form) configurations, it is easy to generate various comparative statics predictions. For

instance, one can explore how parameters of the second stage model, by affecting the

continuation payoffs for the players at the first stage, influence their investment choices and

hence the degree of institutionalization in equilibrium. The logic of the comparative statics can

be presented by reference to figure 2.22 Upward shifts in the reaction functions will lead to

increases in the level of institutionalization within case 1, or eventually to shifts from case 1 to

case 2, that is towards the corner of full institutionalization. In the context of case 3, such shifts

might make a country jump from a LIE to a HIE. Of course the results are exactly the opposite

in the case of downward shifts in the reaction functions. In order to see how the reaction

functions shift in response to changes in parameters of the second stage, it is intuitive to

notice by looking at (2) and (4) or to (3) and (5), that the effect will depend upon the relative

impact of changes in the parameter on each of the y μ (or zμ).

As an example that we believe is of substantive interest, take the parameter γ in the

production function. It can be shown that da(b)

dγ>0, so that the equilibrium values of a and b

are increasing in γ.23 This means that a larger value of γ leads to more institutionalization in

equilibrium. The parameter γ is a measure of how much aggregate output depends on how

well adapted the chosen policies is to the actual values taken by economic and technological

shocks. In the spirit of the new institutional economics, it can be interpreted as the complexity

of the transactions in this economy, a feature that is associated with more advanced economic

environments or sophisticated technologies, which tend to be more demanding in terms of the

22 As stated, given our assumptions (in particular pbaE >0), both reaction functions are increasing.

23 Increasing γ increases y E and y A, and it decreases yB. Given that paE>0, pa

A>0, and paB<0,

this means that the pseudo-reaction function a (b ) shifts upwards, and the same happens to

b (a ). Since both reaction functions are increasing, these shifts increase the level of

institutionalization within LIE in cases 1 and 3, and it also increases the chances of moving from

case 3 to case 2, from a situation where both a (stable) LIE and a FIE exist, to a situation of only

FIE.

21

quality of supporting institutions (Klein, Crawford and Alchian 1978, Williamson 1985) and

public policies.24

This result allows us to provide an example of how this simple static model could be a

useful building block for a richer exploration of institutional and development dynamics. If one

were to embed this static model in a more dynamic environment a la Greif and Laitin (2004)

this would lead to a pattern of self-reinforcing multiplicity of equilibria. Greif and Laitin stress

“feedback effects” that either expand or reduce the set of situations in which an institution is

self-enforcing. They characterize different institutional equilibria as being self-reinforcing when

they induce dynamics that increase the set of parameters for which the equilibrium is self-

enforcing, and self-undermining when they induce dynamics that reduce the set of parameters

for which the equilibrium is self-enforcing. In our example here, if interpreted in its possible

dynamic implications, more institutionalization would lead to better economic outcomes,

which in turn might permit accessing more complex economic technologies, which in turn

would make a high-institutionalization equilibrium more likely, and hence self-reinforcing. On

the contrary, low initial levels of institutionalization would leave the economy stuck with

simpler technologies, which in equilibrium would reinforce the weakness of institutions.

24 “As the economy becomes more diverse and sophisticated, it will require more complex

transactions” (Kydd et al 2003, p. 265, in summarizing North’s view of economic development).

22

III. EXTENSIONS (Investing to control political agents)

Institutions and Alternative Political Technologies

Socioeconomic actors can attempt to influence collective decision-making through the

institutionalized channels explored in the previous part, but they also have other ways of

affecting political and policy outcomes. At the time of this writing, the leader of the main peak

workers’ union in Argentina, Hugo Moyano, has recently threatened to “take the boys to the

streets” if his favorite party does not win the next presidential election. This strategy is an

example of the use of what Scartascini and Tommasi (2009) have dubbed “alternative political

technologies”. More specifically, it is a perfect example of the type of nonelectoral action that

attempts to influence electoral outcomes, studied in the pioneer work of Ellman and

Wanchtekon (2000); in their words, “a losing party may organize a coup; voters may riot;

unions may go on strike; investors may take their capital abroad; terrorists and foreign powers

may threaten disruption and loss of life; foreign powers may withdraw aid or even impose a

trade embargo” (Ellman and Wanchtekon 2000: 499).

More generally, alternative political technologies are technologies that allow actors to

influence public choices by channels different than formal institutions. These channels might

include the threat of force, or the threat of economic damage as in the examples above. It

might also include tinkering with the operation of formal institutions by non-institutional

means, such as bribing public officials. In the language of Acemoglu and Robinson (2006),

formal political institutions allocate de jure political power, while the access to alternative

political technologies characterizes de facto political power. Different socioeconomic actors

might be endowed with differential access to various alternative political technologies. As it is

the case with de jure political power, actors can also spend resources to invest in increasing

their de facto political power. Scartascini and Tommasi (2009) present a more detailed

description of alternative political technologies and of possible ways of investing in them.

In order to incorporate alternative political technologies in a model of policymaking

one needs to specify considerations about mappings from alternative actions to utilities, about

collective action, commitment technologies, allocation protocols in informal arenas, as well as

about the modes of interaction between the formal and informal political arenas. Modifying

any assumption made at this level constitutes some of the comparative statics in this agenda.

For brevity and concreteness, in this paper we use the reduced form of a game which is

23

analyzed in more detail in Scartascini and Tommasi (2009). In model 2, this alternative political

technology is better thought of as a road blockade (“going to the street”), or some other form

in which the threat of violence permits to force policy outcomes more favorable to the actors

making those threats.

Model 2: Investing in institutions or in an alternative political

technology

In this and the next model we use a different specification for the mechanisms by which

institutionalization improves outcomes. In model 1 institutionalization facilitated the

implementation of agreements. In models 2 and 3 institutionalization facilitates the

accountability of political agents. As previously, the intuition for this can be explained with the

example of an agency in charge of policy implementation, such as an independent central

bank. The logic behind model 1 was that given the need of policies to adjust adequately to

economic circumstances and in order to prevent opportunistic use of policy (given the vagaries

of political fortunes over time), it was desirable to have “institutions” that permitted policy

adaptability while restricting political opportunism. In the formal model 1, it was assumed that

more institutionalization increased the chances of enforcement of a complete policy contract.

As widely understood in institutional economics, the possibility of writing complete contracts is

quite unlikely, both in the economic and in the political domain. A possible way of achieving

policies which are responsive to changing economic circumstances without leaving excessive

ex post discretion to the winning coalition of the day is to delegate policy implementation to

independent agencies endowed with technical capabilities (Epstein and O’Halloran 1999,

Huber and Shipan 2002, Acemoglu 2003, Spiller and Tommasi 2003 and 2007). But delegation,

as any agency situation, has its difficulties and its own transaction costs. It is natural to assume

that these agency problems could be better controlled if there are strong complementary

overseeing institutions, such as a Congress with strong policymaking capabilities, or a strong,

capable, and independent judiciary. Even the own technical capabilities of agencies, which

clearly have an impact on the quality of outcomes, are the outcome of institutional

investments. (Ting, 2009)

We present model 2 in a schematic manner. In the second (policymaking) stage an

appointed agent implements policy, which consists of choosing the share going to sector A,

the share going to sector B, and the share appropriated by the governmental agent himself

24

(agency rents), with the constraint that sA+sB+sG=1. The objective function of the

governmental agent is given by βg ( sG ) I +[ λ sA+ (1−λ ) sB ] [ f (s A )+ f ( sB ) ], where the first term

captures the agency problem and the second term is the weighted welfare of the two social

groups, with output X=f ( sA )+ f ( sB ). A and B have a decision whether to deploy the

capabilities they derive from an alternative political technology explained below.

In similar fashion to that of model 1, the stochastic connection between investments in

institutionalization and outcomes in the policymaking game will operate through a probability

of solving the agency problem, given by p (a , b ), increasing in both its arguments.

Operationally, we let the indicator function I taking value of 0 with probability p (a ,b ), and

the value of 1 with probability [1−p (a ,b ) ]. This means that the solution to the governmental

problem is constrained to maximize some weighted function of citizens’ welfare when I=0,

while agency rents will occur in equilibrium when I=1.25 This simplified mechanism is a

common assumption in models of stochastic monitoring, since the pioneer work of Becker

(1968).26

In Stage One both A and B have to decide, given one unit of political capacity to

invest, how much to invest in the institutionalized mechanism, a and b respectively, and how

much to invest in an alternative political technology to which they devote (1−a ) and (1−b )

respectively. One natural interpretation of this APT is the threat of violence or of imposition of

economic costs through pickets, road blockades and the like. Having invested in such

capabilities in the past, actors are able, under some conditions, to exercise threats in order to

obtain larger pieces of the pie (policies more favorable to them). In order to simplify this brief

exposition we postulate a very simple APT in which an actor who has invested (1−a ) in such

technology can obtain an extra piece from total output of size k (1−a ) by extra-constitutional

means, with k '>0 and k ' '<0. This is a reduced form for a more elaborated interaction within

25 The realization of I takes place before the governmental agent takes his action.26 The investments in institutions geared towards reducing the possibility of appropriation of

agency rents include actions that increase transparency (budgeting and accounting systems,

the systematic application of economic and decision tools, independent financial audits,

monitoring and oversight, extra policing, etc.) increasing the probability that corrupt actions

will be detected; and actions that improve accountability (investing in judicial reforms,

streamlining and enforcing laws, rules and regulations, etc.) increasing the probability an

individual will be convicted if detected, and influences the assessment of penalties.

25

alternative political arenas and between institutions and informal arenas (see Scartascini and

Tommasi 2009 for further discussion and references).27

Solving the model by backward induction, and focusing on the case of λ=12 for

brevity, it is easy to see that in case of I=0, the solution leads to sAH=sB

H=12 , while in the case

of I=1, sAL=sB

L< 12 , and sG

L>0; and that X H ≡ X ( I=0 )>X ( I=1 ) ≡ X L. Coming to the

investment decision of the first stage, player A maximizes

p (a , b ) s AH X H+ [1−p (a , b ) ] s A

L X L+k (1−a )−k (1−b )

by choosing a taking b as given. The solution to this and the analogous problem for B gives the

configuration for the Nash Equilibrium to the investment game, which has the same logic and

the same types of equilibria as model 1. Comparative static results from parameters of the

second stage game (including the alternative political technology) or from the probability of

enforcement function can be obtained using the same logic explained above for model 1.

For brevity we do not present here such results and their intuition, and we move to

sketching model 3, which takes a very similar structure than the one of model 2 into a case in

which there are different alternative political technologies available to different actors, to

explore whether such technologies will tend to be used separately or jointly in political

equilibrium.

Model 3: Institutions, corruption, and the use of violence

The scenario of model 3 is very similar to that of model 2, but with the difference that it

assumes that different socioeconomic actors have access to different technologies.28 Actor B

still has access to the same technology of “road blockades” of model 2, but now A has access

to a technology that could be interpreted as the capacity to bribe government agents in order

to tilt the public decision-making process in his favor. The amount obtained through protests,

k (1−b ), now subtracts from the piece of the pie going to player A and adds to the piece of B. 27 Scartascini and Tommasi (2009) explain why, at some level, the choices of investment

strategies by political actors imply trade-offs (you cannot get more of everything). Also, this

simple formulation leads to the implementation of extra-constitutional demands by both

players to the maximum of their APT capabilities.28 This section draws from insights in Trucco (2009).

26

The investment in bribing the government has the effect of increasing λ, the weight of A in

the objective function of the government agent. The properties of the λ (1−a ) function are as

follows: ∈[ 12

,1] , λ (0 )=12 , λ '>0, and λ ' '<0.

In the last stage, given the realization of I , the government agent maximizes the same

objective function as in model 2, now with λ determined by the investment in bribing capacity

λ (1−a ). This leads to the determination of sAH ( λ ), sB

H ( λ ), sAL ( λ ), and sB

L ( λ ) as in the previous

section. The choice of b by B is similar to the one of the previous model also.

Now the choice of a takes into account the impact of the investment in bribes on the

equilibrium weight that the government agent gives to the welfare of A. Investing more in this

bribing capacity implies disinvesting in the institutional capacity to control corruption by the

agent.

The solution to the investment choices of Aand B again delivers pseudo reaction functions

with the same general characteristics as those analyzed for model 1, including their being

increasing, which is a bit less obvious in this case. Hence, the possible types of equilibria are

the same as those already analyzed, opening up the possibility of similar comparative statics

exercises on the various parameters of the model. One result that we want to highlight is the

fact that in the Low Institutionalization Equilibrium there are both more bribes and more

street protests than in the High Institutionalization equilibrium. Also, in that equilibrium

agency rents are higher and output is lower. If we interpret those actors with better access to

bribing as the rich, and players with cheaper access to the streets as the poor, we can see

“bribes by the rich” and “protests by the poor” as countervailing forces that tend to happen

together in polities with weaker political institutions.29

29 Scartascini and Tommasi 2009 shows some correlations between measures of corruption and

of social unrest across countries, consistently with the equilibrium correlations predicted by

model 3. Similarly, Machado et al (2010) find similar correlations with individual level data

within 17 Latin American countries: a higher perception of corruption increases the likelihood

of individual protest.

27

IV. CONCLUSIONS

This paper has presented a simple framework to study how actors choose whether to invest in

political institutions. These choices in turn affect the degree of institutionalization of

policymaking, the extent to which different alternative political technologies (APTs) are

utilized, and the efficiency properties of the resulting public policies and societal outcomes.

The results from the three models together can be summarized as follows. Depending

on values of parameters (that can be interpreted in terms of economic structure, formal

institutional rules, characteristics of APTs, etc.) the model delivers either one High

Institutionalization Equilibrium (HIE), one Low Institutionalization Equilibrium (LIE), or two

(stable) equilibria, one HIE and one LIE. In High Institutionalization Equilibria everybody invests

in institutionalized forms of political participation, intertemporal commitments are well

enforced within political institutions, there is better control of political agents, and better

policy outcomes result. In Low Institutionalization Equilibria actors invest in both

institutionalized and non-institutionalized political technologies, intertemporal commitments

are enforced imperfectly, politicians extract more rents (there is more corruption), and worst

policy outcomes result. There are strategic complementarities in the use of APTs across

political equilibria: in some polities we should observe more corruption, more violence, less

institutionalized policymaking, and worst policy outcomes than in others.

The simplicity of the models presented suggests various relevant extensions, which

would permit to explore the effects of various economic and political configurations on

political institutionalization and on its consequences.

One line of extensions could introduce asymmetries in these fairly symmetric models.

For instance, focusing on model 1, one can introduce asymmetries in the distribution of

efficiency shocks, making some political actors more likely beneficiaries of the more efficient

policies, which would introduce natural tensions between efficiency and political power.

Similarly, the distribution of political power within formal institutions could be asymmetric,

and these asymmetries might increase the use of alternative political technologies by the less

favored actors, thereby reducing institutionalization, and perhaps leading to the domination of

state institutions by some actors, and the use of outside alternatives by others.

Another natural extension would be to increase the number of players. Having more

than two players would be a natural way of introducing richer decision-making processes

28

within institutions. That would enable us to make conjectures about the way in which specific

political (electoral, constitutional) rules affect political institutionalization in equilibrium, as

well as the extent to which different alternative political technologies are utilized, and the

efficiency properties of the resulting public policies and societal outcomes. Of course the

connection between political institutions and policy outcomes is the object of a hefty literature

on political economy; the novelty of our approach is to suggest studying those issues taking

political institutionalization as endogenous to the political investments of socioeconomic

actors. It is possible that the implications of such exercises might have implications different

from those coming from models that implicitly take a high degree of institutionalization as

given. (Caruso et al 2010 present empirical evidence suggesting that standard predictions of

the effects of political institutions on policies work well only for the subset of countries with

high levels of political institutionalization).

There are also dynamic considerations which are touched upon lightly in the two-stage

models of this paper, but that are of fundamental importance for a theory of

institutionalization. Exploring the dynamic effects of some of these institutional choices on

policies and on the economy could provide feedback effects on the degree of

institutionalization in equilibrium, leading to the possibility of self-reinforcement (or lack

thereof) of patterns of institutionalization and of economic development.

29

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-1.5 -1 -0.5 0 0.5 1 1.5-1.5

-1

-0.5

0

0.5

1

1.5Figure 1. Quality of Public Policies and Institutional Capabilities

Institutional Capabilities

Polic

y In

dex

Note: Controlling for Ln(GDPpc) and regional dummies

Source: Author’s calculation using data from Berkman et al (2008)

▲ Latin American Countries ■ All Others

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Figure 2: Nash Equilibria to Institutionalization Game(Note: symmetric case a(1)=b(1))Case 1: b(1)<1

Case 2: b(1)≥1 & b(a) not too convex

Case 3: b(1)≥1 &b(a) quite convex

35