Political Change, Stability and Democracy

Political Change, Stability and Democracy Daron Acemoglu (MIT) MIT February, 13, 2013. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 1 / 50

Motivation Political Change, Stability and Democracy Introduction Almost all social, political, economic institutions have evolved over decades and hundreds of years. e.g., present British democracy with universal suffrage evolved from Magna Carta (1215), Bill of Rights (1689), and Reform Act (1832) The process is slow, and political decisions are made by political actors along the way. these may include kings, landlords, peasants... Institutional arrangements are often very persistent, but such persistence also coexists with change Mexican institutions are still shaped by its colonial history, but Mexico gained its independence almost 200 years ago and many of the economic institutions of colonial era have disappeared. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 2 / 50

Political Change, Stability and Democracy Introduction Motivation (continued) Social conflict often key in institutional change: E.g., the British case, leading up to the First Reform Act: Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 3 / 50

Political Change, Stability and Democracy Introduction Key Ingredients of a Framework 1 A game theoretic environment capturing social conflict. 2 Many agents. 3 Limited discounting (or foresight): not too myopic, but also not extremely forward-looking agents. 4 Stochastic events: inability to predict the future perfectly results is needed to model realistic evolutionary paths. 5 State variables creating potential persistence (both because of equilibrium and because of costs of change), but also allow for changes in political equilibria along transition path or in response to shocks. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 4 / 50

Political Change, Stability and Democracy Introduction Example I Monarch may wish to grant constitution and some limited rights to a small segment of society, but is opposed to full-scale democratization. Constitution may be desirable because it encourages investment or or may simply be a necessary evil from the viewpoint of the monarch wishing to stave off other actions. But emerging middle class may demand (and stochastically succeeded in obtaining) further democratization. This may even lead to instability or revolutions empowering radical groups. Would the monarch wish to grant such a constitution? This will depend on: Whether further democratization will occur (which in turn depends on whether one more round of democratization will ultimately dislocate the middle class from power also) Whether there is a natural coalition between other groups in society How soon further democratization might occur Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 5 / 50

Example I Political Change, Stability and Democracy Introduction autocracy limited franchise full democracy Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 6 / 50

Political Change, Stability and Democracy Introduction Example I (the simple case) Three states: absolutism a, constitutional monarchy c, full democracy d Two agents: elite E, middle class M w E (d) < w E (a) < w E (c) w M (a) < w M (c) < w M (d) E rules in a, M rules in c and d. Myopic elite: starting from a, move to c Farsighted elite (high discount factor): stay in a as moving to c will lead to M moving to d Also richer insights when there are stochastic elements and intermediate discount factors: e.g., fear of shift of power to radicals may limit reform, but also its insulating effects. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 7 / 50

Political Change, Stability and Democracy Introduction Example II What determines tolerance/intolerance towards different groups? Example: secular vs. religious groups. Different countries moving in different directions (e.g., Iran vs. Turkey vs. France) what drives such change? preferences? future changes of preferences? fear of changes in future states? Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 8 / 50

Political Change, Stability and Democracy Introduction Example III Does greater social mobility strengthen democracy? De Tocqueville on America: Nor can men living in this state of society derive their belief from the opinions of the class to which they belong, for, so to speak, there are no longer any classes, or those which still exist are composed of such mobile elements, that their body can never exercise a real control over its members. We would need a model in which individuals anticipates that their position in society my change, i.e., reshuffl ing of individuals. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 9 / 50

Game-theoretic models of regime dynamics: Acemoglu and Robinson Why Did the West Extend the Franchise? QJE 2000, Acemoglu and Robinson A Theory of Political Transitions AER 2001, Acemoglu and Robinson Economic Origins of Dictatorship and Democracy, Cambridge University Press 2006: focus on models with two groups and limited links between periods. No change/persistence. Issues of path dependence and institutions and political equilibria: Acemoglu and Robinson Why Nations Fail: The Origins of Power, Prosperity and Poverty, Crown 2012: no formal models. Modeling coexistence of change and persistence: Acemoglu and Robinson Persistence of Institutions, Elites and Power AER 2008: two groups and limited links between periods. Towards a more general framework: Acemoglu, Egorov and Sonin Dynamics and Stability of Constitutions, Coalitions and Clubs AER 2012: focus on non-stochastic environments and high discount factors. Limited dynamics. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 10 / 50 Past Work Political Change, Stability and Democracy Introduction

Political Change, Stability and Democracy Introduction Ongoing Work The words a general but tractable framework of social (political, economic) evolution. Some simplifying, but not too restrictive assumptions, so ingredients 1 5 can be included. In particular single crossing type assumption; states are ordered from 1 to m, and players ordered in such a way as to satisfy single crossing (increasing differences). Build a dynamic non-cooperative game, with fully rational agents making strategic decisions. Study the impact of discount factor and of stochastic events on the decisions made and on social / political transitions Provide general characterization results and comparative statics. Also a variety of rich applications with tight results. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 11 / 50

Political Change, Stability and Democracy Introduction Outline Model Equilibrium Special case: non-stochastic environment with high discount factor (Acemoglu, Egorov and Sonin AER 2011) General non-stochastic characterization General stochastic characterization Comparative statics Applications Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 12 / 50

Model Model Model: Basics Finite set of individuals N = {1, 2,..., n} Finite set of states S = {1, 2,..., m} Discrete time t 1 Individuals decide on possible transition Key assumption: individuals and states are ordered e.g., from less to more democratic, or from less tolerance to secular values towards less tolerance to religiosity, etc. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 13 / 50

Model Model States and utilities More formally, society starts period in s t 1 and decides on (feasible) s t Let us start with a non-stochastic case first. Individual i in period t gets instantaneous utility w i (s t ) Strict increasing differences: For any agents i, j N such that i > j, w i (s) w j (s) is increasing in s This could be weakened to weak increasing differences for some results. But imposed for simplicity throughout this presentation. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 14 / 50

Transitions Model Model Special case: only one step S1 S2 Sm 1 Sm General case: all transitions are allowed but potentially with transition costs: S1 S2 Sm 1 Sm Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 15 / 50

Model Stochastic shocks: example Model Cost of transitioning to state s m becomes less prohibitive: S1 S2 Sm 1 Sm Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 16 / 50

Model Model Transition costs General transition costs c i (x, y) 0 cost of transitioning from state x to state y for player i These could all be zero Or such that only one step transitions are possible Generally only weak restrictions on transition costs Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 17 / 50

Model Model Transition costs: assumptions Assumptions on c i (x, y) 0 Reverse triangle inequality: Higher marginal cost in longer transitions: These assumptions to ensure single crossing of value functions. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 18 / 50

Winning Coalitions Model Model A transition occurs from state s to feasible state s if suffi ciently many players agree on that set of winning coalitions W s 2 S defined for each s Three assumptions need to hold: if X Y N and X W s, then Y W s if X W s, then N \ X / W s N W s Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 19 / 50

Quasi-median voter Model Model Player i N is a quasi-median voter in state s if for any winning coalition X W s, min X i max X a player that belongs to any connected winning coalition generalization of standard median voter set of quasi-median voters in state s denoted by M s Monotonic Quasi-Median Voter property: Sequences {min M s } s S and {max M s } s S are nondecreasing Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 20 / 50

Illustration Model Model Quasi-median voters: simple majority 5/6 supermajority Monotonic Quasi-Median Voter property: 1 2 3 4 Robert s model; ok also ok not ok Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 21 / 50

Stochastic environments Model Model We introduce stochastic elements as follows. An environment is E = ({W s } s S, {w i (s)} s S,i N, { ( c i s, s )} ) s,s S,i N, β. Set of environments E. Finite set of environments, and finite number of shocks captured by environment transition probabilities q ( E, E ). Non-stochastic model special case in which E = 1. When stochastic elements need to be emphasized, we write w E,i (s) to denote payoffs in environment E, etc. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 22 / 50

Dynamic game Model Model 1 Period t begins with state s t 1 and environment E t 1 inherited from the previous period (where s 0 is exogenously given). 2 Shocks are realized. 3 Players become agenda-setters, one at a time, according to the protocol π s t 1. Agenda-setter i proposes an alternative state a t,i 4 Players vote sequentially over the proposal a t,i. If the set of players that support the transition is a winning coalition, then s t = a t,i. Otherwise, the next person makes the proposal, and if the last agent in the protocol has already done so, then s t = a t,i. 5 Each player i gets instantaneous utility w Et,i (s t ) c Et,i (s t 1, s t ). Equilibrium concept: Markov Perfect equilibrium. But for most of the analysis, we will focus on simpler Markov voting equilibrium. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 23 / 50

Transition mappings Equilibria Equilibria Think of any MPE in pure strategies as represented by a set of transition mappings {φ E } such that if s t 1 = s, and E t = E, then s t = φ E (s) along the equilibrium path we write φ : S S. Transition mapping φ = {φ E : S S} is monotone if for any s 1, s 2 S with s 1 s 2, φ E (s 1 ) φ E (s 2 ). natural, given monotonic median voter property Key steps in analysis fix E characterize φ E and expected payoffs when there is no stochasticity then backward induction and dynamic programming. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 24 / 50

Value functions Equilibria Equilibria More explicitly for given fixed state E (i.e., non-stochastic case), continuation value not including transition costs is V φ i (s) = w i (s) + Recursively k=1 V φ i (s) = w i (s) + β [ ) ( )] β k w i (φ k (s) c i φ k 1 (s), φ k (s). [ ] V φ i (φ(s)) c i (s, φ (s)), or V φ i (s) = w i (s) βc i (s, φ (s)) + βv φ i (φ(s)) Also define continuation value inclusive of transition costs: V φ i (s x) = V φ i (s) c i (x, s) Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 25 / 50

Equilibria Value functions (continued) Equilibria In the stochastic case: V φ E,i (s) = w E,i (s) + β E q ( E, E ) [ ] V φ E,i (φ E (s)) c E,i (s, φ E (s)) E And also: V φ E,i (s x) = V φ E,i (s)) c E,i (x, s). Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 26 / 50

Equilibria Markov voting equilibrium Markov voting equilibrium φ = {φ E : S S} is a Markov Voting Equilibrium if for any x, y S, {i N : V φ E,i (y x) > V φ E,i (φ E (x) x) } {i N : V φ E,i (φ E (x) x) V φ E,i (x) } / W E,x W E,x The first is ensures that there isn t another state transition to which would gather suffi cient support. Analogy to core. The second one ensures that there is a winning coalition supporting the transition. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 27 / 50

Equilibria Markov voting equilibrium General result Theorem (existence) There exists a Markov voting equilibrium with monotone transition mapping φ. Theorem (uniqueness) Generically there exists no other Markov voting equilibrium with monotone transition mapping if either every set of quasi-median voters is a singleton or preferences are single-peaked (plus additional conditions on transition costs; e.g., only one step transitions). Thus monotone transition mappings arise naturally. though equilibria without such monotonicity may exist. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 28 / 50

Equilibria General characterization Limiting states and effi ciency Theorem (limit behavior) In any Markov voting equilibrium, there is convergence to a limiting state with probability 1. The limiting state depends on the timing of shocks. Theorem (effi ciency) If each β E is suffi ciently small, then the limiting state is Pareto effi cient. Otherwise the limiting state may be Pareto ineffi cient. Example of Pareto ineffi ciency: elite E, middle class M E rules in a, M rules in c and d. w E (d) < w E (a) < w E (c) w M (a) < w M (c) < w M (d) Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 29 / 50

Equilibria General characterization Comparative statics Theorem ( monotone comparative statics) Suppose that environments E 1 and E 2 coincide on S = [1, s] S and β E 1 = β E 2, φ 1 and φ 2 are MVE in these environments. Suppose x S is such that φ 1 (x) = x. Then φ 2 (x) x. Implication, suppose that φ 1 (x) = x is reached before there is a switch to E 2. Then for all subsequent t, s t x. Intuition: if some part of the state space is unaffected by shocks, it is either reached without shocks or not reached at all. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 30 / 50

Equilibria General characterization MPE vs. Markov voting equilibria Theorem (MPE MVE) For any MVE φ (monotone or not) there exists a set of protocols such that there exists a Markov Perfect equilibrium of the game above which implements φ. Conversely, if for some set of protocols and some MPE σ, the corresponding transition mapping φ = {φ E } E E is monotone, then it is MVE. In addition, if the set of quasi-median voters in two different states have either none or one individual in common, and only one-step transitions are possible, every MPE corresponds to a monotone MVE (under any protocol). For each Markov voting equilibrium, there exists a protocol π such that the resulting (pure-strategy) MPE induces transitions that coincide with the Markov voting equilibrium. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 31 / 50

Equilibria Applications Simple example Suppose three groups: elite, middle class and workers. The elite rule under absolutist monarchy, a. Suppose that with limited franchise, c, the middle class rules with probability p and workers rule with probability 1 p. Workers rule in full democracy, d. The middle-class prefer limited franchise, workers prefer full democracy. Payoffs w E (d) < w E (a) < w E (c) w M (a) < w M (d) < w M (c) w W (a) < w W (c) < w W (d) Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 32 / 50

Equilibria Simple example (continued) Applications autocracy? limited franchise full democracy What happens if β large and p small? Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 33 / 50

Equilibria Simple example (continued) Applications autocracy! limited franchise full democracy Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 34 / 50

Equilibria Simple example (continued) Applications What happens if p = 1 or close to 1? autocracy! limited franchise full democracy What happens if β small or intermediate? Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 35 / 50

Equilibria Simple example (continued) Applications Now suppose that p takes different values in different environments. We start in E 1 and then stochastically transition to either E 2 or E 3, both of which are absorbing, and p E2 = 1 and p E3 < 1. Is an early resolution of uncertainty good for transitioning to democracy? autocracy limited franchise??? full democracy Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 36 / 50

Equilibria Applications Application: Radicals in Politics Most regime transitions take place in the midst of uncertainty and turmoil, which sometimes brings to power the most radical factions such as the militant Jacobins during the Reign of Terror in the French Revolution or the Nazis during the crisis of the Weimar Republic. The possibility of extreme outcomes also of interest because, in many episodes, the fear of such radical extremist regimes has been one of the drivers of repression against a whole gamut of opposition groups. Leading example: the Bolshevik Revolution in Russia. A fringe group that was repressed from the early 1900s came to power after the February Revolution, first entering into an alliance with the liberal left, then with the Social Revolutionaries, then with the left Social Revolutionaries, and at each stage, tilting power towards itself. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 37 / 50

Equilibria Applications Application (continued) Consider a society consisting of n + 1 groups. The stage payoff of each group depends on the current political state which encapsulates the distribution of political and economic rights. Each group maximizes the discounted stage payoffs and may also incur additional costs from transitions across (political) states. Stochastic shocks affect both stage payoffs and the likelihood of shifts in political power in a given political state (e.g., in the Russian context, the possibility of a group inside or outside the Duma grabbing power or sidelining some of the rest of the groups). Suppose that a shock to the environment starting from the stable dictatorship of the tzar changes stage payoffs and makes it desirable to include share power with moderate groups. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 38 / 50

Equilibria Applications Application (continued) Now several considerations are potentially important. First, the tzar may not go all the way to including all left groups or may maintain a veto power if feasible, because he may be worried of a slippery slope once power shifts to these groups, they may later include additional groups further to the left, which is costly for the tzar. Second, the probability that radical extremist groups may gain power might be higher in states in which additional groups to the left are included in the decision-making process (again potentially as in the Russian case), further discouraging limited power-sharing. Thus, in these first two scenarios, the tzar might be afraid of our stylized description of the Russian path where power gradually (and stochastically) shifts from left liberal groups to the coalition of socialist/communist groups, and then ultimately to the most extreme elements among them, the Bolsheviks. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 39 / 50

Application (continued) Equilibria Applications Third, and counteracting the first two, the most moderate left groups may be unwilling to enter into alliances with other groups to their left because they are themselves afraid of a yet another switch of power to groups to their left. But if so, the tzar may be more willing to allow power-sharing in this case, calculating that further slide down the slope will be limited. Can we model these dynamics and get more insights? Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 40 / 50

Equilibria Applications Application: Model There is a fixed set of n players (groups) N = { l,..., r} (so n = l + r + 1). We interpret the order of groups as representing some economic interests (poor vs. rich) or political views. The set of states is S = { l r,..., l + r} (so the total number of states is m = 2l + 2r + 1 = 2n 1), and they correspond to different combinations of political rights. Repression: a way of reducing the political rights of certain groups The set of players who are not repressed in state s is H s, where H s = { l,..., r + s} for s 0 and H s = { l + s,..., r} for s > 0. Thus, the states below 0 correspond to repressing the rich (in the leftmost state s = l r only the group l has vote), the states above 0 correspond to repressing the poor (again, the rightmost state s = l + r on the group r has vote), and the middle state s = 0 involves no repression and corresponds to full democracy (with the median voter, normalized to be from group 0, ruling in state 0). Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 41 / 50

Equilibria Applications Application (continued) Stage payoff with policy p (and repression of groups j / H s ): u i (p) = (p b i ) 2 j / Hs γ j C j. The weight of each group i N is denoted by γ i and represents the number of people within the group, and thus the group s political power. in state s, coalition X is winning if and only if i Hs X γ i > 1 2 i H s γ i. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 42 / 50

Equilibria Applications Application: Model (continued) It is possible that a radical will come to power without having majority because of shocks and crises. Let us model this by assuming that there is a set of k environments R l r,..., R l r +k 1, and probabilities λ j [0, 1], j = 1,..., m, to transition to each of these environments; the environment R j is the same as E, except that in states l r,..., j, the decision-making rule comes into the hands of the most radical group l. In other words, the probability of a radical coming to power if the current state is s is µ s = s j= l r λ j, and it is (weakly) increasing in s. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 43 / 50

Application: Results Equilibria Applications Proposition (Equilibria without radicals) In the absence of shocks (i.e., if environment E never changes), there exists a unique MVE given by a function φ : S S. In this equilibrium: 1 Democracy is stable: φ (0) = 0. 2 For any costs of repression {C j } j N, the equilibrium involves non-increasing repression: if s < 0 then φ (s) [ s, 0], and if s > 0, then φ (s) [0, s]. 3 Consider repression costs parametrized by parameter k: C j = kc { where C j } are positive constants. Then there is k > 0 such that: if k > k, then φ (s) = 0 for all s, and if k < k, then φ (s) = 0 for some s. j, Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 44 / 50

Equilibria Applications Application: Results (continued) But if there are radicals, then radicals themselves will use repression, and this may increase repression. Proposition (Radicals) There exists a unique MVE. In this equilibrium: 1 After radicals came to power, they are more likely to move to their preferred state l r (repress everyone else) if (a) repression is less costly (in the sense that k is lower, as in parametrization above), and (b) they are more radical (meaning their ideal point b l is lower). 2 Before radicals come to power, if s 0 then φ (s) s, but φ (s) > s is possible if s > 0. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 45 / 50

Equilibria Applications Application: Results (continued) In fact, the fear of radicals can push moderates to repression. Define: W i (s) = 1 µ s 1 β (1 µ s ) u µ i (s) + s (1 β) (1 β (1 µ s )) u i ( l r). Proposition (Repression by moderates anticipating radicals) Suppose that the radicals, when in power, move to their preferred state. 1 If W 0 (0) < W 0 (x) for some x > 0, then there is a state s 0 such that φ (s) > s. In other words, in some state there is an increase in repression in order to decrease the chance of radical coming to power. 2 If for all states y > x 0, W Mx (y) < W Mx (x), then for all s 0, φ (s) s. (This will happen if costs C are high enough.) Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 46 / 50

Equilibria Application: Results (continued) Applications Comparative statics of repression: Proposition (More repression) Suppose that there is a state s 0 (i.e., full democracy or some state } favoring the right), which is stable in E for some set of probabilities {µ j. Let us consider an anticipated or unanticipated } { } change from {µ j to µ j such that µ j = µ j for j s. After this change, there will never be less repression of the left, i.e., φ E (s) φ E (s) = s. Both greater and lesser power of radicals in left states leads to greater repression. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 47 / 50

Equilibria Application: Results (continued) Applications Path dependence in history: Proposition (Role of radicals in history) Suppose the society was in a stable state x 0 before the radical came to power. Then the ultimate state, after the radical comes and possibly goes, will be some y x. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 48 / 50

Equilibria Application: Results (continued) Applications Strategic complementarities and repression: Proposition (Strategic Complementarity) Suppose the costs of repressing other groups declines for the radicals. Then it becomes more likely that φ (s) > s for at least one s 0. The history of repression in places such as Russia may not be due to the culture of repression but to small differences in costs of repression (resulting from political institutions and economic structure). Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 49 / 50

Roadmap Roadmap Roadmap Work in progress for a general framework for the analysis of political change, stability and regime dynamics. Plan: Complete development of the framework. Systematic general comparative static results. Sharper results for specific applications. Many general insights in the context of economic, social and political change. Many new applications (as well as new areas). Empirical and historical applications. Acemoglu (MIT) Political Change, Stability and Democracy February, 13, 2013. 50 / 50