Abstract
Networks underlie notable cases of rapid development without democratic institutions, a phenomenon known as crony capitalism that has two distinctive features: (1) dispensation of selective privileges, and (2) social connections among beneficiaries. This paper advances a formal theory that explains how crony networks can induce large-scale effects that can both propagate risk of predation and incentivize private protection to withstand it. Dense networks that activate both relational mechanisms translate into aggregate outcomes wherein governments respect property rights for favored parties. From formal theory, I derive equilibrium predation conditions for a computational model that examines how variable network structures impact the number of protected privileges. A statistical analysis of computer simulations lends support for the posited relational mechanisms that scale up protection in successful cases of crony capitalism.
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Notes
I conceptualize democracies and autocracies (or dictatorships) as distinct types of regimes but acknowledge that discretion alone is not sufficient to fully distinguish them. For instance, it’s possible for nominally democratic governments to have sufficient discretion to behave as autocrats (Weldon 1997).
Leeson (2007) makes a similar argument based on a cost–benefit analysis, but instead of statelessness versus formal government, I am contrasting autocracy with democracy.
To simplify the presentation, I henceforth use the term autocrat in a broad sense to denote a government with unchecked authority and discretion.
Rents are supranormal profits beyond what would be obtained in a competitive setting.
Some asset holders can obtain rents from specialized assets that cannot be easily replicated. However, this is an unlikely economic condition for asset holders in developing countries, who will instead turn to political mechanisms. Evidence exists that economic actors care primarily about their own property rights, and if given the opportunity, would prefer market power to competition (Do and Levchenko 2009).
\(A_{i}\) has a reservation value \(v_{i}\) reflecting its ability to deploy assets elsewhere, which incorporates extant distinctions between captive and fugitive assets (Vahabi 2016).
When indifferent, players will choose as follows: \(G\) will enforce, \(D\) will honor its commitment, and \(A_{i}\) will invest.
I argue that search costs for private enforcers give public officials an advantage because the latter can be readily identified and their capacities to punish \(D\) verified more easily. Thus, I refer to elements of \(G\) as public officials, but membership extends to any elites with enforcement capacity.
Networks have structural properties, such as density, which captures overall connectivity. Labeled \(d\), density is equal to the ratio of actual to possible connections. For the network at hand, 16 possible connections exist. Null protection networks have zero density. A universal protection network with 16 connections attains the maximum value of 1. Other network types will have densities between zero and 1.
The collection of sets generally will not be mutually exclusive, with the exception of the special case of \(P_{i} {\bigcap }P_{j} = \left\{ \emptyset \right\}\), \(i \ne j\), a case of isolated firms corresponding to the model in Sect. 2.3. \(P_{i}\) can also be an empty set if no public officials protect a given \(A_{i}\).
Formally, \(S = { \hbox{max} }\left\{ {length\left( {A_{i} ,A_{j} } \right)} \right\}\), for all \(A_{j} \in A\), where length measures the number of steps that separate two particular nodes. When all public officials are related to at least one other member in \(G\), the maximum distance will be finite: \(S \le N - 1\). For completeness, I introduce a residual subset \(P_{i}^{\infty }\) to identify a group of isolated public officials (again, with respect to \(P_{i}\)) that are unreachable (as though the distance to them were infinite).
Note that it is a simpler network structure that connects nodes of the same type, also known as a one-mode network structure or network for short.
The scenario is similar to the logic that competition among autocrats can mitigate predation (Vahabi 2016). However, competition among autocrats also entails separate political domains. The term autocrat herein identifies a single political actor with uncontested authority within his own domain.
The example is contrived because it assumes homogeneous firms to highlight relational mechanisms. In the real world, we ought to see more heterogeneity, resulting in a more stringent condition for aggregate outcomes: for all firms to expect reliable protection, \(G_{1}\) must be powerful enough to inflict a penalty commensurate with the most profitable firm.
My theory does not analyze the optimal selection of initial attacks, which are plausible with a small number of players. However, optimizing attacks with large networks is an intractable problem that requires separate numerical analyses.
To clarify, the simulations are not agent-based, wherein actors follow simple behavioral rules. Rather, I apply game theory from previous sections that provides an implicit equilibrium condition applying to any network structure. The algorithm was coded in the R statistical environment to access existing SNA libraries and other statistical features (R Core Team 2017). See electronic supplementary materials to access computer code and related documentation.
Policy credibility is inversely related to successful predatory attacks.
The zero-inflation part of the model is not shown here to facilitate the presentation. The predictor for that model was AA_comp on the basis of the discussion above about the impact of fragmentation in precluding predation. The corresponding coefficient was statistically significant in all models.
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Acknowledgements
The author thanks the Editor-in-Chief, Prof. William F. Shughart II, for editorial guidance and detailed feedback. Three anonymous reviewers provided excellent comments. I am also grateful to Lee J. Alston and other participants at an Ostrom Workshop colloquium for additional comments on an earlier draft. The usual caveats apply. Computer simulations used equipment financed with a Faculty Research Support Grant from Indiana University’s Office of the Vice Provost for Research.
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Razo, A. Network structure and performance of crony capitalism systems credible commitments without democratic institutions. Public Choice 189, 115–137 (2021). https://doi.org/10.1007/s11127-020-00864-9
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DOI: https://doi.org/10.1007/s11127-020-00864-9