Abstract
The paper constructs a framework where both welfare-impact and corruption-impact of the introduction of competition in a monopoly bureaucracy can be derived. Two different measures of corruption i.e. Incidence of Corruption and Corruption Rents have been applied to measure two different types of corruption: extortion and collusion. The paper shows that the conclusion we draw about corruption-impact and welfare-impact of the introduction of competition in a bureaucracy depends on the type of corruption we are looking at and the type of measure we are using. It also shows that with the introduction of competition in a monopoly bureaucracy the corruption measure and the welfare measure of an economy may move in opposite directions. The policy implications of the results are discussed.
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Menes (1999, 2003) argues that an important contributing factor to declining municipal corruption in the United States during the turn of the nineteenth century was the expansion of American Frontier and development of railroads, which raised the ‘elasticity’ of the local revenue base to bribe rates.
In India a FIR (First Investigation Report) can be registered at any police station, not necessarily at the jurisdiction where the crime has taken place.
One of these measures of corruption has been widely used (Cadot 1987; Mookherjee and Png 1995; Bliss and Di Tella 1997; Guriev 2004; Barron and Olken 2009).One can also think about additional alternative measures of corruption like Relative Rent which is defined as the amount of bribe paid as a proportion the value of the firm’s license. We do not discuss it separately here as it gives identical results to the comparison of CR measure. Also, the axiomatic foundation of such a measure remains to be checked.
In Drugov (2010) they differ with each other in terms of their cost of production.
See Ahlin and Bose (2007) and Bhattacharya and Mukherjee (2019) for models where the information about the firm remains private even at the time of interaction. While both papers discuss red tape, the former concentrates on the effect of introduction of bureaucratic competition on welfare of such an economy.
As opposed to Nash Bargaining, one can think of a take-it-or-leave-it bribe offer (TIOLI) where firms have no bargaining power. Although TIOLI bribe offer changes the bribe amounts, the results of the paper that compares a monopoly bureaucracy with a competitive bureaucracy qualitatively remain unaffected.
In this paper we assume the number officials in the bureaucracy is sufficiently large. An interesting extension of this paper will be the case of a small bureaucracy where the game will have a finite horizon. We discuss the heuristics of the finite horizon case in footnote 10 below.
In the present model, officials and firms discount the delay at the same rate. However, Drugov (2007) discusses the case where the firms have a cost of reapplication different from cost of delay.
See Svensson (2005).
Notice that monopoly bribe rate is non-discriminatory. The qualified firm is forced to pay the same bribe as the unqualified firm because the qualifying investment is sunk. The monopoly official while negotiating bribe does not care about whether the firm has undertaken qualifying investment or not. Anticipating this, a firm (with potential revenue \(R_{i}\)) adopts investment decision in such a way that its profit is maximized.
Note here depending on the regime type and their own period 1 investment strategy it is the disagreement payoff of the firms that changes. Also, that the assumption of availability of large number of officials in the bureaucracy and infinite reapplication possibility plays an important role in determination of bribes in competition regime. For realizing this clearly, consider the case of a firm which has decided never to invest in qualifying technology. There is a possibility that it meets a corrupt official and obtains the license immediately. However, it may meet an honest official and on denial of the license reapplies to a randomly chosen official in the next period. In period 3 the same situation may arise again, and the sequence can be repeated for infinitely large number of periods. Thus the expected profit of the firm becomes \(\left( {1 - h} \right)\left( {R_{i} - b_{c}^{u} } \right) + \delta h\left[ {\left( {1 - h} \right)\left( {R_{i} - b_{c}^{u} } \right) + \delta h\left( {1 - h} \right)\left( {R_{i} - b_{c}^{u} } \right) + \ldots } \right]\). With each reapplication the expected profit of the firm increases and the bribe surplus falls but at a diminishing rate. Consequently, the bribe rate falls. In a bureaucracy with small number of officials, the bribe surplus and the bribe rate are expected to be higher than the bribe rates presented in Lemma 3 above. In each case the bargaining surplus is equally divided between the firm and the corrupt official in determination of bribe.
One might also implement Relative Corruption Incidence (CRI) which measures the ratio of licenses involving a bribe to the total number of licenses administered. Note that since license through a bribe is delivered by the proportion of corrupt officials this measure is represented \(\left( {1 - h} \right)\) and thus is same across the regimes.
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Earlier versions of the paper received helpful comments from conference participants at NIPFP, New Delhi, The University of Calcutta, Indian Institute of Management, Bangalore, Indian Statistical Institute, New Delhi, Heidelberg University, Technical University Dresden and Indira Gandhi Institute of Development Research, Mumbai. Discussions with Mihir Bhattacharya, Sukanta Bhattacharya, Tapas Kundu, Tobias Stoehr and Marcel Thum were beneficial. An earlier version was circulated as NIPFP Working Paper #152. The usual disclaimer applies.
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Banerjee, P., Mukherjee, V. Bureaucratic competition versus monopoly: measuring corruption and welfare. Ind. Econ. Rev. 55, 51–65 (2020). https://doi.org/10.1007/s41775-020-00080-8
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DOI: https://doi.org/10.1007/s41775-020-00080-8