Corruption and Investment: Theory and Evidence from China
Introduction
Traditionally, corruption is considered a hurdle to investment and growth (e.g., Shleifer, Vishny, 1993, Mauro, 1995, Fisman, Svensson, 2007). China is one of the most corrupt countries in the world. Despite rampant corruption, however, China is thriving economically, posting an average growth rate of 10% for three decades powered by investment, particularly infrastructure investment.3 The coexistence of rampant corruption and unprecedented infrastructure development poses a serious question: why has rampant corruption not slowed infrastructure development in China?
Some have suggested that corruption provides an incentive for Chinese officials to promote infrastructure investment.4 This view is not formalized or developed, however, and we therefore lack an understanding of why and under what conditions corruption can increase investment. The incentive effect of corruption on government investment is clearly important, especially for policy evaluations. If corruption is found to be a major factor fueling Chinese officials’ insatiable appetite for investment, the implications for China’s push for rebalancing and reconsidering the relationship between corruption and development could be enormous.
This paper develops a principal-agent model to analyze the relationship between corruption and investment and examines three policies that can be used to combat corruption. In this model, the principal (the government in this case) hires agents (bureaucrats or officials) to implement infrastructure investment. Each bureaucrat alone knows the benefit and cost of the project assigned to him. He chooses costly effort to implement the investment project and the bribe amount to take from the investment. Although unable to directly observe effort or corruption behavior, the government can detect corruption and punish corrupt bureaucrats.
The model shows that an incentive to seek bribes can motivate self-interested bureaucrats to exert costly effort to implement investment, thereby resulting in high investment driven by corruption. In addition, when facing the choice between stealing at no cost and implementing investment at a cost, a bureaucrat may abstain from stealing and instead exert costly effort to implement investment. This occurs when the expected kickbacks from the investment are sufficiently large relative to the amount that can be stolen and when stealing is easier to detect than bribery. Empirically, this finding implies that there could be a decrease in nontransactional corruption (embezzlement) and a simultaneous increase in transactional corruption (bribery in public asset transfers and public contracts). The stylized facts of corruption behavior in China provide rare supporting evidence.
Furthermore, since investment decisions are made for the purpose of corruption gains, some investments are bound to be socially inefficient. In particular, corruption distorts government spending toward investments that feed corruption and away from investments that generate higher social returns but provide fewer opportunities for corruption. As a consequence, officials’ endless pursuit of large investment projects would result in wasteful investments. The policy implication of this theoretical finding is crucial: if government officials attempt to create opportunities for corruption in designing investment policies, for example, investment subsidies, such policies could lead to capital market misallocation (see, e.g., Lien et al., 2016).
We consider three policies that can be used to combat corruption and improve investment efficiency: compensation policy, increased monitoring intensity, and political reforms to enhance accountability. Our theory suggests that higher wages reduce the likelihood of a bureaucrat being corrupted but increase the bribe amount demanded by corrupt bureaucrats. In contrast, higher monitoring intensity reduces not only the number of corrupt bureaucrats but also the bribe amount under conditions that are realistic for many developing countries. Furthermore, increased monitoring intensity in general results in lower investments. An implication of this result is that it is optimal to strengthen anticorruption enforcement as the marginal benefit of investment declines. Finally, we find that enhancing accountability helps to reduce corruption and inefficient investment while at the same time not slowing down growth.
Since the theoretical model has a number of predictions that can be tested empirically, we also provide some empirical evidence in support of the theory. We apply a random effect model to panel data on corruption and investment in China, and estimate the causal effect of anticorruption effort on infrastructure investment using the feasible generalized least squares estimation method. Our empirical findings suggest that anticorruption efforts reduce infrastructure investment, supporting our major theoretical prediction.
This article contributes to a large literature on the impact of corruption on economic development.5 Some researchers (e.g., Leff, 1964, Hutington, 1968, Lui, 1985) have suggested that corruption may improve efficiency, as it allows entrepreneurs to bypass cumbersome regulations in many developing countries. However, others (e.g., Myrdal, 1968 and Bardhan, 1997) have noted that the distortions that corruption is assumed to mitigate are not exogenous and that corruption may provide officials with an incentive to create more distortions.
Our paper differs from these studies in that the total amount of resources is endogenous and increasing in efforts to promote investment, whereas the amount of resources for development is assumed to be fixed in the literature. Thus, according to our model, corruption leads to an increase in the quantity of investment and a decrease in the quality of investment, and the overall effect of corruption on development may be ambiguous. This model helps reconcile the seemingly contradictory findings in empirical studies. Whereas some empirical studies (e.g., Aidt, 2009) have uncovered a negative correlation between corruption and economic performance across countries, others (e.g., Rock, Bonnett, 2004, Méon, Weill, 2010) have found evidence that corruption can promote investment and growth, especially in countries with ineffective institutions and poor governance.6 This conflicting evidence prompts Svensson (2005, pp.39) to write the following in his survey paper: “This finding seems to lead to a puzzle. Most of the theoretical literature as well as case study and micro evidence suggest that corruption severely retards development. However, to the extent we can measure corruption in a cross-country setting, it does not affect growth.” In our model, while the authoritarian regime itself is an impediment to growth, mainly because officials are not held accountable as their counterparts in democratic societies are, corruption can provide them with an incentive to promote investment. As such, we offer a novel explanation for the so-called East Asian Paradox—the coexistence of high levels of investment, rapid economic growth and rampant corruption in China and some other East Asian countries (e.g., Rock and Bonnett, 2004).
In this sense, this paper is more closely related to those that emphasize the trade-off between market failure and corruption. According to these studies, markets malfunction in many instances, and corruption results as a byproduct of government intervention designed to correct market failures (e.g., Acemoglu and Verdier, 2000). However, these studies seldom consider the role of anticorruption policies; therefore, we lack an understanding of how different antigraft policies affect the objectives of government interventions. Mookherjee and Png (1995) analyze the trade-off among corruption, pollution and compensation policy but consider only the effect of compensation policy on corruption.
By identifying corruption as an important driver of China’s investment boom, we also offer a novel explanation of Chinese officials’ incentives to promote investment and therefore also contribute to the literature on the Chinese economy. In this literature, Chinese officials’ addiction to investment is usually associated with a promotion incentive (e.g., Li and Zhou, 2005). However, some recent studies also consider a corruption incentive, in addition to the promotion incentive, in explaining China’s economic growth (e.g., Wang, Zheng, Huang, Zheng, Xu, Huang, Shi).
The remainder of the paper is organized as follows. Section 2 provides some background information on infrastructure investment and corruption in China. Section 3 sets up the basic model. Section 4 explores the effects of different policies on corruption and investment. Section 5 considers some extensions of the basic model. Section 6 presents the empirical evidence. Section 7 concludes.
Section snippets
Background
Under China’s regionally decentralized authoritarian (RDA) regime, political and personnel governance are centralized, but economic governance is regionally decentralized. The central government has control over personnel and uses appointment and promotion as tools to induce local governments to follow the central government’s policies. Local governments, however, are the major actors in the economy. Local government officials assume immense responsibilities for economic development. They
The setup
There are three types of players in the game: a benevolent government, bureaucrats, and a continuum of citizens of measure one.
Government: The aim of the government is to implement a set of infrastructure projects. However, as it lacks the information and expertise needed to implement any projects on its own, it relies on bureaucrats (also called officials or agents) to collect information, make decisions, and implement projects. Time is continuous with a common discount factor r.
Citizens:
Bureaucrat’s choices
For a given monitoring intensity σI, the optimization problem facing a bureaucrat who takes a bribe is:
From the above discussion, we know that under certain conditions, a bureaucrat may choose not to take any bribe. For the discussion to be non-trivial, we make the following assumption: Assumption 2 .
Assumption 2 ensures that at least some bureaucrats will take a bribe. To see this, recall that the maximum bribe the
Allow stealing
In this section, we assume that each bureaucrat needs to simultaneously perform two tasks. The first is to implement infrastructure investment at a cost as described in the basic model, while the second is to administer a government-spending program E. We assume that fulfilling this task is costless and, thus, the only choice for a bureaucrat is how much to steal, denoted by s. Stealing will be detected with probability σE ∈ (0, 1). For simplicity, we assume that the probability of detection σE
Empirical evidence
The theoretical model provides several testable predictions. In this section, we use provincial-level macrodata from China to provide some empirical evidence consistent with the theoretical model.
Conclusion
This paper analyzes the links between corruption and government infrastructure investment. The model demonstrates that corruption incentives can drive public infrastructure investment and predicts that increased anticorruption enforcement in general reduces investment. Moreover, it shows that the ability of a society to resolve collective action problems may not only affect its development outcome but also determine the types of corruption that it faces. Empirical tests using Chinese provincial
Declaration of Competing Interest
The authors declare that he has no relevant or material financial interests that relate to the research described in this paper.
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We are grateful to Shuaizhang Feng and Xiaolan Zhou for invaluable assistance. We thank Alberto Batinti, Sambuddha Ghosh, Srihari Govindan, Dimitar Gueorguiev, James Heckman, Lars Lefgren, David Levine, Lance Lochner, Francis T. Lui, Arunava Sen, Ling Shen, Andre Veiga, Xi Weng, Jan Werner, Zhiyong Yao, the associate editor and two anonymous referees for comments. This work is supported by the Chinese National Science Foundation (Project No. 71573168).
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Xiao acknowledges support from the Major Project of Key Research Base of Humanities and Social Sciences of Ministry of Education (18JD790002), during his visit to the Center for the Industrial and Business Organization at the Dongbei University of Finance & Economics.