There is a vast, yet inconclusive, literature exploring the link between Corruption and economic growth, measured by a whole range of indicators (GDP, total factor productivity growth, investment rates). Some authors argue that corruption may foster economic development in that it constitutes the necessary "grease" to lubricate the wheels of stiff government administration, helping to overcome bureaucratic constraints, inefficient provision of public services and rigid laws. Others point out that the direction of the impact depends on the context in which corruption takes place, because instead of speeding up procedures, corrupt officials have an incentive to cause greater administrative delay in order to attract more bribes. The advocates of the "sand-the wheels" hypothesis argue that corruption reduces economic performance due to rent-seeking, increases of transaction costs and uncertainty, inefficient investment and misallocation of production factors. Moreover, the size of a country and the "industrial organization" of corruption, i.e. the degree of centralization of control and the time horizon of bureaucrats in power, can also influence the significance and sign of the relationship between corruption and economic growth, suggesting that nonlinearities are at play.
The incidence of corruption in the business environment can affect Aggregate total factor productivity (TFP) growth both directly and indirectly. Corruption influences individual firm performance directly by favouring or constraining productive activities. Indirectly, corruption may condition the degree of efficiency with which production factors are allocated across firms operating in a given sector, by diverting or channeling resources from the most to the least productive units. The reasons are manifold. Since corruption is illegal and must be kept secret, government officials will tend to induce substitution into the goods on which bribes can be more easily collected, shifting a country's investments away from the highest value projects to less useful projects if the latter offer better opportunities to collect bribes and avoid detection (Shleifer and Vishny 1993). Corrupt bureaucrats may also maintain monopolies, prop up inefficient firms, prevent firm entry, discourage innovation and allocate talent, technology and capital away from their most productive uses (Murphy, Shleifer and Vishny 1991; 1993; Campos, Estrin and Proto 2010). When profits are extracted from firms via bribes, entrepreneurs may choose to expand less rapidly or to forgo productive activity altogether, to shift their savings towards the informal sector, to organize production to minimize the need for public services and therefore interaction with public officials, thus leading to a sub-optimal size of their enterprise. By giving preference to businesses that are not necessarily on the cusp of innovation, corruption can impede "creative destruction". Indeed, the better connected firms, which successfully pay bribes to obtain government services and not necessarily are the most productive, can operate with far from optimal input combinations and survive (Garcia Santana et al. 2016). More in general, enormous time is lost by entrepreneurs engaged in corrupt activities, at the expense of firms productively running their business. On the other hand, it has been argued that corruption can guarantee efficient outcomes in competitions for government services: more productive entrepreneurs can afford higher bribes, so that licenses and government contracts are assigned to the most efficient firms (Lui 1985; Beck and Maher 1986). Moreover, bureaucrats themselves have an incentive to drive the most inefficient firms out of business, thereby enhancing the profitability of remaining firms, which in turns allows demanding higher bribes (Bliss and Di Tella 1997). More generally, corruption may promote allocative efficiency by allowing firms to correct pre-existing government failures, such as weak institutions or stiff regulations. Ultimately, the impact of corruption on input allocation is an empirical question that we intend to explore in this article.
Most of the empirical literature has focused either on the effect of firm-level bribery on firm productivity (for example, De Rosa, Gooroochurn and Gorg 2010; Hanousek and Kochanova 2016) or on the impact of total-economy corruption on a country's aggregate economic performance (for instance, Mauro 1995; Tanzi and Davoodi 1997). In this study, instead, we use firm-level data on bribes, which allow exploring the variance in firm experiences with corruption within countries, and we investigate the relationship between bribes and one specific determinant of sectorial TFP growth, that is the within-sector allocative efficiency of both capital and labour. To our knowledge, this is the first attempt in the literature to employ corruption data, collected at firm level and appropriately aggregated at the sector level, in order to explain sectorial input (mis)allocation. (1)
We focus on nine Central and Eastern European (CEE) economies, namely Croatia, the Czech Republic, Estonia, Hungary, Lithuania, Poland, Romania, Slovakia and Slovenia, over time, thereby employing a three-dimensional dataset (i countries, j sectors, t time-periods). These countries, selected on the basis of firm-level data availability, represent a fascinating case study for the analysis of the link between corruption and input misallocation. First, following their entry into the European Union, significant action was undertaken to fight corruption, albeit to a varying extent across countries and sectors. Second, according to total-economy, qualitative measures, corruption is still high in CEE countries relative, for example, to core euro-area countries, suggesting large scope for improvement still. Finally, to our knowledge, with the exception of Benkovskis (2015) which focuses on Latvia, not included in our sample, this is the first cross-country/sector study on allocative efficiency in the CEE region. (2)
Based on Hsieh and Klenow's (2009) seminal model, input misallocation can be measured by the dispersion in the marginal productivity of inputs across firms within a sector. In the absence of distortions and assuming all firms in the sector face the same marginal costs, in equilibrium the marginal productivity of a given input should be equalised across firms, i.e. the dispersion should be zero. The CompNet data we employ in this article show a significant increase in within-sector input dispersion in CEE countries over the period 2003-2012, albeit with different time patterns according to the type of production factor (labour or capital).
We adopt a narrow measure of corruption, focusing on a synthetic indicator we construct based on the frequency and amount of bribes to engage in productive activities reported by private non-financial firms, in turn taken from the World Bank and the European Bank for Reconstruction and Development's Business Environment and Enterprise Performance Survey (BEEPS). We therefore clearly distinguish corruption from organized crime and from industrial fraud by outsiders or by employees of the firms involved.
In our empirical analysis, framed within a neoclassical conditional Convergence model, we find that that corruption dynamics negatively affect changes in the efficiency with which both capital and labour are allocated across firms within given sectors, especially in economies which are small and politically unstable, with lesser civil freedom and with a weaker regulatory framework. "Contextual" variables are thus crucial in determining the effect of changes in bribery on input misallocation dynamics. These results are robust to the use of two instrumental variables for corruption, the share of female representation in Parliament and the degree of freedom of the press.
In conclusion, this article provides evidence on how fighting corruption in the CEE region is a significant means to reduce both capital and labour misallocation across firms and thus, via this channel, to boost aggregate TFP growth. We, however, necessarily underestimate the impact of eliminating corruption on TFP growth for at least two reasons: a) our definition of corruption is very narrow, so we are not considering other potential forms of corruption which can affect a country's development process and b) due to restricted data availability (i.e. the fact that the CompNet database only provides the distribution of firm's productivity within a sector and not the productivity of all firms in a given sector), in this article we cannot analyze the effect that bribes may exert on individual firms' productivity growth. The latter effect has been found to be sizeable in the literature (see, for example, Hanousek and Kochanova 2016) and would therefore have to be considered in addition to our results, when computing aggregate TFP gains from reducing corruption.
This article is structured as follows. Section 2 provides the theoretical And empirical framework underpinning the measures of input misallocation used herein and presents some evidence on resource misallocation in CEE countries since 2003. Section 3 provides a detailed analysis of BEEPS bribe data in the CEE region in the same period. Section 4 presents our empirical results referring to the relationship between changes in corruption and input misallocation. Section 5 concludes.
Labour and capital misallocation dynamics in CEE countries
2.1. A theoretical model for input misallocation
To measure input misallocation we adopt the theoretical approach developed by Hsieh and Klenow (2009; 2013), based on an economy with S intermediate goods sectors and one final goods producer that combines the output of the S sectors using a Cobb-Douglas production technology. In turn, each sector s is a CES aggregate of M differentiated products ([Y.sub.si]):
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Is corruption efficiency-enhancing? A case study of the Central and Eastern European region.
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