Competition is a good thing not only because of lower prices and larger variety. Higher competition in the domestic market also shifts necessary labour and capital resources from less productive domestic-oriented firms to export-oriented productivity champions. Such firms will make better use of production factors and generate larger output. Thus, simply increasing the level of competition in the domestic market can boost the aggregate productivity of a country.
The aggregate productivity of a country can be boosted even without changing the productivity of individual enterprises. This can be achieved by improving the allocation of resources – the redistribution of labour and capital towards more productive firms. These firms will make better use of production factors and generate larger output. But how can one affect the allocation of resources? Economic theory says that allocation depends on the productivity of individual firms: more productive enterprises attract more labour and capital. However, there exists another factor behind allocation: distortions.
Distortions affect the allocation of resources
A model developed by Hsieh and Klenow (2009) – one of the most popular frameworks to study the allocation of resources – has a very important and realistic feature: it acknowledges that firms are not treated equally. Some firms may face lower supply of banking loans ending with higher capital costs. Other firms could confront with trade unions and higher wages. Tax rates may also differ across firms. These are all examples of distortions. Firms facing larger distortions are forced to underuse respective production factor, while firms that enjoy more favourable conditions tend to overuse capital and labour, generating more output.
While it is virtually impossible to imagine an economy without any distortions (the one where all firms face the same taxes, costs of labour, capital etc.), not all distortions damage the allocation of resources. Only distortions to productive firms create misallocation of resources by shifting labour and capital towards unproductive firms. Thus, removal of such distortions can improve the efficiency of allocation and raise the aggregate output of the country.
According to Hsieh and Klenow (2009) the distortions faced by every individual firm can be quantified from the balance sheets and profit/loss data. For example, observing lower-than-usual ratio of capital to intermediate inputs (comparing with other enterprises in a narrowly defined industry) indicates a capital distortion, possibly related with limited access to banking loans. Similarly, lower-than-usual share of wages in total production costs implies high labour distortions. Finally, the size of the distortion can be detected as a case of abnormally low share of intermediate inputs in total output, and signals about the restrictions to total output (e.g. due to higher taxes for large enterprises).
Misallocation of resources is small in Latvia
In my recent research (see Benkovskis, 2015), I use anonymised firm-level dataset for 2007–2013 and apply the Hsieh and Klenow (2009) model to study the allocation of resources in Latvia – a unique example of a small and open economy facing extreme structural shifts during the financial crisis. According to my estimates, the negative contribution of misallocation to aggregate productivity was close to 27% in 2013 (see Figure 1). In other words, it suggests that actual aggregate productivity could be boosted by 27% if all distortions were removed!
This may seem large but in fact 27% is a comparatively low figure. Hsieh and Klenow (2009) argue that full liberalisation would boost aggregate manufacturing productivity by 86–115% in China, 100–128% in India, and 30–43% in the US. Dias et al. (2015) show that removing distortions would lead to a 30% gain in output of Portugal in 2011. Thus, misallocation of resources is relatively small in Latvia. Even more important: the misallocation of resources decreased after the crisis in Latvia (contrary to the case of Portugal), adding more than 10 percentage points to aggregate productivity growth between 2010 and 2013.
Figure 1. Contribution from misallocation of resources to aggregate total factor productivity, %
Source: Benkovskis (2015). Note: shows the contribution of misallocation comparing with the counterfactual case of no distortions.
The finding that allocation of resources improved after the crisis is interesting per se, but uncovering the reasons behind the improvement is even more important. Figure 1 provides a decomposition, which shows that labour distortions are minor in Latvia due to high flexibility of labour market (in line with recent findings by Braukša and Fadejeva, 2016). The capital distortions, while being minor in 2007–2008, increased afterwards, pointing to some credit supply constraints faced by the highly productive enterprises after the financial crisis. However, by far largest contribution comes from the misallocation of intermediate inputs – the turnover of the most productive firms face some constraints. And it was the ease of constraints to turnover for the most productive firms that determined the improvements in aggregate productivity since 2010.
The level of competition matters for misallocation
My research stresses the importance of the competition level on the market, since higher competition serves as a natural constraint for the firm to increase its turnover. What if the most productive Latvia’s firms systematically come up against higher competition? I found that indeed this is the case. First, recent results by Fadejeva and Krasnopjorovs (2015) show that Latvia’s domestic market has lower competition level comparing with external markets. Second, it is widely acknowledged that exporters tend to be more productive comparing with domestically oriented firms (see e.g. Bertou et al., 2015, who report positive export premiums for EU countries, while Benkovskis and Tkačevs, 2015, find higher productivity of exporters in Latvia). Thus, Latvia’s productive export-oriented firms are subject to higher competition and cannot enlarge their turnover as easy as other entities. This shifts labour and capital towards small and less productive firms working solely on domestic market, creating the misallocation of resources.
The domestic competition factor can also explain the improving allocation of resources after 2010. The study by Fadejeva and Krasnopojorovs (2015) reveals that the competition gap between domestic and foreign markets narrowed after the financial crisis (see Table 1). Namely, life was too easy on the local Latvia’s market during the boom time, allowing unproductive firms to survive and drain away resources from more productive firms. But conditions became tougher after the crisis (although the competition level still remained lower than abroad). We can view this as a “cleansing effect of the crisis”: some of the least productive domestic oriented firms went bankrupt (or decreased their turnover), freeing the necessary capital and labour resources for productive exporters.
Table 1: Change in the competitive pressure on main product in domestic and foreign markets compared to the situation before 2008, %
|Domestic market||Foreign market|
|Does not apply||2.8||2.8||9.4||13.1|
Source: Fadejeva and Krasnopjorovs (2015), Table A.102. Notes: based on the sample of 557 Latvia’s firms; results are weighted to represent firm population.
This research has an important policy conclusions applicable to any country that seeks to increase aggregate productivity. The competition level in the domestic market is important not only for consumers, who enjoy lower prices and higher variety. Higher competition in the domestic market also shifts necessary resources from less productive domestic-oriented firms to export-oriented productivity champions.
- Benkovskis, Konstantins; 2015. “Misallocation of resources in Latvia: did anything change during the crisis?”, Latvijas Banka Working Paper No.5/2015.
- Benkovskis, Konstantins; and Olegs Tkacevs, 2015. “Everything you always wanted to know about Latvia’s service exporters (but were afraid to ask)”, Latvijas Banka Working Paper No.6/2015.
- Berthou, Antoine; Emmanuel Dhyne; Matteo Bugamelli; Ana-Maria Cazacu; Calin-Vlad Demian; Peter Harasztosi; Tibor Lalinsky; Jaanika Meriküll ; Filippo Oropallo; and Ana Cristina Soares, 2015. “Assessing European Firms’ Exports and Productivity Distributions: The CompNet Trade Module”, ECB Working Paper, No. 1788.
- Braukša, Ieva; and Ludmila Fadejeva, 2016. “Internal labour market mobility in 2005–2014 in Latvia: the micro data approach”, Baltic Journal of Economics, 16(2), 152–174.
- Dias, Daniel A.; Carlos Robalo Marques; and Christine Richmond, 2015. “Misallocation and Productivity in the Lead Up to the Eurozone Crisis“, International Finance Discussion Papers 1146.
- Fadejeva, Ludmila; and Olegs Krasnopjorovs, 2015. “Labour Market Adjustment during 2008–2013 in Latvia: Firm Level Evidence”, Latvijas Banka Working Paper, No. 2/2015.
- Hsieh, Chang-Tai; and Peter J. Klenow, 2009. “Misallocation and manufacturing TFP in China and India“, The Quarterly Journal of Economics, 124(4), 1403–1448.
Authors: Vasiliki Bageri, University of Athens, Yannis Katsoulacos, Univeristy of Athens, and Giancarlo Spagnolo, SITE.
Competition law has recently been introduced in a large number of developed and emerging economies. Most of these countries adopted the common practice of basing antitrust fines on affected commerce rather than on collusive profits, and in some countries caps on fines have been introduced based on total firm sales rather than on affected commerce. Based on recent research, this policy brief explains how a number of large distortions are connected to these policies, which may facilitate competition authorities in their everyday job but at the high risk of harming the consumer and distorting industrial development. We conclude by discussing the possibility to depart from these distortive rules-of-thumb opened by recent advancements in data availability and econometric techniques, as well as by the considerable experience matured in estimating collusive profits when calculating damages in private antitrust litigation.
Competition policy has become a prominent policy in many developing economies, from Brazil to India. Indeed, the available evidence suggests that in countries where law enforcement institutions are sufficiently effective, a well designed and enforced competition policy can significantly improve total and labor productivity growth.
It is already well known that the private enforcement of competition policy can give rise to large distortions: since competition law is enforced by Judges and not by economist, it is easy for firms to strategically use the possibility to sue under the provision of competition law to protect their market position rather than the law being used to protect competition.
It is somewhat less known that a poor public enforcement of Competition Law by publicly funded competition authorities can also end up worsening market distortions rather than curing them. In the reminder of this policy brief we explain why, according to recent research, a mild and suboptimal enforcement of antitrust provisions – in the sense of fines that are too low to deter unlawful conduct (horizontal agreements and cartels in particular) and fines which are based on firm revenue rather than on the extra profits generated by the unlawful conduct, could significantly harm social welfare, even if we abstract from the direct cost the public enforcement of competition law imply for society.
Current Practice in Setting Fines
A very important tool for the effective enforcement of Competition Law is the penalties imposed on violators by regulators and courts. In this policy brief, we uncover a number of distortions that current penalty policies generate, we explain how their size is affected by market characteristics such as the elasticity of demand, and quantify them based on market data.
In contrast to what economic theory predicts, in most jurisdictions, Competition Authorities (CAs), but also courts where in charge, use rules-of-thumbs to set penalties that – although well established in legal tradition and in sentencing guidelines and possibly easy to apply – are hard to justify and interpret in logical economic terms. Thus, antitrust penalties are based on affected commerce rather than on collusive profits, and caps on penalties are often introduced based on total firm sales rather than on affected commerce.
A First Well Known Distortion Due to Legal Practice
A first and obvious distortive effect of penalty caps linked to total (worldwide) firm revenue is that specialized firms which are active mostly in their core market expect lower penalties than more diversified firms that are also active in several other markets than the relevant one. This distortion – why for God’s sake should diversified firms active on many markets face higher penalties than more narrowly focused firms? – could in principle induce firms that are at risk of antitrust legal action to inefficiently under-diversify or split their business to reduce their legal liability.
In a recent paper published in the Economic Journal, we examine two other, less obvious, distortions that occur when the volume of affected commerce is used as a base to calculate antitrust penalties.
A Second Distortion: Poorly Enforced Competition Law May Increase Welfare Losses from Monopoly Power
If expected penalties are not sufficient to deter the cartel, which seems to be the norm given the number of cartels that CAs continue to discover, penalties based on revenue rather than on collusive profits induce firms to increase cartel prices above the monopoly level that they would have set if penalties were based on collusive profits. Intuitively, this would be done in order to reduce revenues and thus the penalty. However, this exacerbates the harm caused by the cartel relative to a monopolized situation with similar penalties related to profits, or even relative to a situation with no penalties due to the distortive effects of the higher price and, in comparison to a situation with no penalties, the presence of antitrust enforcement costs.
A Third Distortion: Firms at the Bottom of the Value Chain May Pay a Multiple of the Fine Paid by Firms at the Top for an Identical Infringement
Firms with a high revenue/profit ratio, e.g. firms at the end of a vertical production chain, expect larger penalties relative to the same collusive profits that firms with a lower revenue/profit ratio would get. Our empirically based simulations suggest that the welfare losses produced by these distortions can be very large, and that they may generate penalties differing by over a factor of 20 for firms that instead should have faced the same penalty.
Note that this third distortion takes place also when at least for some industries fines are sufficiently high to deter cartels. This distortion means that competition is only enforced in industries that happen to be in the lower end of the production chain, and not in industries where the lack of competition is producing larger social costs. Note also that our estimation is based only on observed fines, i.e. on fines paid by cartels that are not deterred. Since cartels tend to be deterred by higher fines, this suggest that if we could take into account the fines that would have been paid by those cartels that were deterred (if any), the size of the estimated distortion would likely increase!
We argue that if one wants to implement a policy, one must be ready to do it well otherwise it may be better to not do it at all. This is particularly relevant for countries with weaker institutional environments where it is likely that political and institutional constraints will not allow for a sufficiently independent and forceful enforcement of the Competition Law.
It is worth noting that – in particular in the US but also increasingly so in the EU – the rules-of-thumb discussed above do not produce any saving in enforcement costs because the prescribed cap on fines requires courts to calculate firms’ collusive profits anyway. Furthermore, the distortions we identified are not substitutes where either one or the other is present. Instead, they are all simultaneously present and add to one another in terms of poor enforcement.
Where there are sufficient resources to allow for a proper implementation and where enforcement of Competition Law is available, developments in economics and econometrics make it possible to estimate illegal profits from antitrust infringements with reasonable precision, as regularly done to assess damages. It is time to change these distortive rules-of-thumb that make revenue so central for calculating penalties, if the only thing the distortions give us is savings in the costs of data collection and illegal profit estimation.