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Rewarding Whistleblowers to Fight Corruption?

Posted on October 23, 2017 | Policy Brief

Whistleblower reward programs, or “bounty regimes”, provide financial incentives to witnesses that report information on infringements, helping law enforcement agencies to detect/convict culprits. These programs have been successfully used in the US against procurement fraud and tax evasion for quite some time, and were extended to fight financial fraud after the recent crisis. In Europe there is currently a debate on their possible introduction, but authorities appear much less enthusiastic than their US counterparts. In this brief, we discuss recent research on two commonly voiced concerns on whistleblower rewards – the risk of increasing false accusations, and that of crowding out other motivations to blow the whistle – and the adaptations these programs may need to fight more general forms of corruption. Research suggests that the mentioned concerns can be handled by an appropriate design and management of the programs, as apparently done in the US, and that these programs can indeed be a cost effective instrument to fight corruption, but only in countries with a sufficient quality of the judicial system and administrative capacity. They may instead be problematic for weak institutions environments.

Corruption and fraud seem to remain highly widespread in almost all countries. For example, a recent survey of over 6,000 organizations across 115 countries shows that one in three organizations, both worldwide and in the US, experienced fraud in the past 24 months, prevalently in the form of asset misappropriation, cybercrime, corruption, and procurement and accounting fraud (Global Crime Survey, 2016).

Whistleblower (protection and) reward programs are a possibly effective tool to combat fraud and corruption, at least in the light of the US successful experience, where for a long time whistleblowers reporting large federal fraud have been entitled to up to 30% of recovered funds and sanctions under the False Claims Act. The US Internal Revenue Service (IRS) also allows whistleblower rewards in the tax area, and the Dodd-Frank Act introduced them for financial and securities fraud, apparently also with success (c.f. Call et al., 2017, and Wilde, 2017).

In Europe and the rest of the world, instead, rewards are absent and whistleblowers are still poorly protected from retaliation from employers. Some countries have taken encouraging legal steps to at least improve protection, and a discussion is ongoing at the G20 level on how to further improve the situation (G20 report, 2011).

Although many praise whistleblowers, there has been a large range of objections raised against introducing rewards (and even against improving whistleblower protection); mostly by corporate lawyers and lobbyists, but also by regulatory and law enforcement agencies (see Nyreröd and Spagnolo, 2017, for an overview).

In the rest of this brief, we focus on two often voiced concerns, the risks of eliciting false/fraudulent reporting and of crowding out of non-financial motivation, on which recent research has shed light that should be taken into account in the current policy debate. We then discuss some problems linked to the use of whistleblower rewards programs in a more general corruption context.

Fraudulent reports

One concern commonly raised in the discussion of whistleblower rewards is that they may create incentives to fraudulently report false or fabricated information in the hope of receiving a reward. Although clearly an important concern to take into account, we only know of very few anecdotal cases of malicious or false reporting, and fraudulent reporting does not appear to have been a major problem in the US (see again Nyreröd and Spagnolo, 2017 for an overview of the empirical evidence).

A recent paper by Buccirossi, Immordino and Spagnolo (2017) analyzes this concern within a formal economic model and shows that it is not a ground (or an excuse) for not introducing appropriately designed and managed protection and reward programs in countries with sufficiently effective court systems. In these countries, stronger sanctions against lying to the court can (and should) be introduced to balance the incentives for manipulation that may be generated by large bounties. Most legal systems already have defamation and perjury laws, which means that a whistleblower is already committing a crime by fraudulently reporting false information, that can easily be strengthened where necessary without giving up whistleblower rewards. According to this study, the balancing of incentives is what allows the US to effectively use large financial incentives for whistleblowers, besides a very strong protection from retaliation, with little problems in terms of fraudulent reports.

However, the study also shows that this is only possible if the precision (effectiveness, independence) of the court system is sufficiently high. Where court systems are imprecise, the interaction between courts’ mistakes in the legal case based on the information reported by the whistleblower and in the following case for perjury/defamation against the whistleblower if the first case is dismissed, incentives for fraudulent reports, and courts’ adaptation of the standard of proof to account for these incentives, make it impossible to appropriately balance the two incentives. Therefore, whistleblower reward programs should not be introduced in environments where the law enforcement system is ineffective, independently from why it is so (bureaucratic slack, incompetence, political interference, corruption, etc.).

Crowding-out non-financial motivation

Another concern is that whistleblower rewards may have a “crowding out” effect on intrinsic motivation. The problem is that “the commodification of whistleblowing via the provision of bounties may render would-be whistleblowers less likely to come forward by reducing the moral valance of the wrongdoing” (Engstrom, 2016:11). Recent experimental evidence suggests that this concern is overstated. In particular, Schmolke and Utikal (2016) investigate the effects of whistleblower rewards in an environment where one subject may increase his payoff at the cost of harming the group, and find rewards to be highly effective in increasing the number of crimes reported. Data from that experiment suggests a little role for crowding out of non-monetary motivation, if any. Another recent study by Butler, Serra and Spagnolo (2017) investigates if and how monetary incentives, expectations of social approval or disapproval, and the salience of the harm caused by the reported illegal activity interact and affect the decision to blow the whistle. Experimental results show that financial rewards significantly increase the likelihood of whistleblowing and do not substantially crowd out non-monetary motivations activated by expectations of social judgment. The study also finds that public scrutiny and social judgment decrease (increase) whistleblowing when the public is less (more) aware (aware) of the negative externalities generated by the reported crime. All in all, most the recent studies we are aware of suggest that crowding-out of non- financial concerns is not a first-order problem for whistleblower reward schemes as long as there is a clear perception of the public harm linked to the illegal behavior reported by the whistleblower.

Whistleblower rewards and corruption

Although whistleblowing can occur in any sector, firm, or government, an area of particular interest is corruption. Corruption in public procurement is estimated to cost the EU 5.3 billion Euros annually. Hence, corruption deterrence through increased whistleblowing could save the EU significant resources annually (EC Report, 2017).

Contrary to fraud, corruption always takes at least two parties, a bribe taker, typically a government official or politician, and a bribe giver, which may be a firm or an individual. The fact that at least one additional party is involved than in the standard case of fraud, should make whistleblower rewards programs even more powerful since they may deter corruption by increasing the fear that a (potential or real) partner in crime may blow the whistle, even when no third party witness observes the illegal act (Spagnolo, 2004).

When the reported wrongdoer is an individual, as is often the case with corruption, there may be an issue in the use of rewards for whistleblowers linked to the funding of the rewards (c.f Nyreröd & Spagnolo, 2017b for an overview).

In the current US schemes, rewards for whistleblowers are ‘self-financing’, as they constitute a fraction of the funds recovered thanks to the whistleblower or/and of the fines paid by the culprits. An individual and a government official involved in a corrupt deal may, however, not be wealthy enough for the fines and the recovered funds to amount to a sufficiently strong incentive to blow the whistle, given the loss of future gains from the corrupt relationships and the various forms of retaliation whistleblowing may lead to. This problem is of course also relevant for fraud when an individual with few or well-hidden assets is the culprit, rather than a corporation, but it seems particularly relevant for corruption.

Whistleblower reward programs are also malleable to the concerns at hand. If the priority is to combat higher-level corruption, then setting a monetary threshold for when a claim is to be considered is appropriate to limit administrative costs for the program. Indeed, a concern with utilizing whistleblower rewards programs for combating lower-level corruption is that the administrative burden required looking through the whistleblower claims and the costs of limiting abuses may outweigh the benefits gained in detection and deterrence. This concern is also valid for small fraud and tax evasion, which is why all the US programs have a minimum size for cases eligible to whistleblower rewards, but the problem is likely to be more relevant to the case of ‘petty’ corruption. These programs are more suited for ‘large cases’ in which the amount of funds recovered is large enough to pay for rewards and administrative costs, making these programs self-financing even without calculating the benefits for the deterrence/prevention of future infringements. However, when focusing on large corruption cases, other issues become relevant.

An issue particularly important for the case of ‘grand’ corruption is how independent the judicial system is from political pressure, and how able it is to protect whistleblowers against politically mandated retaliation. If corrupt politicians can importantly influence courts, the police or other relevant administrative agencies, then protection can hardly be guaranteed and inducing witnesses to blow the whistle through financial incentives may put their life at risk, although sufficiently large rewards can partly compensate for this risk and help escaping part of the retaliation.

Conclusion

On the whole, whistleblower rewards, in general and in the corruption context specifically, remain a promising tool to detect and deter crime. Careful design and implementation are necessary, because as for any powerful tool, these programs can be well used to do great thing, but also misused to do great damage. As the US experience has shown, along with sufficiently independent and precise courts and an effective administration of law enforcement, well designed and administered whistleblower reward programs hold the promise of greatly improving fraud and corruption detection and of being self-financing through recovered funds and fines.

Of course, even in a very good institutional environment, a poor design and/or implementation can lead to poor performance and do more harm than good (c.f. the case of leniency policies in China discussed in Perrotta et al., 2017). Moreover, in poor institutional environments, where the court system is not sufficiently precise and independent and other law enforcement institutions are not effective, even well-designed and implemented whistleblower reward schemes may bring more problems than benefits. Whistleblower rewards, as any other high-powered incentives, need good governance to ensure that the potentially very high benefits they can generate will be realized. Third parties like international courts and organizations could potentially provide for some low institution environments, the independent safe harbor necessary to protect whistleblowers and a check on court effectiveness for the award of financial incentives.

References

Global Economic Crime Survey, 2016. Available at: https://www.pwc.com/gx/en/economic-crime-survey/pdf/GlobalEconomicCrimeSurvey2016.pdf
Buccirossi, P., Immordino, G., and Spagnolo, G., 2017. “Whistleblower Rewards, False Reports, and Corporate Fraud”. SITE Working Paper No. 42, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2993776
European Commission Report, 2017. Estimating the Economic Benefits of Whistleblower Protection in Public Procurement, Milieu Ltd.
Engstrom, D., 2016. “Bounty Regimes”, in Research Handbook on Corporate Criminal Enforcement and Financial Misleading (Jennifer Arlen ed., Edward Elgar Press, forthcoming 2016)
Butler, J., Serra, D., and Spagnolo G., 2017. “Motivating Whistleblowers.” Unpublished manuscript. Available at: https://www.aeaweb.org/conference/2017/preliminary/1658
Schmolke, K.U., Utikal, V., 2016. “Whistleblowing: Incentives and Situational Determinants.” FAU – Discussion Papers in Economics, No. 09/2016. 2016. Available at: https://ssrn.com/abstract=2820475
Call, A.C., Martin, G.S, Sharp, N.Y., Wilde, J.H., 2017. “Whistleblowers and Outcomes of Financial Misrepresentation Enforcement Actions.” Journal of Accounting Research, forthcoming.
Wilde, J.H., (2017). “The Deterrent Effect of Employee Whistleblowing on Firms’ Financial Misreporting and Tax Aggressiveness”, The Accounting Review, forthcoming.
Nyreröd, T. Spagnolo, G., 2017a “Myths and evidence on whistleblower rewards”, SITE Working Paper No.
Spagnolo, G., 2004. “Divide et Impera: Optimal Leniency Programs.” CEPR Discussion Papers 4840, 2004.
Nyreröd, T. Spagnolo, G. 2017b. “Whistleblower Rewards in the Fight against Corruption?” (in Portuguese), forthcoming in the book Corrupção e seus múltiplos enfoques jurídi
Berlin-Perrotta, M., Qin, B. and Spagnolo, G., 2017. “Leniency, Asymmetric Punishment and Corruption: Evidence from China,” SITE Working Paper. Available at:https://ssrn.com/abstract=2718181 or http://dx.doi.org/10.2139/ssrn.2718181
G20 Anti-Corruption Action Plan, Protection OF Whistleblowers Study on Whistleblower Protection Frameworks, Compendium of Best Practices and Guiding Principles for Legislation, 2011. Available at: https://www.oecd.org/g20/topics/anti-corruption/48972967.pdf
Wolfe S., Worth M., Dreyfus S., Brown A.J., 2015. Breaking the Silence, Strengths and Weaknesses in G20 Whistleblower Protection Laws, 2015. Available at: https://blueprintforfreespeech.net/wp-content/uploads/2015/10/Breaking-the-Silence-Strengths-and-Weaknesses-in-G20-Whistleblower-Protection-Laws1.pdf

Latvia Stumbling Towards Progressive Income Taxation: Episode II

Posted on October 16, 2017 | Policy Brief

20171015 Latvia Stumbling Towards Progressive Income Taxation Image 01

In August 2017, the Latvian parliament adopted a major tax reform package that will come into force in January 2018. This reform was a long-awaited step from the Latvian authorities to make the personal income tax more progressive. Some of the elements of the adopted reform, e.g. the changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income inequality. At the same time, the way the newly introduced progressive tax rate is designed will effectively lead to a reduction in the tax burden on labor and will hardly introduce any progressivity to the system.

In recent years, reducing income inequality has become one of the top priorities of the Latvian government. Income inequality in Latvia is higher than in most other EU and OECD countries, and the need to address this issue has been repeatedly emphasized by the Latvian officials, the European Commission, the World Bank and OECD.

The main reason for high income-inequality is a low degree of income redistribution ensured by the tax-benefit system. The personal income tax (PIT) has been flat since the mid-nineties. While the non-taxable income allowance introduces some progressivity to the system, the Latvian tax system is characterized by a very high tax burden on low wages, compared to other EU and OECD countries.

Since the beginning of 2017, the government has worked on an extensive tax reform package that was passed in the parliament in August and will become effective as of January 2018.

Two years ago, we wrote about the tax reform of 2016. In this brief, we estimate the effect of the 2018 reform on the tax burden on labour and income inequality. We will only consider changes in direct taxes on personal income – the changes in enterprise income tax and excise tax are outside the scope of our analysis. Parts of our estimations are done using the tax-benefit microsimulation model EUROMOD (for more details about the EUROMOD modelling approach, see Sutherland and Figari, 2013) and EU-SILC 2015 data.

Tax reform 2018

We focus our analysis on four elements of the reform that are expected to affect income inequality and that are described below. In our simulations, however, we take into account all changes in the PIT rules.

First, the flat PIT rate of 23% will be replaced by a progressive rate with three brackets: 20% (applied to annual income not exceeding 20,000 EUR), 23% (for annual income above 20,000 EUR and below 55,000 EUR) and 31.4% (applied to income exceeding 55,000 EUR per year).

Second, the maximum possible PIT allowance will be increased and the structure of the PIT allowance will be made more progressive. Latvia has a differentiated allowance since 2016, which means that individuals with lower incomes are eligible for a higher tax allowance. Figure 1 shows the changes in the non-taxable allowance that will be introduced by the reform. Another important change is that the differentiated allowance will be applied to the taxable income in the course of the year. The current system foresees that, during a calendar year, all wages are taxed applying the lowest possible allowance (60 EUR per month in 2017), but workers eligible for a higher allowance have to claim the overpaid tax in the beginning of the next year.

Figure 1. Basic PIT allowance before (2017) and after (2018-2020) the reform, EUR

Source: compiled by the authors.

Third, the rate of social insurance contributions will be increased by 1 percentage point. Social insurance contributions are capped and the cap will be increased from 48,600 EUR per year to 55,000 EUR per year, i.e. to the same income threshold that divides the top PIT bracket.

Finally, the reform will modify the solidarity tax – a tax, which was introduced in Latvia in 2016 and which is paid by top income earners. When this tax was initially introduced, one of its objectives was to eliminate the regressivity from the tax system caused by the cap on social insurance contributions. Hence, the rate of the solidarity tax was set at the same level as the rate of social insurance contributions and was effectively replacing social insurance contributions above the cap. The reform foresees that part of the revenues from the solidarity tax (10.5 percentage points) will be used to finance the top PIT rate. This element of the reform implies that after January 2018 those falling into the top PIT bracket will, in fact, not face a higher PIT rate than those falling into the second income bracket – the introduction of the top rate will be offset by the restructuring of the solidarity tax.

Results

There are four main findings. First, the reform will reduce the tax wedge on labor income, whereas the tax wedge on low wages will remain high by international standards. Second, most of the PIT taxable income earners (93.5%) will fall into the bottom income bracket. Hence the reform will effectively reduce the tax burden, while the effect on progressivity is very limited. Third, the (small) increase in tax progressivity is ensured mainly by changes in the tax allowance, while the effect of changes in the tax rate on progressivity is negligible: Even those few PIT payers that fall into the top tax bracket will not experience any increase in the tax burden due to a compensating change in the solidarity tax. Finally, it is mainly the households in the middle of the income distribution that will gain from the reform.

Effect on tax wedge

We start with a simple comparison of the average labor tax wedge in Latvia and other OECD countries for different wage levels before and after the reform. The tax wedge measures the share of total labor costs that is taxed away in the form of taxes or social contributions payable on employees’ income.

Table 1. Average tax wedge for single wage earners without dependents in Latvia and other OECD countries, before and after the reform

	67% of average worker’s wage	100% of average worker’s wage	167% of average worker’s wage
OECD average in 2016, % ^(a)	32.3	36.0	40.4
Latvia 2016, % ^(a)	41.8	42.6	43.3
Latvia’s rank in 2016* ^(a)	6	11	16
Latvia 2018, % ^(b)	39.4	42.3	42.6
Latvia 2019, % ^(b)	39.1	42.1	42.6
Latvia 2020, %^(b)	39.0	41.9	42.8

Source: (a) OECD and (b) authors’ calculations. Note: * Ranking across 35 OECD countries. Higher ranking implies higher tax wedge relative to other countries.

Table 1 shows that the tax wedge on low wages (67% of an average worker’s wage) in Latvia is pretty high. In 2016, it was the 6th highest across OECD countries, while the tax wedge on high incomes (167% of the wage) is much closer to the OECD average.

While the reform will slightly reduce the tax wedge for low wage earners (from 41.8% to 39.0% in 2020), it will still remain high by OECD standards. Despite an increase in PIT rate for high-income earners, the reform will also lower the tax wedge for those who earn 167% of the average wage. Why? The explanation comes from the income thresholds for the tax brackets. The income of those earning 167% of the average wage is estimated to fully fall into the first tax bracket in 2018–2019 and only slightly exceed the income bracket for the second PIT rate by 2020. This means that most of the incomes of people earning 167% of the average wage will be taxed at the rate of 20%, which is lower than the current flat rate of 23%. Moreover, in 2020, only a small share of their income will be taxed at 23% – the same rate that these individuals would have had faced in the absence of the reform. Hence, we observe a reduction in the tax wedge for high-income earners.

Generally, only a very small share of taxpayers will fall into the middle and the top income brackets. According to our estimations, as many as 93.5% of all PIT taxable income earners will fall into the lowest income bracket, and only about 6.5% will fall into the second income bracket and about 0.5% will face the top PIT rate.

Apart from the progressive PIT schedule, the reform envisages important changes in the solidarity tax. As explained above, part of the revenues from the solidarity tax will be used to finance the top PIT rate. Therefore, even those (very few) taxpayers whose income will exceed the threshold for the top PIT rate, will not experience any increase in the tax burden because of the compensating change in the solidarity tax. Therefore, the reform will effectively reduce the tax burden on labour with very little effect on progressivity.

While lowering the tax burden is generally welcome, the motivation for applying the top rate to such a small group of taxpayers is not clear. For example, in their recent in-depth analysis of the Latvian tax system, the World Bank (World Bank, 2016) came up with a tax reform proposal that envisaged a considerably lower threshold for the top PIT rate, which, according to our estimations, would cover about 12% of the taxpayers. Given the limited budget resources and an especially high tax wedge on low wages, a more targeted reduction in the tax burden would be preferable. Similar concerns about insufficient reduction in the tax burden on low-income earners are expressed in the latest OECD economic survey of Latvia (OECD, 2017).

Effect on income distribution

Below we present the results from the tax-benefit microsimulation model EUROMOD. Figure 2 shows the simulated change in equivalized disposable income by income deciles compared to the baseline “no-reform” scenario in 2018-2020.

Figure 2. Change in equivalized disposable income by income deciles caused by the reform compared to “no-reform” scenario, %

Source: authors’ calculations using EUROMOD-LV model

The first thing to note is that these are mainly households in the middle of the income distribution who will gain from the reform – their income will increase due to both the increase in non-taxable allowance and the introduction of the progressive rate.

The gain in the bottom of the income distribution is smaller for several reasons. First, the proportion of non-employed individuals (unemployed and non-active) is larger in the bottom deciles. Second, individuals with low wages are less likely to gain from the reduction in the tax rate and the increase in the basic allowance, since they might already have most of their income untaxed due to the currently effective basic allowance. The same applies to pensioners who have a higher basic allowance than the employed individuals and who are mainly concentrated in the bottom of income distribution.

Our results suggest that the wealthiest households will also see their incomes grow as a result of the reform (by about 1% in 10th decile). The growth is ensured by the fact that annual income below 20,000 EUR will be taxed at a reduced rate of 20%, and, taking into account that even in the top decile only about half of the individuals get income from employment that exceeds 20,000 EUR per year, the gain from the tax reduction is considerable even in the top decile. A reduction in the tax allowance for high-income earners will have a negative effect on wealthy individuals’ income, but this will be more than compensated by the above positive effect of the change in the tax rate. Hence, the net effect on the incomes in the top deciles is estimated to be positive.

Finally, Table 2 summarizes the effect of the reform on the income distribution, measured by the Gini coefficient on equivalized disposable income. On the whole, the reform is estimated to slightly reduce income inequality – in 2020, the Gini coefficient is expected to be 0.6 points lower than it would have been in the absence of the reform. This reduction is mainly driven by the changes in the non-taxable allowance, while the three PIT rates are estimated to have an increasing impact on income inequality.

Table 2. Gini coefficient on equivalized disposable income in the reform and “no-reform” scenario

	2018	2019	2020
“No-reform” scenario	35.2	35.4	35.7
Reform scenario	35.0	35.0	35.1

Source: authors’ calculations using EUROMOD-LV model

Conclusion

The 2018 tax reform was a long-awaited step from the Latvian authorities on the way to a more progressive tax system. The planned changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income-inequality.

At the same time, the second major aspect of the reform, the introduction of a progressive PIT rate, raises more questions than answers. The progressive rate, the way it is designed, will effectively lead to an across-the-board reduction of the tax burden on labor and will hardly help to reach the proclaimed objective of taxing incomes progressively. Given the limited budgetary resources and given that taxes on low wages will remain high compared to other countries even after the reform, a more targeted reduction of the taxes on low-income earners would have been a more preferred option.

References

OECD, 2017. “OECD Economic Surveys: Latvia 2017”, OECD Publishing, Paris. http://dx.doi.org/10.1787/eco_surveys-lva-2017-en
Sutherland, H. and Figari, F., 2013. “EUROMOD: the European Union tax-benefit microsimulation model”, International Journal of Microsimulation, 1(6), 4-26.
World Bank, 2016. “Latvia Tax Review”, available at http://fm.gov.lv/files/nodoklupolitika/Latvia%20Tax%20Review%20Draft%20231216%20D.pdf

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On Economics of Innovation Subsidies in Russia

Posted on October 9, 2017 | Policy Brief

Following the general agreement that innovation is a source of economic growth, the Russian government has provided various stimuli to foster domestic innovation. One of the mechanisms of innovation policy is research subsidies. This policy brief starts off with a discussion of the theoretical predictions and empirical evidence, which relates the economic incentives of research subsides to innovation and growth. We then address the potential adverse effects of focusing innovation subsidies mainly on large public companies in Russia. Finally, we attempt to establish a link between the innovation rate and market competition within Russian industries.

Overview

According to data from the Russian Statistical Agency, the R&D intensity – measured by R&D expenditure as percent of sales – increases with company size. Companies with 50 to 500 employees spend 1% of their sales on R&D, while the R&D intensity varies from 2 to 5% of sales for larger businesses (see Figure 1). The size non-neutrality of R&D in Russia contradicts the findings in the theoretical and empirical literature, which hold for companies in the developed countries (Cohen, 2010). An explanation may be the excessive government support to public companies in Russia, and in particular, to larger public corporations. A positive consequence of such policies is that public corporations come ahead of private companies, not only in R&D intensity, but also in innovation rates (see Figures 2–3).

However, government support towards innovation does not necessarily have a positive impact on overall economic activity. The purpose of this brief is to discuss the unwanted effects of the government policy in the form of research subsidies, both in theory and in an application to public companies and corporations in Russia. We base our analysis on the outcomes of the 2014–2017 micro surveys by the Analytical Center under the Government of the Russian Federation.

The role of government

Fighting under-provision of innovation

According to the seminal paradigm of the endogenous growth models with technological change, companies are engaged in quality competition, and their innovations are explained by a rational decision to raise profits through expanding the markets for existing products or entering markets for new products (Schumpeter, 1942; Romer, 1990; Grossman and Helpman, 1991; Kletter and Kortum, 2004). The innovation becomes one of the causes of economic growth, which is proved in empirical applications for developed countries, such as the U.S., Japan and the Netherlands (Akcigit and Kerr, 2010; Lentz and Mortensen, 2008; Grossman, 1990).

Figure 1. Innovation rate and R&D intensity by company size (number of employees)

Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.4, 2.16, Data for 2015. Innovative rate is % of companies involved in innovative activity.

However, the technological change is closely linked to knowledge disclosure, which means that new products become vulnerable to imitation, and that the non-rival character of knowledge causes an under-provision of innovation on the market (Arrow, 1962). The argument supports the cause for government policies through the system of intellectual property rights on the legal side, and research subsidies as an economic mechanism (Rockett, 2010; Hall and Lerner, 2010). Research subsidies are expected to have a positive effect on innovation rate, as is empirically shown for the U.S. in Acemoglu et al. (2016) and Wilson (2009). However, the impact on economic growth is ambiguous (Acemoglu et al., 2013; Grossman, 1990).

Figure 2. Innovation rate and R&D intensity by ownership

Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.6, 2.17, Data for 2015, public corporations are different from organizations by regional/federal government.

Figure 3. Share of public funds in R&D financing, % of company budget

Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.13; Innovation Development Programmes of Russian State-Owned Companies, Fig.4.

Unwanted effects of subsidies

Two concerns are associated with subsidization of innovation. First, while research subsidies may stimulate innovation among the targeted companies, the growth effect is likely to be heterogeneous across companies in the industry or economy, leading to a neutral or even negative overall effect. For instance, the increased innovation rate in subsidized large incumbents may curb entry of new (and more productive) firms, so the net outcome is deceleration of growth in the economy (Acemoglu et al., 2013). Research subsidies may even cause a shrinking of the high-tech sectors: if skilled labor moves from manufacturing to research labs, manufacturing may experience a shortage of labor, resulting in the net effect being a decrease in production (Grossman, 1990).

Another extreme of subsidizing entrants, in view of antitrust policies, occurs when former entrants change their market status to incumbents: now they face lower profits relative to newer entrants and hence, become less incentivized in their economic activity (Segal and Whinston, 2007).

Second, innovation policy (for instance, in the form of subsidies) may sometimes not even increase the innovation rate. Indeed, incumbents have no incentives to innovate in order to keep their market power or to prevent entry of higher quality firms in industries with non-perfect competition (Rockett, 2010; Qian, 2007).

Both mechanisms are likely to hold for Russian industries, where the protection of large public corporations has led to low competition, various forms of distortions on the market and hence, weak incentives to innovate.

Potential adverse effects in Russia

Large companies are likely to attract public attention owing to their obvious advantages in spreading fixed costs of innovations (Cohen,

2010). Russia is no exception to the phenomenon, so public corporations, which are commonly of a large size, received government subsidies. However, the subsidy is primarily used for acquiring new technologies and perfecting design, rather than conducting R&D (See Figure 4 with comparison available for communications and IT industry). The fact points to a possibility of a small effect of innovations on growth of public companies. Only if the research subsidy is spent on delegating the R&D research to specialized firms, with a subsequent acquiring of the resulting technology, the existing policy of supporting public corporations may induce their growth and/or growth of the corresponding industry.

Figure 4. Structure of spending the research subsidy in communications and IT in 2013, %

Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.134 Innovation Development Programmes of Russian State-Owned Companies, Fig.3.

In an attempt to formally assess the effect of innovation subsidies on company growth, we focus on the time profiles of the common proxies for company size: sales, profits and employment (Akcigit et al., 2017; Akcigit and Kerr, 2010; Acemoglu et al., 2013). The macroeconomic literature predicts that innovation becomes one of the channels for an increase of each of the three variables through a rise in quality. Motivated by this literature, the micro-data analysis “On the Interaction of the Elements of the Innovation Infrastructure”, conducted by the Analytical Center under the Government of the Russian Federation (2014), asked companies to assess their changes in sales, profits and employment in response to the innovation subsidy. As a result, the outcomes of the above analysis allow for a comparative assessment of the impact of the government’s innovation subsidy for public and private companies.

In particular, the results point to higher growth across private companies owing to research subsidies: the percent of private companies with new employees is higher than that of public companies. Similarly, the percentage of private companies that increased market share or raised profits/export due to subsidies exceed those of the public companies (see Figure 5). Here, we interpret new hires as employment growth and increase of market share as a potential indicator of sales growth.

Figure 5. Economic activity owing to research subsidies, % of companies

Source: Analytical Center under the Government of the Russian Federation, 2014. Fig.22

The innovation activity in private Russian companies lead to a higher prevalence of new products in comparison with public companies. The fact goes in line with a more important role of research and development in the innovative activity of private Russian companies (see Figure 4).

Finally, we attempt to establish a link between the innovation rate and market competition at the level of Russian industries. For this purpose, we use the results of the annual surveys “An assessment of the competitiveness in Russia”, conducted in 2015–2017 by the Analytical Center across 650–1500 companies from 84 Russian regions. The respondents were asked if they implemented R&D as a strategy for raising their competitiveness. We use the percentage of firms doing R&D as a proxy for the innovation rate. Competition in the industry was evaluated by respondents on a five-point scale (no competition, weak, median, high and very high), and we combine the prevalence of the two top categories as a proxy for competition in the industry.

Figure 6. Competition and R&D in Russian industries, % of firms

Source: Analytical Center under the Government of the Russian Federation, 2017, pp.8, 18.

The results show that innovative activity in the form of R&D or product modification is observed in industries with relatively high competition in Russia – for instance, in machinery and electric/electronic equipment (Figure 6). At the same time, industries where competition is not as high (e.g. woodworking, construction) show absence of either type of innovation. The findings go in line with the economic theory about market competition being a prerequisite for the rational choice of companies about innovation. Moreover, if the purpose of government subsidies is to foster innovation, the effective allocation of subsidies would imply the focus on Russian industries with high competition – here various forms of innovation do play a role in the company strategy on the market.

Conclusion

Our analysis outlines the theoretical foundations for the potential adverse effects of innovation policies in the form of research subsidies. The unwanted outcomes may relate to heterogeneity of companies and absence of the association between innovation activity and growth on non-competitive markets.

We offer the empirical evidence, which points to the undesired effects of subsidizing public companies in Russia. For instance, compared to the overall Russian sector of communications and IT, the innovative activity in public corporations has a weaker association with research and development. Additionally, compared to private companies, the innovations may result in smaller prevalence of increased exports, profits or new hires, as well as in a less frequent development of new products by public companies in Russia.

References

Acemoglu, D., Akcigit, U., Bloom, N., Kerr, W. R., 2013. “Innovation, reallocation and growth”, National Bureau of Economic Research Working paper, No. 18993.
Acemoglu, D., Akcigit, U., Hanley, D., Kerr, W. (2016). Transition to clean technology. Journal of Political Economy, Volume 124(1), pages 52-104.
Akcigit, U., Kerr, W. R., 2010. “Growth through heterogeneous innovations” National Bureau of Economic Research Working Paper, No. 16443.
Analytical Center under the Government of the Russian Federation, 2014. “On the Interaction of the Elements of the Innovation Infrastructure”, Analytical report, in Russian.
Analytical Center under the Government of the Russian Federation, 2015-2017. “An Assessment of the Competitiveness in Russia”, Analytical reports, in Russian.
Arrow, K., 1962. “Economic welfare and the allocation of resources for invention”, In The Rate and Direction of Inventive Activity: Economic and Ssocial Factors, Princeton University Press, pages 609-626.
Cohen, W. M., 2010. “Fifty years of empirical studies of innovative activity and performance”, Handbook of the Economics of Innovation, Volume 1, pages 129-213.
Grossman, G. M., Helpman, E., 1991. “Quality ladders in the theory of growth”, The Review of Economic Studies, Volume 58(1), pages 43-61.
Grossman, G.M., 1990. ”Explaining Japan’s innovation and trade”, BOJ Monetary and Economic Studies, Volume 8(2), pages 75-100.
Hall, B. H., Lerner, J., 2010. “The financing of R&D and innovation”, Handbook of the Economics of Innovation, Volume 1, pages 609-639.
Indicators of Innovation in the Russian Federation: 2017. N. Gorodnikova, L. Gokhberg, K. Ditkovskiy et al.; National Research University Higher School of Economics, in Russian.
Innovation Development Programmes of Russian State-Owned Companies: Interim Results and Priorities, 2015. M. Gershman, T. Zinina, M. Romanov et al.; L. Gokhberg, A. Klepach, P. Rudnik et al. (eds.), National Research University Higher School of Economics, in Russian.
Klette, T. J., Kortum, S., 2004. “Innovating firms and aggregate innovation”, Journal of Political Economy, Volume 112(5), pages 986-1018.
Lentz, R., Mortensen, D.T., 2008. “An empirical model of growth through product innovation”, Econometrica, Volume 76(6), pages 1317–1373.
Qian, Y., 2007. “Do national patent laws stimulate domestic innovation in a global patenting environment? A cross-country analysis of pharmaceutical patent protection, 1978–2002”, The Review of Economics and Statistics, Volume 89(3), pages 436-453.
Rockett, K., 2010. “Property rights and invention”, Handbook of the Economics of Innovation, Volume 1, pages 315-380.
Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.
Segal, I., Whinston, M.D., 2007. “Antitrust in innovative industries”, American Economic Review, Volume 97(5), pages 1703-1730.
Schumpeter, J., 1942. “Creative destruction”, Capitalism, Socialism and Democracy, pages 82-83.
Wilson, D. J., 2009. Beggar thy neighbor? The in-state, out-of-state, and aggregate effects of R&D tax credits. The Review of Economics and Statistics, Volume 91(2), pages 431-436.

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Fiscal Redistribution in Belarus: What Works and What Doesn’t?

Posted on September 30, 2017 | Policy Brief

Belarus proudly calls itself a social state. Indeed, Belarus boasts one of the lowest poverty and inequality levels in the region. Fiscal policy in Belarus is equalizing and pro-poor, effectively redistributing income from rich to poor. As in Russia and many other Post-Soviet states, the equalizing effect of the fiscal policy in Belarus is mostly attributable to the pension system. Some of the other social policies are highly inefficient, failing to redistribute income. The prominent examples are utility subsidies and student stipends, which mainly benefit the upper part of the income distribution. The lack of adequate unemployment benefits is an opportunity to improve the efficiency of the social support system in Belarus.

The Constitution of Belarus characterizes Belarus as a social state, and Belarus takes its social state status seriously. The economic growth in the beginning of the 2000’s was strongly pro-poor (Chubrik, 2007). Poverty according to the national definition (calorie-based poverty line, which in 2015 corresponded to $10.67 PPP per day) declined from 42% in 2000 to 5.7% in 2016, while the poverty according to the international threshold of $3.1 per day in PPP terms is fully eradicated. Belarus also has one of the lowest levels of income inequality in the region with a Gini coefficient of only 0.27 (UNDP, 2016).

How much of the pro-poor and equalizing effects could be attributed to the government policy? Probably it is impossible to give a complete answer to the question. Many non-formalized and not easily quantifiable government policies lead to the decrease in poverty and inequality. For example, the policy of support to state-owned enterprises might have redistributive effects through job creation. However, the absence of access to relevant data makes it impossible to estimate the effects of the policy.

Some of the government policies, on the other hand, are easily quantifiable with available data. Bornukova, Chubrik and Shymanovich (2017) analyze the redistributive effects of fiscal policies in Belarus using the Commitment to Equity methodology (Lustig, 2016). The authors find that the direct taxes and transfers in Belarus (taxes, transfers, and subsidies) are equalizing and pro-poor, lowering the national poverty headcount by 17 percentage points and the income Gini coefficient from 0.41 to 0.27. The high equalizing effect of the fiscal policies in Belarus surpasses those in other developing countries, including Russia where the direct taxes and subsidies reduced the income Gini coefficient by 0.13 (Lopez-Calva et al., 2017). The remaining discussion in this brief is based on the results from Bornukova, Chubrik and Shymanovich (2017), if not otherwise stated.

Fiscal policies and their redistributive effects

Taxation

The two types of direct personal taxes – the personal income tax and the social contributions tax – are both almost flat in Belarus. To fight tax evasion, the Belarusian authorities introduced flat tax rates in 2009, following a successful experiment in Russia. The personal income tax has some small exemptions for families with children, while the social contributions tax has a lower rate for agriculture employees. However, the effect of these deductions is relatively small: the direct taxes decrease the Gini coefficient by only 0.015.

The indirect taxes – the value-added tax, the import duties, and the excises – are weakly regressive, putting the burden of taxation on the poor. This is particularly true for the alcohol and tobacco excises. Again, the main purpose of these taxes is to penalize unwelcome behavior, and not to redistribute income, hence the result is not unexpected, and common for many countries. Overall the indirect taxes in Belarus increase the Gini coefficient by 0.05.

Direct transfers

Direct transfers are responsible for most of the equalizing effects of the fiscal policies. This is not surprising, given that the main purpose of the direct transfers is to fight poverty and provide support for those in need. However, most of the transfers are not need-based or targeted to the poor. Instead they are assigned to households based on their socio-economic characteristics aside income, such as age and maternity status.

Pensions are the main factor of reducing poverty and inequality. They reduced the Gini coefficient by 0.11 and decreased poverty (according to national definition) by 19 percentage points. The incredible effectiveness of the pensions is largely explained by the absence of other sources of income of the retirees. The majority of them does not work, and have no other pension savings or passive income. Pensions in Belarus are also redistributive in nature since they only weakly depend on one’s income during the working life.

Different benefits and privileges also decrease poverty and inequality, but at a much smaller scale. The childcare benefits (for families with children aged 0-3 years) contribute most to the effects, decreasing the Gini coefficient by 0.013 and poverty by 3 percentage points. The variety of privileges does not contribute much due to their relatively small size.

Subsidies

Utilities and transport subsidies are also important elements of the social support system, and their existence is usually justified by the necessity to support those in need. Since the utilities subsidies are incorporated into tariffs and available for everyone independent of need, they are in fact benefitting the rich (i.e. people with big apartments and houses).

Figure 1. Incidence of utilities subsidies by income deciles

Source: Bornukova, Chubrik and Shymanovich, 2017

As seen on Figure 1, upper deciles receive more support through utilities subsidies, and this support is quite substantial, often surpassing $1 per day in PPP. However, as a share of income the utilities subsidies are still progressive, and they in fact decrease the Gini coefficient by the tiny amount of 0.006, and decrease poverty (as any handout). The same is true for transport subsidies.

What could be improved?

Due to the flat nature of direct taxation and an absence of well-targeted needs-based transfers, some of the people in need still fall through the cracks. 1.9% of the population actually becomes poor after we account for the direct taxes and transfers. This headcount increases to 3.3% if we account for indirect taxes.

Another important issue is the efficiency of government transfers and subsidies in fighting poverty and inequality. It is not surprising that pensions have the largest equalizing contribution, as the government spends almost 11% of GDP on pensions. If we account for this fact and look at the efficiency (effect on poverty and inequality per dollar spent), pensions are not the leading program. It is in fact surpassed by different kinds of child support. Given that mothers in Belarus are allowed to take 3 years of unpaid maternity leave, which decreases household income, childcare benefits are relatively efficient.

The unexpected leader in efficiency is unemployment benefits, despite (or maybe due to) their negligible size. Shymanovich (2017) shows that unemployed face high risks of poverty, suggesting that an increase in the size of unemployment benefits and an easier access may bring huge benefits. The current minuscule size of the benefits (around $10-15 per month) is still enough to lift some people out of poverty, and has important equalizing effects, generating the biggest “bang for the buck” out of all benefits.

The student grants (stipends), the utilities subsidy and the transport subsidy have very low efficiency. These programs relocate a lot of funds to the upper deciles of the income distribution. Our calculations show that if all benefits, privileges and subsidies were not available to those in the top two income deciles, the Belarusian budget could save 1.4% of GDP.

Conclusion

Fiscal policies in Belarus are quite effective in redistributing income. Bornukova, Chubrik and Shymanovich (2017) show that the direct taxes and transfers in Belarus result in a decrease of poverty by 17 percentage points, and decrease the Gini coefficient of inequality from 0.41 to 0.27. The pension system has the most important contribution, decreasing poverty by 19 percentage points, and the Gini coefficient by 0.11.

However, the absence of a needs-based, well-targeted social support system leads to many inefficiencies. Direct and indirect taxes lead to impoverishment of 3.3% of population, which is not compensated by direct transfers.

The absence of targeting also leads to 1.4% of GDP redistributed towards the two upper income deciles through benefits, privileges and subsidies. This is, of course, highly inefficient. Better targeting could allow saving these funds or redirecting them to unemployment benefits – the most efficient but a very small benefits program so far.

References

Bornukova, Kateryna, Alexander Chubrik and Gleb Shymanovich, 2017. “Fiscal Incidence in Belarus: a Commitment to Equity Analysis”, BEROC Working Paper Series, WP no. 42
Chubrik, Alexander, 2007. “GDP Growth and Income Dynamics: Who Reaps the Benefits of Economic Growth in Belarus?” In Haiduk, K., Pelipas, I., Chubrik, A. (Eds.) Growth for All? Economy of Belarus: The Challenges Ahead; IPM research Center
Lopez-Calva, L. F., Lustig, N., Matytsin, M., Popova, D., 2017. “Who Benefits from Fiscal Redistribution in Russia?”,in The Distributional Impact of Fiscal Policy: Experience from Developing Countries, edited by Gabriela Inchauste and Nora Lustig (Washington: World Bank, forthcoming).
Gleb Shymanovich, 2017. “Poverty and Vulnerable Groups in Belarus: The Consequences of 2015-2016 Recession (in Russian)”, IPM Research Center Bulletin
UNDP, 2016. “Regional Human Development Report 2016: Progress at Risk”, United Nations Development Programme, Istanbul Regional Hub, Regional Bureau for Europe and the CIS

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Financing for Development: Two Years after Addis

Posted on June 12, 2017 | Policy Brief

At the Third International Conference on Development Finance in Addis Ababa on July 13—16, 2015, the world committed itself to an action agenda to raise resources to realize the 2030 sustainable development goals. The question is how much progress the world has achieved two years down the road, when the initial enthusiasm and commitments are no longer in the immediate spotlight. This policy brief reports on the discussion from a conference on this topic, Development Day 2017, held in Stockholm on May 31.

The year 2015 has been lauded as a landmark year for sustainable development. As many as three major global agreements were negotiated and signed: the 2030 Agenda for Sustainable Development; the Paris Agreement on Climate Change; and the Addis Ababa Action Agenda (AAAA) on Financing for Development. The latter may be less known, but is essential to the ambition to achieve the first since it concerns how to finance the necessary investments to achieve the Sustainable Development Goals (SDG). The AAAA identified seven action areas spanning both the public and the private sectors, and involving both domestic revenues and international transfers (domestic public resources, domestic and international private business and finance, development cooperation, trade, debt and debt sustainability, systemic issues and science, technology and innovation). This event focused primarily on international commercial private capital flows, and indirectly on development cooperation as a facilitator and catalyst for such private transfers.

Combining good business and good development

A major theme of the conference was combining good business with good development. Should private companies also take responsibility for environmental and social sustainability, or is the “only business of business to do business”? If firms do engage in sustainability investments, does it eat into profits or does it rather create a competitive edge? Reading business journals, it is easy to get the impression that there is a win-win situation. This picture is, however, based on rather limited information and the relationship is fraught with methodological challenges as both profitability and sustainability investments may be driven by other factors (such as competent leadership), and firms performing well may have the capacity and feel the obligation to invest part of their surplus into corporate social responsibility (CSR). Hence, there may be a question of reverse causality.

At the conference, new research was presented using data on investments in low and middle-income countries from the International Finance Corporation that includes both measures of financial rates of returns and subjective ratings of environment, social and governance (ESG) performance. Simple correlations suggested a significant positive relationship, or a win-win situation. However, once care was taken to identify a causal effect from ESG on profits, the results became insignificant. That is, the causal effect of ESG investments on profits seemed neither positive nor negative. However, when looking at broader measures of private sector development, the results suggest that both profits and ESG investments have a positive impact on sector development. This implies that there are good reasons for the public sector to encourage ESG activities even beyond the direct sustainability benefits through for instance public-private partnerships but also regulations that encourage good behavior.

How should results like these be interpreted? The presentation spurred an interesting debate on what are reasonable expectations and whether “the glass is half full or half empty”. It was emphasized that systematically beating the market should not really be expected from any group of investments, so a half-full interpretation seems more plausible.

This debate also came up in a panel discussion on institutional investments in developing countries, and where the growing success of green bonds was presented. Though still small in absolute size (1-2% of the bonds coming to the market are green bonds), there has been an impressive growth in the last 3-4 years. Currently, the Swedish bank SEB is cooperating with the German government in developing a green-bond market in emerging markets. Some of the lessons emphasized from the green-bond market were the importance of being clear towards investors about the motivation and the value proposition, to package the information in a credible way emphasizing independent verification, and to continuously monitor and give feedback to investors.

From the institutional investor side, it was mentioned how important it is to tell investors a compelling story. This may be easier with regards to environmental sustainability relative to social sustainability, both in terms of conveying the urgency and in developing indicators that can be monitored and communicated. It was also argued that even though there are initiatives out there, emphasizing how sustainable investments can be competitive in terms of profitability (such as green bonds), it would also help to change the relative price on the other end of the spectrum, i.e. through regulations, taxes or other instruments that can make investments with particularly negative externalities less profitable.

Finally, an overarching theme of the discussion was the challenge to have institutional investments reach the places with the most needs, i.e. the fragile and least developed countries. If this is to happen, pension funds and insurance companies have to be allowed to take on more risks, and it would be essential to reduce the corporate risk in public-private partnerships (more on this below).

In a second panel discussion, different Swedish corporate initiatives, emphasizing sustainability, were showcased. For example, the Swedish steel producers’ association, Jernkontoret, showcased the Swedish steel industry’s vision 2050 with the target of domestically based steel production using hydrogen and with zero CO2 emissions. Another example is the Sweden Textile Water Initiative, launched in 2010 by major Swedish textile and leather brands together with the Stockholm International Water Institute, has created the first guidelines for sustainable water and wastewater management in supply chains. Currently working with 277 suppliers in 5 countries, the initiative features clear win-win situations and is now self-sustaining and in the process of going private.

Skandia, a major Swedish insurance company, emphasized the business costs of socially unsustainable situations with examples from the costs in Sweden of sick leave, and the costs for protection and security for Swedish retailers and mall developers. Positive preventive work focusing on rehabilitation and the development of blossoming and inclusive neighborhoods were featured. These examples showcased how the SDGs are feeding into the thinking and planning of the private sector in Sweden, and how important it is to identify the business cases for thinking about sustainability in order for this to become mainstream.

However, the case for private capital to be the panacea for reaching the SDGs is by no means obvious. The non-governmental organization Diakonia pointed out that for every dollar flowing into a developing country, more than two dollars are lost. The biggest loss is coming from illicit financial flows, and within this category, tax evasion is the biggest problem. While the private sector is key to development, the main contributions this sector can do for development is to pay taxes where they are due, abide by international standards, and be transparent and accountable to the citizens and governments in the countries where they operate.

Swedwatch, used two examples from Borneo and what is now South Sudan, to illustrate how investors at times turn a blind eye towards human rights and environmental abuses by private multi-national companies. Transparency, due diligence in evaluating human rights risks prior to investment decisions, and a readiness to push for compensation and remedy if abuse is still unearthed were pointed out as key components to avoid this type of malpractice.

Development cooperation as facilitator for private flows

The second main theme of the day dealt with the ability to use development cooperation as a catalyst for private investments.

Swedfund, the Swedish government’s development financier, emphasized the need to move fast and find a business model in which one dollar spent becomes ten dollars on the ground. Based on a business model around three pillars (societal impact, sustainability and financial viability) Swedfund focus on areas with relatively high risk and where private capital are in short supply, with the hope to foster job creation, inclusive growth and poverty reduction.

Sida, the Swedish main aid agency, showcased their guarantee instruments. Through partnerships with bigger actors such as the International Finance Corporation (IFC) of the World Bank group as well as local banks in developing countries, Sida can shoulder part of the default risks involved when trying to reach more high-risk investors (such as small and medium sized enterprises) with great potential development impact. In this way, one dollar from the public aid budget can lure a multiple of dollars in private capital towards sustainable development.

The OECD Development Assistance Committee (DAC) emphasized that governments generally lack a policy for how to deliver official development assistance (ODA) in a sustainable way and a strategy for how to enable capital flows from the private sector. A DAC initiative to better track all financial flows going towards development, beyond just ODA, was presented.

From the Center for Global Development, the case for using public resources to facilitate private sector insurance mechanisms against human disasters was presented (concessional insurance). Benefits emphasized from explicit insurance contracts included faster and better-coordinated payouts, more certainty that compensation will come, incentives to invest in disaster prevention (to reduce premiums) and involvement of commercial insurance professionals.

Importantly, though, it was emphasized that it is crucial that aid money are truly complementary in the sense that they crowd in private investments that otherwise would not have taken place (and not end up subsidizing private investors in donor countries). It was also emphasized that donors must not forget about the focus on the poorest and people in fragile states.

In some environments donors must shoulder 100% of the risk to lure private capital. In those cases alternatives must be considered. Sida emphasized the importance to match financial instruments with the appropriate context, i.e. there is a need to identify where different instruments should be used. For instance, big institutional investors need investments that are manageable, predictable, and of a reasonable size. Aid agencies can help through subsidized risk management, but also by helping build strong institutions in partner countries that can work as counterparts, and encourage public-private collaborations to package investment deals and reduce information asymmetries.

Where are we now?

Turns out that this is not a simple question to answer. The Ministry for Foreign Affairs presented the Swedish government’s priority areas – strengthening the implementation of SDG 5, 8, 14 and 16 (all goals can be found here: https://sustainabledevelopment.un.org/?menu=1300) – and reported from a recent follow-up meeting at the UN.

In principle the Addis Agenda identifies action areas and connects areas and actors, which makes it possible for systematic follow-ups, and an inter-agency task force produces an annual report of the general state of the implementation of the Addis Agenda. The Swedish government has produced a report on the implementation of the AAAA covering all seven action-areas with examples of progress. This initiative was commended at the UN meetings, and together with the private sector engagement, as showcased during the 2017 Development Day, it paints a rather positive picture of progress and engagement in Sweden.

However, globally, there are many uncertainties and challenges. The Center for Global Development reported on the budget proposal of the US president, which among other things includes a 32% cut to topline funding for the Department of State and Foreign Operations. There are also plans to eliminate the Overseas Private Investment Corporation and to zero out US food assistance. On the other hand, in this fiscal year, the US Congress (controlled by the Republicans) increased the amount going into foreign aid compared to what previous president Obama suggested. What will eventually come out of the current president’s budget proposal for the coming fiscal year is thus highly unclear.

Participants at the conference

Rami AbdelRahman, Sweden Textile Water Initiative
Frida Arounsavath, Swedwatch
Owen Barder, Center for Global Development
Eva Blixt, Jernkontoret
Magnus Cedergren, Sida
Penny Davies, Diakonia
Raj Desai, Georgetown University and the Brookings Institution
Ulf Erlandsson, Fourth Swedish National Pension Fund (AP4)
Måns Fellesson, Ministry for Foreign Affairs
Charlotte Petri Gornitzka, OECD-DAC
Anna Hammargren, Ministry for Foreign Affairs
John Hurley, Center for Global Development
Lena Hök, Skandia
Måns Nilsson, Stockholm Environmental Institute
Mats Olausson, SEB
Anders Olofsgård, SITE
Anna Ryott, Swedfund
Elina Scheja, Sida

Monetary Policy Puzzle in the Presence of a Negative TFP Shock and Unstable Expectations

Posted on May 29, 2017 | Policy Brief

20170528 FREE Policy Brief - Monetary Policy Puzzle Image 01

The Belarusian economy has given birth to a very interesting phenomenon of extremely high real interest rates in a prolonged recession. Despite an expected intuitive guess about the linkage between them (high interest rates cause recession), the reality turned out to be more difficult. The era of high real interest rates was due to past mistakes in economic policy, which undermined the credibility of the latter and gave rise to high and volatile inflation expectations. However, the adverse output path following the too high interest rates was not essential. The recession was mainly predetermined by a negative Total Factor Productivity (TFP) shock. The shock itself forms a disagreeable and contradictive environment for monetary policy. Together with unanchored inflation expectations, this makes monetary policy ineffective and too risky.

Unusually high real rates and recession

Since the painful currency crisis of 2011, the Belarusian monetary environment has become extremely vulnerable in many respects. In 2011 and early 2012, the country faced (once again) a 3-digit inflation rate. While the inflation rate later went down gradually, it was not sufficient to enhance monetary stability in a broader sense. For instance, for nominal interest rates, the level of 20% per annum was an unachievable lower bound until 2016. Moreover, in 2013—2016, upside jumps in the nominal interest rates took place regularly (see Figure 1).

Figure 1.Nominal interest and inflation rates, % per annum

Source: Belstat. Note: Inflation rate is calculated on average basis for last three months on a seasonally adjusted basis and then annualized

Such combination of nominal interest and inflation rates has resulted in an extremely high and volatile level of real interest rates throughout the last 4 years. Real returns at the Belarusian financial market fluctuated in 2013—2016 within the range of 10-30% per annum. For instance, a median (monthly) value of the real interest rate on new loans in 2013—2016 was 17.6% per annum (in the beginning of 2017 it approached the level of 8-10% per annum). So, one may say that the real monetary conditions have been extremely tight in the last couple of years.

At the same time, in 2015—2016 Belarus has dipped into a prolonged and deep recession. During the last two years, the country has lost roughly 7% of its output. The combination of high real interest rates and a recession gave rise to a naive, but acceptable diagnosis: the excessively high interest rates caused (or at least contributed to) the recession. This view became popular in the domestic policy discussions. Furthermore, often this story transformed into a claim that ‘too tight monetary policy causes (or at least contributes to) recession’. Given this pressure, the National bank of Belarus (NBB) became accustomed to justifying its policy stance by considerations of financial stability given financial fragility. So, the economic policy discussion got into the discourse of these two extremes. Finally, it boiled down to the question whether ‘the monetary environment has stabilized enough in order to soften monetary policy’.

However, a naive story about the stance of monetary policy and the business cycle is not (fully) true in the case of Belarus in several respects.

Unanchored expectations drive interest rates

First, high interest rates at the financial market were not because of the excessively high policy rate of the NBB. It happened due to volatile, but still persistently high inflation expectations (Kruk 2017, 2016a). The latter visualized the loss of monetary-policy credibility by the general public.

Before 2016, the level of inflation expectations was persistently higher than the actual inflation, demonstrating an extremely slow (if any) convergence (see Figure 2). At the same time, the ex-ante level of real returns has remained relatively stable. When setting its policy rate, the NBB has taken into consideration existing inflation expectations, otherwise the high expected inflation would have been realized.

Figure 2. Actual and expected inflation, %

Note: Expected inflation has been estimated according to the methodology in Kruk (2016a).

So, in the recent past, the stance of the monetary policy could hardly be accused of generating too tight monetary conditions through the setting of an improper policy rate. The problem was (is) more severe, and one can argue about the inability (and the lack of willingness) of the NBB to anchor inflation expectations.

However, in the late 2016 and early 2017, the expected and actual inflation rates converged, mainly due to a contraction of the former. This introduced more stability into the monetary environment, in a broader sense. Kruk (2017, 2016a) shows that the turn of 2016—2017 has become a breakpoint for the monetary environment to return into a ‘normal’ stance (see Figure 3).

The NBB reacted to the milder monetary environment by a number of reductions in the policy rate (from 18% since August 2016 down to 14% since April 2017). However, a shift of both expected and actual inflation into the range between 5% and 9% may be interpreted as there being room for further reductions.

Figure 3. Classification of monetary environment stance in Belarus, probability estimates

Note: Classification and the methodology for estimates are based on Kruk (2016a). ‘Normal’ regime is characterized by reasonable and relatively stable real interest rates; ‘subnormal’ – too high real interest rate due to ‘inflation expectations premium’; ‘abnormal’ extremely volatile and mainly huge negative real interest rates due to the swings of actual inflation.

Therefore, as of today, one may argue that the long-expected time for a softening of the monetary policy has come, as the ‘expectations overhang’ has disappeared. However, such a view might be too optimistic. Kruk (2017) argues that the convergence of expected and actual inflation rates might be a temporary lucky combination, as there is a lack of evidence supporting a growing credibility of monetary policy among the general public. On the contrary, inflation expectations seem to have shrunk due to a depressed domestic demand and lower consumer confidence. So, even if expectations have contracted, they have not been anchored. Hence, ‘the expectations overhang’ may resurge at any time.

Monetary softening cannot neutralize structural recession

Even if we assume that the ‘expectations overhang’ has disappeared, it would still not mean that there is room for a new monetary stimuli. A naive story about high real interest rates that cause recession glitches once again when interpreting this linkage. Most frequently, countries face a cyclical recession (i.e. caused by temporary demand fluctuations). If that is the case, a negative impact of excessively high interest rates on output path is taken for granted.

However, the Belarusian story of recession is different. Kruk and Bornukova (2014) have shown that the country faced a negative TFP shock, which determined the weakening of the long-term growth rate. Kruk (2016b) shows that due to this shock, the long-term growth rate crossed the zero level approximately at the turn of 2014—2015, and dipped into a negative range later on. Hence, the Belarusian recession that started in 2015 was a combination of a negative contribution from both the long-term dynamics and the business cycle. Furthermore, since the second half of 2016, the negative contribution of the business cycle has faded out, and the recession was determined by the negative TFP shock almost solely (Kruk, 2017) so that, by 2017, the recession has become a purely structural phenomena.

From a monetary policy stance, this gives rise to a new challenge. Although the majority of methodologies still assess the output gap to be negative (but not far away from zero), the output gap will soon be closed automatically because of continuing negative TFP shocks (Kruk, 2017). In a sense, the negative TFP shock contributes to the closing of the output gap in the same way as monetary policy does. However, it does this job in an opposite manner (i.e. by squeezing the trend growth, and not by stimulating the business cycle), it leaves almost no room for monetary policy. It creates a situation where a reasonable loosening of the monetary policy may immediately turn into an excessive one. Taking into account that the dormant inflation expectations can resurge, monetary policy decisions resembles walking on the edge.

Conclusions

Today’s policy discussion in Belarus is extensively concentrated around the search for the best monetary policy to fight the recession. However, this formulation of the problem is a mistake in itself. Today’s contradictions in monetary policy are simply a reflection of the bulk of accumulated structural weaknesses in the economy. Today, monetary policy can hardly do anything to stabilize output. The solutions for ending the recession, and enhancing growth should be found in structural policies, not in the sphere of monetary policy. As for monetary policy, it can, at this moment, hardly contribute to output stabilization (without challenging price stability). To do so, it has to ensure an anchoring of the inflation expectations first.

References

Kruk, D. (2017). Monetary Policy and Financial Stability in Belarus: Current Stance, Challenges, and Perspectives (in Russian), BEROC Policy Paper Series, PP No.43.
Kruk, D. (2016a). SVAR Approach for Extracting Inflation Expectations Given Severe Mnonetary Shocks: Evidence from Belarus, BEROC Working Paper Series, WP No. 39
Kruk, D. (2016b). The Reasons and Characteristics of Recessiion in Belarus: the Role of Structural Factors (in Russian), BEROC Policy Paper Series, PP No. 42.
Kruk, D., Bornukova,K. (2014). Belarusian Economic Growth Decomposition, BEROC Working Paper Series, WP no. 24.

“New Goods” Trade in the Baltics

Posted on May 22, 2017 | Policy Brief

We analyze the role of the new goods margin—those goods that initially account for very small volumes of trade—in the Baltic states’ trade growth during the 1995-2008 period. We find that, on average, the basket of goods that in 1995 accounted for 10% of total Baltic exports and imports to their main trade partners, represented nearly 50% and 25% of total exports and imports in 2008, respectively. Moreover, we find that the share of Baltic new-goods exports outpaced that of other transition economies of Central and Eastern Europe. As the International Trade literature has recently shown, these increases in newly-traded goods could in turn have significant implications in terms of welfare and productivity gains within the Baltic economies.

New EU members, new trade opportunities

The Eastern enlargements of the European Union (EU) that have taken place since 2004 included the liberalization of trade as one of their main pillars and consequently provided new opportunities for the expansion of trade among the new and old members. Growth in trade following trade liberalization episodes such as the ones contemplated in the recent EU expansions could occur because of two reasons. First, because countries export and import more of the goods that they had already been trading. Alternatively, trade liberalization could promote the exchange of goods that had previously not been traded. The latter alternative is usually referred to as increases in the extensive margin of trade, or the new goods margin.

The new goods margin has been receiving a considerable amount of attention in the International Trade literature. For example, Broda and Weinstein (2006) estimate the value to American consumers derived from the growth in the variety of import products between 1972 and 2001 to be as large as 2.6% of GDP, while Chen and Hong (2012) find a figure of 4.9% of GDP for the Chinese case between 1997 and 2008. Similarly, Feenstra and Kee (2008) find that, in a sample of 44 countries, the total increase in export variety is associated with an average 3.3% productivity gain per year for exporters over the 1980–2000 period. This suggests that the new goods margin has significant implications in terms of both welfare and productivity.

In a forthcoming article (Cho and Díaz, in press) we study the patterns of the new goods margin for the three Baltic states: Estonia, Latvia and Lithuania. We investigate whether the period of rapid trade expansion experienced by these countries after gaining independence in 1991—average exports grew by more than 700% between 1995 and 2008 in nominal terms, and average imports by more than 800%—also coincided with increases in newly-traded goods by quantifying the relative importance of the new goods margin between 1995 and 2008. This policy brief summarizes our results.

Why focus on the Baltics?

The Baltic economies present an interesting case for a series of reasons. First, along a number of dimensions, the Baltic countries stood out as leaders among the formerly centrally-planned economies in implementing market- and trade-liberalization reforms. Indeed, those are the kind of structural changes that Kehoe and Ruhl (2013) identify as the main drivers of extensive margin increases. Second, unlike other transition economies, as part of the Soviet Union the Baltics lacked any degree of autonomy. Thus, upon independence, they faced a vast array of challenges, among them the difficult task of establishing trade relationships with the rest of the world, which prior to 1991 were determined solely from Moscow. Lastly, as former Soviet republics, the Baltic states had sizable portions of ethnic Russian-speaking population, most of which remained in the Baltics even after their independence. At least in principle, this gave the Baltic economies a unique potential to better tap into the Russian market.

Defining “new goods”

We use bilateral merchandise trade data for Estonia, Latvia and Lithuania starting in 1995 and ending in 2008, the year before the Global Financial Crisis (GFC). The data are taken from the World Bank’s World Integrated Trade Solution database. The trade data are disaggregated at the 5-digit level of the SITC Revision 2 code, which implies that our analysis deals with 1,836 different goods.

To construct a measure of the new goods margin, we follow the methodology laid out in Kehoe and Ruhl (2013). First, for each good we compute the average export and import value during the first three years in the sample (in our case, 1995 to 1997), to avoid any distortions that could arise from our choice of the initial year. Next, goods are sorted in ascending order according to the three-year average. Finally, the cumulative value of the ranked goods is grouped into 10 brackets, each containing 10% of total trade. The basket of goods in the bottom decile is labeled as the “new” goods or “least-traded” goods, since it contains goods that initially recorded zero trade, as well as goods that were traded in positive—but low—volumes. We then trace the evolution of the trade value of the goods in the bottom decile, which represents the growth of trade in least-traded goods.

Findings

For ease of exposition, we present the results for the average Baltic exports and imports of least-traded goods, rather than the trade flows for each country. Results for each individual country can be found in Cho and Díaz (in press). We report the least-traded exports and imports to and from the Baltics’ main trade partners: the EU15, composed of the 15-country bloc that constituted the EU prior to the 2004 expansion; Germany, which within the EU15 stands out as the main trade partner of Latvia and Lithuania; the “Nordics”, a group that combines Finland and Sweden, Estonia’s largest trade partners; and Russia, because of its historical ties with the Baltic states and its relative importance in their total trade.

Least-traded exports

Figure 1 shows the evolution over time of the share in total exports of the goods that were initially labeled as “new goods”, i.e., those products that accounted for 10% of total trade in 1995. We find that the Baltic states were able to increase their least-traded exports significantly, and by 2008 such exports accounted for nearly 40% of total exports to the EU15, and close to 53%, 49% and 49% of total exports to Germany, the Nordic countries, and Russia, respectively. Moreover, we find that the fastest growth in least-traded exports to the EU15 and its individual members coincided with the periods when the Association Agreements and accession to the EU took place. Finally, we discover that the rapid increase in least-traded exports to the EU15 during the late 1990s and early 2000s is accompanied by a stagnation of least-traded exports to Russia. This suggest that, as the Baltics received preferential treatment from the EU, they expanded their export variety mix in that market at the expense of the Russian. Growth in least-traded exports to Russia only resumed in the mid 2000s, when the Baltics became EU members and were granted the same preferential treatment in the Russian market that the other EU members enjoyed.

Figure 1. Baltic least-traded exports

Source: Cho and Díaz (in press).

Least-traded imports

Figure 2 plots the evolution of Baltic least-traded imports between 1995 and 2008. We find that new goods imports also grew at robust rates, but their growth is about half the magnitude of the growth in the least-traded exports—the least-traded imports nearly doubled their share, whereas the least-traded exports quadrupled it. The least-traded imports from the EU15 and its individual members exhibited consistent growth throughout. On the other hand, imports of new goods from Russia—which had also been growing since 1995—started a continuous decline starting in 2003. This change in patterns can be attributed to the Baltics joining the EU customs union. Prior to their EU accession, the average Baltic tariff was in general low. Upon EU accession, the Baltics adopted the EU’s Commercial Common Policy, which removed trade restrictions for EU goods flowing into the Baltics, but—from the perspective of the Baltic countries—raised tariffs on non-EU imports, in turn discouraging the imports of Russian new goods.

Figure 2. Baltic least-traded imports

Source: Cho and Díaz (in press).

Are the Baltics different?

Figure 1 shows that the Baltic states were able to increase their least-traded exports by a significant margin. A natural question follows: Is this a feature that is unique of the Baltic economies, or is it instead a generalized trend among the transition countries?

Table 1: Growth of the share of least-traded exports (percent, annual average)

Source: Cho and Díaz (in press).

Table 1 reveals that the new goods margin played a much larger role for the Baltic states than for other transition economies such as the Czech Republic, Hungary and Poland (which we label as “Non-Baltics”), for all the export destinations we consider. Moreover, we find that while until 2004—the year of the EU accession—both Baltic and Non-Baltic countries displayed high and comparable growth rates of least-traded exports, this trend changed after 2004. Indeed, while there is no noticeable slowdown in the Baltic growth rate, after 2004 the Non-Baltic growth of least-traded exports to the world and to the EU15 all but stops, with the only exception being the Nordic destinations.

Conclusion

The Baltic states, and in particular Estonia, are usually portrayed as exemplary models of trade liberalization among the transition economies. Our results indicate that the Baltics substantially increased both their imports and exports of least-traded goods between 1995 and 2008. Since increases in the import variety mix have been shown to entail non-negligible welfare effects, we expect large welfare gains for the Baltic consumers experienced due to the increases in the imports of previously least-traded goods. Moreover, the literature has documented that increases in export variety are associated with increases in labor productivity. Our findings reveal that the Baltics’ increases in their exports of least-traded goods were even larger than their imports of new goods, thus underscoring the importance of the new goods margin because of their contribution to labor productivity gains.

References

Broda, Christian; and David E. Weinstein, 2006. “Globalization and the gains from variety,” Quarterly Journal of Economics, Vol. 121 (2), pp. 541–585.
Chen, Bo; and Ma Hong, 2012. “Import variety and welfare gain in China,” Review of International Economics, Vol. 20 (4), pp. 807–820.
Cho, Sang-Wook (Stanley); and Julián P. Díaz. “The new goods margin in new markets,” Journal of Comparative Economics, in press.
Feenstra, Robert C.; and Hiau Looi Kee, 2008. “Export variety and country productivity: estimating the monopolistic competition model with endogenous productivity,” Journal of International Economics, Vol. 74 (2), pp. 500–518.
Kehoe, Timothy J.; and Kim J. Ruhl, 2013. “How important is the new goods margin in international trade?” Journal of Political Economy, Vol. 121 (2), pp. 358–392.

Independent Media and Contemporary Military Doctrines

Posted on May 17, 2017 | Policy Brief

Governments often take unpopular measures. To minimize the political cost of such measures policy makers may strategically time them to coincide with other newsworthy events, which distract the media and the public. We test this hypothesis using data on the recurrent Israeli-Palestinian conflict. We show that Israeli attacks are more likely to be carried out when the U.S. news are expected to be dominated by important (non-Israel-related) events on the following day. In contrast, we find no evidence of strategic timing for Palestinian attacks.

The role of media in today’s conflicts is enormous. Parties to conflicts use propaganda in state-sponsored media and enroll state-sponsored trolls in social media to gain domestic public support for their military campaigns and, more generally, to raise own popularity. Involvement of Russia in Syria and Eastern Ukraine and its coverage on Russia-sponsored TV is a forceful illustration of this. Some most devastating conflicts used state media to enroll paramilitary. For example, Yanagizawa-Drott (2014) estimated that 51,000 perpetrators in Rwandan genocide were persuaded to participate in mass killings by RTLM radio.

Not all the media are under control of parties involved in conflicts. What is the role of independent media during conflicts? It is one thing to use the dependent media to portray one’s participation in conflict in a slanted manner; it is another to change one’s military strategy in order to improve one’s image in the independent media. Do military choose the timing and the weapon for their offences depending on the expectation of how their actions will be portrayed by the independent media? A statement on June 4, 2002, by Major General Moshe Ya’alon, then the Israel Defense Forces (IDF) chief of staff designate and until recently the defense minister of Israel, strongly suggests this is the case for the Israeli-Palestinian conflict. Mr. Ya’alon said: “This is first and foremost a war of ideology, and as such the media factor, the psychological impact of our actions, is critical. If we understand that a photograph of a tank speaks against us on CNN, we can take this into account in our decision as to whether or not to send in the tank. We schedule helicopter operations for after dark so they cannot be photographed easily. … Such considerations are already second nature to us. Officers … must understand that there are strategic media considerations. The tension between the need to destroy a particular building or to use a tank or helicopter, and the manner, in which the world perceives these actions, can affect the ultimate success or failure of the campaign. Even if we triumph in battle, we can lose in the media and consequently on the ideological plane.”

Our recent paper “Attack When the World Is Not Watching? U.S. News and the Israeli-Palestinian Conflict” (Durante and Zhuravskaya, 2017) forthcoming in the Journal of Political Economy investigates how Israeli military changes the planning of its operations in Gaza and the West Bank in the face of coverage by US media. In particular, we test whether Israeli authorities choose the timing of their attacks strategically to coincide with other newsworthy events so as to minimize the negative impact of their actions on U.S. public opinion by avoiding U.S. media coverage of their military operations, especially when they might lead to civilian casualties.

Methodology

We compile a list of fully exogenous events from forward-looking political and sports calendars in the U.S. between 2001 and 2011 and verify which of these events actually dominate US TV news, leaving little or no time to coverage of other events. Then, we compare the timing of these events to the timing of Israeli attacks on a daily basis.

We also use another, more continuous measure of whether the U.S. media and the public are distracted by other important events, namely the length of top three non-conflict-related news stories during evening news on three U.S. TV networks, where the evening newscasts are limited to 30 minutes, namely ABC, CBS, and NBC. As Eisensee and Stromberg (2007) point out, due to the competition between networks for audience, we can measure the importance of newsworthy events featured on the evening broadcasts because more important stories appear before less important stories, and they are longer.

Results

Timing of Israeli attacks and their coverage in US media

We find that both the incidence and the severity of Israeli attacks increased sharply when U.S. news were dominated by other events, such as US primaries and caucuses, general elections, and Presidential inaugurations. The probability that Israel carried out an attack against Palestinians rose to 53.2% one day before these important U.S. events from 38.7% on days that did not coincide with these events (over our observation period of 11 years, which includes heavy fighting during the Second Intifada). Figure 1 illustrates this finding. Attacks which coincide with the major political and sports events are also more deadly; as a consequence, the number of victims of Israeli attacks per day is 1.51 times higher during the days that coincide with major political and sports events compared to days that do not coincide with major events.

Figure 1. IDF attacks and exogenous predictable newsworthy events in the U.S.

Source: Durante and Zhuravskaya, 2017.

Using another measure, the length of top three non-conflict-related news stories during evening news on three U.S. TV networks, we also find that Israeli attacks are significantly more likely to occur and are more deadly when top three non-conflict-related news are longer on the following day.

Does it matter which military operation?

As some military operations are more costly to postpone than others, one should expect that only attacks that are less costly to more be strategically timed to other important events. This is exactly what we find: the timing of special targeted-killing operations, which are considered as extremely urgent by IDF, is not related to U.S. news cycle. In addition, one should expect military operations to be timed to other newsworthy events only when they are likely to generate negative publicity. As negative publicity about the conflict is mainly associated with civilian casualties, and civilian casualties are more likely when the operations are executed with heavy weapons, we find that the relationship between occurrence and severity of Israeli attacks and U.S. newsworthy events on the following day holds only for operations that involve the use of heavy weapons. We also check that the attacks are only timed to predictable newsworthy events.

Why tomorrow’s coverage matters more?

Israeli attacks get news coverage in U.S. media both on the day of the attack and one day later. Why, then, Israel times its attacks to news pressure on the following day rather than on the same day? To answer this question, we analyzed the content of news broadcasts and found that the type of coverage of Israeli attacks differs substantially between same-day and next-day reports. While the same-day and next-day news stories are equally likely to report information on the number of victims, news stories that appear on the day after the attack are much more likely to present personal stories of civilian victims and include interviews with their relatives or friends. Furthermore, next-day coverage is significantly more likely to include emotionally charged visuals of burial processions and scenes of mourning. Anecdotal evidence suggests that it is both easier and safer for a foreign journalist to get details of the story on the next day; and that the next day affords an opportunity to produce emotionally charged videos of funerals. Figure 2 illustrates these findings.

Figure 2. Comparison of the content of news casts about attacks that aired on the same day as an attack and on the day following the attack.

Source: Here you can write notes to the figure, graph or table. Do not forget to state the source of the figure, graph or table.

Since people react more strongly to personal stories than to statistics and facts, and since information transmitted only through words is less likely to be retained than information accompanied by images, it is not surprising that Israel times its attacks to predictable international newsworthy events expected on the following day, as the next-day news stories are more damaging to Israel’s public image.

Conclusion

These results have broader implications. Policy makers in other policy domains and other countries may also strategically manipulate the timing of their unpopular actions to coincide with other important events that distract the mass media and the public. Examples of unpopular policies characterized by suspicious timing abound: Silvio Berlusconi’s government passed an emergency decree that freed hundreds of corrupt politicians on July 13, 1994, the day Italy qualified for the FIFA World Cup final. Russian troops stormed into Georgia on August 8, 2008, the opening day of the Beijing Summer Olympics. Political spin-doctors often release potentially harmful information in tandem with other important events. This is exemplified by a notorious statement from the former UK Labour Party’s spin doctor, Jo Moore, who, in a leaked memo sent to her superiors on the afternoon of 9/11, said that it was “a very good day to get out anything we want to bury” (see http://www.telegraph.co.uk/news/uknews/1358985/Sept-11-a-good-day-to-bury-bad-news.html (accessed on July 7, 2015) and http://www.theguardian.com/politics/2001/oct/10/uk.Whitehall (accessed on July 7, 2015)).

Overall, policy makers’ strategic behavior may undermine the effectiveness of mass media as a watchdog, thus reducing citizens’ ability to keep public officials accountable

References

Durante, Ruben; and Ekaterina Zhuravskaya, 2017. “Attack When the World Is Not Watching? U.S. News and the Israeli-Palestinian Conflict”, Journal of Political Economy (forthcoming)
Eisensee, Thomas; and David Stromberg, 2007. “News Droughts, News Floods, and U.S. Disaster Relief,” Quarterly Journal of Economics, 05, 122 (2), 693–728.
Nevo, Baruch; and Shur Yael, 2003. The IDF and the press during hostilities, Jerusalem: The Jerusalem Democracy Institute, pp. 84-85, available at http://en.idi.org.il/media/1431355/IDFPress.pdf, accessed on May 18, 2016.
Yanagizawa-Drott, David, 2014. “Propaganda and Conflict: Evidence from the Rwandan Genocide,” Quarterly Journal of Economics, 129(4), pp.1947-1994.

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Intergenerational Mobility of Russian Households

Posted on May 2, 2017 | Policy Brief

To understand the nature of income inequality one needs to know how persistent the inequality is across generations. The same inequality levels could conceal different intergenerational mobility. We utilize the Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility. We find that although a sizeable upward intergenerational educational mobility, there is a pronounced occupational immobility and a low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially their mothers.

Sizeable and non-decreasing inequality in Russia poses a threat to social stability and long-term sustainability. Inequality in Russia has remained high throughout the transition period, and even slightly increased in the 2000s; the Gini inequality index rose from 0.397 in 2001 to 0.416 in 2014. The ratio of average incomes of the highest decile to those of the lowest decile also increased from 13.9 to 16 during this same period. This income gap is driven primarily by the gap between incomes of the top decile and all of the others: the top decile is estimated to have thirty percent of total monetary income in the economy. Furthermore, income inequality originates in earnings inequality: the top decile of wage earners gets thirty five percent of total wage earnings in the economy.

A key question is how persistent the inequality is, given that the same inequality levels could conceal different intergenerational mobility. In particular, social stability is challenged when income inequality is stable across generations, or put differently; there is little intergenerational mobility. Economic developments of the last 25 years seem to increase the risks of getting this problem in Russia.

Data and research methodology

We employ Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility (Denisova and Kartseva, 2016). The RLMS-HSE questionnaires in 2006 and 2011 contain questions on dates of birth, education and occupation of the father and mother of the respondent when the respondent was 15 years old.

To study occupational and educational mobility, we use the subsample of respondents of 25-55 years old and utilize the information on education and occupation of the respondent and his/her parents. We then estimate whether the parental education level predicts the probability that children have a university degree, a secondary or a junior professional degree.

To study intergenerational occupational mobility, we estimate influence of parental occupation on the probability that the child works as a manager, a professional, a technician or professional associate, a clerk, a qualified worker or an unskilled worker.

To study the child-parent income correlation based on RLMS is trickier. There is a panel component in RLMS but it is not long enough to study intergenerational mobility directly since we for most cases are not able to observe both parents and children during their working ages. To overcome the problem we impute wages for parents. In particular, we choose respondents aged 25-35 (children) in 2006 (and 2011). We then identify respondents born in the period 1945-1961 (1945-1966 for children in 2001) (‘parents’) and use the labor market information for this group as of 1995 (2001 as robustness check) to impute parental wages. We estimate a wage equation (separately for males and females) on the sample of ‘parents’ and then use the estimated returns (coefficients) and the reported age and education of respondent’s mother and father to impute wages of respondent’s parents.

We follow Björklund and Jantti (1997) to estimate the child-parent correlation of earnings based on the equation:

delta= β0 + β1X+ β2 delta_father + β3 delta_mother + ε

where delta=log(wage/average wage in respective sample), X – age, education, settlement type, region. Standard errors are clustered on primary sampling unit.

Intergenerational educational mobility

Our analysis shows that the education of parents, high professional (university) and secondary professional in particular, is a major determinant of children’s education. Moreover, there are clear signs of upward educational mobility across generations for both males and females: the coefficients in the transition parent-child matrix are significantly higher above the diagonal (Table 1).

Table 1. Father-child education matrix

Source: Authors’ calculations based on RLMS

The probability to have a university degree is 2.4 percentage points higher if the mother’s education is at university level (as compared to secondary school), and 2.1 percentage points higher if the father’s degree is at university level (as compared to secondary school). A secondary professional degree of parents also increases the probability of a child getting a university degree by about 1 percentage point. The probability of having secondary professional degree decreases if the father or mother has a university degree.

Intergenerational correlation of occupations

There are signs of sizeable occupational rigidity between generations, especially for the top two occupational groups (managers and professionals). The probability that a child works in the same occupational group is the highest for parents-professionals: it is 40% for fathers-professionals and 35% for mothers-professionals. Surprisingly, it is also rather high for parents employed as skilled workers – about 20%. These patterns survive controlling for other variables.

Income mobility

The correlation of parent-child wages measured for 2006 data are presented in Table 2. The results point to the sizeable average intergenerational rigidity of relative wages: the wage elasticity of children’s wages with respect to parental wages is about 0.4. This is at the level of the intergenerational wage rigidity in the US (Solon 1999).

There is sizeable gender asymmetry in the rigidity: we observe a high and significant correlation of son-mother wages, but an insignificant correlation of son-father wages. There is no significant correlation of daughter-parents wages.

Table 2. Parent-child income correlations, 2006

Source: Authors’ calculations based on RLMS

Conclusion

Generational poverty stemming from low intergenerational income mobility is a threat for sustainable development in any country. The economic and social development in transition seems to increase the risks of having this problem in Russia. Our estimates show that although there is sizeable upward intergenerational educational mobility in Russia, there is a pronounced occupational immobility, and low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially mothers. These findings are worrisome signals important for the design of policies of sustainable development.

References

Björklund, Anders; and Markus Jantti, 1997. “Intergenerational Income Mobility in Sweden Compared to the United States,” American Economic Review, 87(5), 1009–18.
Denisova, Irina; and Marina Kartseva, 2016, “Intergenerational Mobility of Russian Households”, mimeo
Solon, Gary, 1999. “Intergenerational Mobility on the Labor Market,” Chapter 29 in Handbook of Labor Economics, Vol.3 edited by O.Ashenfelter and D.Card , 1761-1800.

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Operating and Financial Hedging: Evidence from Trade

Posted on April 12, 2017 | Policy Brief

FREE Policy Brief - Operating and Financial Hedging Image 01.jpg

There is a large and growing literature that has modeled how real policies affect and interact with financial policies. It is important to consider such an interaction since a firm, just as a single value-maximizing agent, should make its strategic decisions optimally, taking into account all of its multi-dimensional facets (contracts with employees and suppliers, situation with market competitors, innovation, foreign-market operations and others – on the real side, and capital structure, dividend policy, IPO, hedging behavior – on the financial side). This policy brief introduces a new type of hedging exchange-rate risks through matching currencies of export revenues and import costs, and shows how it substitutes out financial hedging using currency derivatives.

Exchange-rate exposure and financial hedging around the world

Many firms are exposed to exchange-rate fluctuations in one way or the other. Because volatility is typically considered to be bad for a firm – either because small firms are risk-averse or because it may reduce the value of a risk-neutral firm through costly distress or agency costs – firms attempt to hedge it. Indeed many successfully do so. Bartram et al. (2009) report that about 60% of non-financial firms around the world use financial derivatives (forwards, futures, swaps, etc.), with the most popular type being currency derivatives (44%). These large numbers indicate the importance of risk management in general and hedging exchange-rate shocks in particular. There is also a considerable heterogeneity across countries. According to their investigation based on a subsample of world firms, currency derivative usage ranges from 6% in China and 15% in Malaysia, to 37% in the United States and 48% across Europe, to 80% in New Zealand and 88% in South Africa.

There is also some cross-sectional variation across firms. Geczy et al. (1997) report that among U.S. firms those with greater growth opportunities, tighter financial constraints, extensive foreign exchange-rate exposure and economies of scale in hedging activities are more likely to use currency derivatives.

Operational hedging

So what are potential alternatives to hedging exchange-rate exposure through currency derivatives? The literature has suggested other ways of reducing such cash-flow volatility – through operational hedges. The examples include diversifying the company’s operations and production geographically (as in Allayannis et al., 2001). The authors provide an example of Schering-Plough (a United States-based pharmaceutical company) that in their 1995 annual report suggested that hedging using financial instruments was not considered cost-effective, since the company operated in many foreign countries where the currencies would not generally move in parallel. More recent studies (e.g. Kim et al., 2006; Hankins, 2011) also support the geographical diversification of production and acquisition of foreign subsidiaries as important channels of operational hedging, and as such they can act as substitutes for financial hedging.

These papers are also part of the larger literature on the interrelations between real and financial strategies, and in particular the literature that has modeled how real policies, aimed at lowering operational risks (or alternatively increasing operating flexibility), reflect in various financial decisions (such as e.g. capital structure). Examples of such policies include the use of flexible manufacturing systems that allow changing the level of output, the product mix, or the operating “mode” (as in Brennan and Schwartz, 1985; He and Pindyck, 1992; and Kulatilaka and Trigeorgis, 2004); employing a contingent workforce (e.g. part-time and seasonal labor, as in Hanka, 1998 or workers on temporary contracts, as in Kuzmina, 2014); adopting a defined contribution, rather than a defined benefit or pension plan (as in Petersen, 1994); and many others.

Trade-related operational hedges

In Kuzmina and Kuznetsova (2016), we explore a different type of operational hedging – the one arising from exporting final goods and importing intermediate inputs from abroad at the same time. As previous literature has suggested, firms that export their final goods are naturally more exposed to exchange-rate risks due to their foreign-denominated contract obligations that have to be translated into domestic currency when the transaction clears in the future, the so-called transaction exposure of companies (Glaum, 2005). As long as volatility is costly for firms, higher exchange-rate exposure leads to more financial hedging, so previous papers indeed find a positive correlation between exporting and currency hedging (e.g. Geczy et al., 1997; He and Ng, 1998; Allayannis and Ofek, 2001).

This argument would similarly apply to firms that import their intermediate inputs from abroad, since they are similarly exposed to exchange-rate fluctuations on the cost side. In our paper, we attempt to provide new evidence on these channels, as well as to introduce a novel explanation to why not all firms hedge using financial derivatives. We show that firms that export and import at the same time hedge less using currency derivatives, and especially when volatility of exchange rate is high. We argue that when firms both export and import at the same time, their net foreign-denominated position (and thus exchange-rate exposure) becomes lower on average, and hence there is less incentive to hedge against it. This is consistent with foreign-currency matching of costs and revenues, which is a phenomenon also observable in other data. Although in our data we cannot observe currency of individual transactions for each firm, we do so in another project based on the data from Russia. Our calculations for Russian data, based on the whole universe of import and export declarations, suggest that for the major currencies, the probability of importing in the same currency is higher than in any other currency when a firm also exports in this currency. For example, out of all firms that have exports in Euro and some imports, 82% would import in Euro. The similar number for the U.S. dollar is 71%. Such trade-related operational hedge may arise naturally for firms in the global world, thus reducing their need to use financial instruments.

Germany as an interesting laboratory

To test our hypotheses, we use hand-collected data on a sample of German public firms during 2011-2014. Germany is a particularly relevant country for testing our hypotheses for at least three reasons.

First of all, it is the world’s third largest exporter and importer and the top one in Europe. Second and most importantly, if we want to explore currency risk arising from exporting and importing, at least some (and preferably many) of the export and import transactions have to occur in a foreign currency. This means that, for example, looking at the U.S. data would not give us a lot of power in identifying our mechanism, since according to Goldberg and Tille (2008), only 5% of all U.S. export contracts are set in a currency other than the U.S. dollar. On the other hand, more than half of German exports and imports outside the euro area are denominated in a currency other than the Euro, and in particular about 30-40% of all contracts are set in U.S. dollars. This means that our measured shares of non-euro zone exports and imports will actually have a large component of non-euro-denominated contracts, and we will have more power to measure the actual exchange-rate exposure arising from exporting and importing. Finally, we analyze the largest companies in Germany – those that trade on the Prime Standard segment of the Frankfurt Stock Exchange, since they have to disclose their use of derivatives due to the highest accounting and transparency requirements of this listing. These mandatory disclosure rules enable us to collect the data on hedging from companies’ annual reports and perform the analysis.

Identification strategy and results

To start the analysis, we provide some cross-sectional correlations. We find that firms in industries with more out-of-euro-zone exporting (importing) have a higher propensity to hedge using currency derivatives. In particular, a firm in an industry with 10pp higher export (import) shares has on average a 10.5pp (28.9pp) higher probability of currency hedging.

Although many industries simultaneously export and import a lot, others have a substantial imbalance in terms of export and import shares. We are therefore interested in whether this translates into different hedging behaviors. By adding the interaction between export and import shares in our regression specifications, we find that firms that simultaneously export and import hedge less than firms that just export or import. This is consistent with our hypothesis that firms decrease their effective exchange-rate exposure by having both revenues and costs in foreign currency and implies that operational hedging through matched currencies is a substitute for financial hedging.

In order to strengthen the result, we complement our cross-sectional correlations with a difference-in-differences methodology. To do this, we compare firms in industries with higher and lower out-of-euro-zone export and import shares during times of higher and lower exchange-rate volatility. We find that the higher the exchange-rate volatility, the larger this substitution effect is. This finding is stronger than a simple cross-sectional correlation between exporting, importing and hedging (which can be driven by omitted factors), since it uses an arguably exogenous volatility shock to show that operational hedging substitutes for financial hedging precisely during times when firms have highest incentives to hedge. The results are robust to using a set of control variables and firm and year fixed effects.

Implications

From an applied perspective, the interrelation between operational and financial strategies of the firm suggests that the decisions of the CEO and CFO should be complementary to each other to achieve the value-maximization goal of the firm. From a policy perspective, they imply that exogenous changes in government policies aimed at certain organizational changes in the firm (e.g. export promotion policies) could have indirect consequences for their riskiness and financing decisions.

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