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Avoiding Corruption and Tax Evasion in Belarus’ Construction Sector

Posted on November 20, 2017 | Policy Brief, Policy Papers

20171119 Avoiding Corruption and Tax Evasion in Belarus Image 01

This brief summarizes our research on the problem of corruption and tax evasion in the construction sector in Belarus. We conducted a survey of construction companies, asking them to estimate the extent of different dimensions of tax evasion and corruption within the sector. The results show the most problematic directions in the sphere. Based on international experiences, we develop recommendations of how to reduce corruption and tax evasion in construction of Belarus.

Shadow economy and the construction sector

The problem of a shadow economy is real for many countries in the world. Many countries try to minimize the level of this illegal activity. But it is very difficult to liquidate tax evasion or envelope wages fully.

In Belarus there is a lot of discussion about corruption and tax evasion limitation. The country ranked 79th in the Corruption Perception Index 2016. The situation in Belarus is much better then in Russia or Kazakhstan, but worse than in Sweden, Finland and Switzerland.

There is lack of systematically updated knowledge about the situation with corruption and tax evasion in the different economic spheres of Belarus. At the same time, there are sectors, which are more prone to develop a shadow economy. One of them is the construction sector. Multilevel chains of relations between contractors and subcontractors, numerous suppliers, and complicated procedures for facility acceptance create possibilities for illegal schemes.

Construction plays an important role in national production. In 2016, the construction sector corresponded to more than 6% of Belarusian GDP. In 2014, this indicator was above 10%. The decline can be explained by a reduction of preferential lending in housing construction and a recession in the economy. Despite the reduction in the share of GDP, around 8% of the total labor force works in construction. More than 90% of the legal entities in the sphere are presented by privately owned enterprises [8].

Taking into account the importance of construction it is necessary to emphasize that reducing the size of the shadow economy could create a better business environment, reduce companies’ expenditures for resolving issues in informal ways, and increase budgetary revenues.

In this brief we present a short summary of our research “Problems of corruption and tax evasion in construction sector in Belarus”, which is forthcoming in the International Journal Entrepreneurship and Sustainability Issues. The project was made in the framework of the project “Corporate engagement in fighting corruption and tax evasion”, financed by the Nordic Council of Ministries.

Method

In order to understand the main issues and challenges in construction sector, we surveyed 50 Belarusian construction companies. We took 20 companies from Minsk and its surrounding region, and 6 organizations from each Belarusian region (Brest, Grodno, Vitebsk, Gomel, and Mogilev). The survey was based on the method used in Putnins and Sauka (2016). This method includes a questionnaire, which helps understanding the actual situation with the shadow economy in the sector. The questions of the survey were divided into three parts.

The first part included neutral questions about economic characteristics of the company, such as number of employees, profit level, the year of establishment, wage levels, and form of ownership.

The second part include more sensitive questions, but which can help us understanding the most problematic issues concerning to corruption and tax evasion. These questions concern such indicators as the level of underreported business income, the degree of underreported number of employees, the percentage of revenue that firms pay in unofficial payments to ‘get things done’, and main barriers to business development. In order to make the answers easier for participants, all the questions deal with the situation in the sector as a whole, and not the company in particular.

The third part of questions concerns the situation in public procurement, and includes the perception of main problems in the sphere.

Survey results

The first part of the survey shows that there has been a decline in many of the economic indicators during the last two years. This may be one factor stimulating the sector’s development of informal activities. Indeed the results of the second part of survey demonstrate that level of shadow economy has significant dimensions. More then 60% of the respondents agree that some firms in the sector received hidden income. More than 50% of the interviewed companies believe that some organizations in the construction sector hire part of their employees unofficially. Wages in “envelopes” is also a problem for the construction companies.

Unregistered firms are a big threat to having a well-developed construction sector. More than 60% of the interviewed companies agree with the existence of unregistered companies. Such non-official organizations create unfair competition in the sector and decrease the level of budget revenues. Many of the unregistered companies work in the sphere of home improvements and renovations.

Figure 1. Estimation of the approximate level of hidden salaries (“wages in the envelopes”) in construction industry

Notes: X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey

The survey results allow us to conclude that the state budget loses part of its corporate income taxes, taxes on wages and social contributions due to the existence of hidden incomes, wages in envelopes, and unregistered companies and employees.

The last, but not the least, question in the second part of the survey was about main obstacles and barriers for operating in the construction sphere. Most of the respondents underlined three groups of barriers. One of them is the administrative challenge, including high level of taxation, inconsequent business legislation, and attitude of the government towards business in general. The second barrier includes economic problems such as lack of funds for business investments, payment behavior of clients, low product or service demand from customers, low access to credits, and inflation. The third group of problems in the construction sector is related to the shadow economy. A large part of the enterprises experiences a problem of high competition from illegal business and corruption. At the same time, a positive thing is that the majority of respondents does not consider crime and racketeering as a threat for the sector.

Figure 2. Estimation of approximate share of unregistered firms production in the total output in construction industry

Notes: The X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey

In the third part of the survey, companies were asked about their participation in public procurement tenders. About 42% of all respondents did not have this experience over the past two years. One of the questions was about competition among construction companies. About 40% of all respondents underlined that they have lost at least one public tender because of unfair competition. Given that only 58% of the companies participated in tenders, we can conclude that unfair competition is a widespread problem for the majority of public procurement auction participants. Imperfect legislation is another problem for the companies. 46% of all respondents believe that the quality of legislation in the sphere is unsatisfactory. Only 12% of the companies did not see any problems in the national legislation.

At the end of the interview, companies were asked to list three main problems in the sphere of public procurement. The answers are shown in Figure 3.

Figure 3. Main problems that companies face when participating in public procurement tenders

Notes: The X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey

The most common answer was corruption. Unfair competition and nepotism were also quite common problems in the public procurement sphere. Among administrative barriers, companies emphasized the complexity of documentation preparation and imperfect legislation. Important economic problems were inflation and unequal conditions for public and private enterprises.

International experiences and recommendations in fighting corruption and tax evasion in the construction sector

Corruption and tax evasion can be stimulated by different factors. One of the main preconditions of the shadow economy in the Belarusian construction sector is inconsistent and frequently changing legislation. For example, public procurements are regulated by the Presidential Decree (Ukaz) on procurement of goods (works, services) in construction. However, this regulation document expires at the end of 2018. Before 2017, such operations were regulated by several legislative acts. Developing understandable and sustainable legislation, which creates clear rules for participants of the market, is very important to increase transparency and openness of the market [11; 12; 13; 15; 18].

Another problem concerns the relations of contractors and sub-contractors. In many cases negotiations between parties are closed and non-transparent. So, it is very difficult to estimate the effectiveness of costs and proper use of funds.

Modern E-Government system adoption can support increased transparency between contractors and sub-contractors, as well as improve the quality of state services. One of the directions in this sphere is the transition towards full electronic document management. [3; 4; 6].

Another risk is related to public procurement procedure. Direct communications between public tender participants and organizers create possibilities for unfair competition. There is substantial international evidence showing that full digitalization of the process would improve the transparency of the public procurement procedure [3; 4; 21]. For example, good reference points for implementation of such digitalization can be the Georgian or Ukrainian experiences of electronic tenders. These two countries have relatively similar institutional environment and heritage as Belarus.

The problem of tax evasion is often related with payments in cash. Such transactions are less transparent and visible for authorities. According to national legislation operations between legal entities should be in cashless form. But there are exceptions to the rule [20]. In this regards the level of tax evasion would be decreased if payments in cash will be minimized.

Another concern is the efficiency of the public procurement procedures. During public procurement auctions in construction, price plays the most important role. The share of “Bid Price” criterion in total volume of all criteria can be up to 50%. The project with the lowest price has the best chance to win the tender. This is not always reasonable. Moreover, some companies hire disabled people that allow them to obtain preferential treatment in the public procurement procedure – for example, apply special correction indicators to the final price. In many cases it is better to install more expensive but high efficiency (more qualitative or ecological) equipment instead of buying cheap but low quality ones. Of course, even in EU legislation, the cost or price of projects is a very important criterion. But then it is often defined as a price-quality ratio. In this regards, the quality of the project can be estimated from the environmental, qualitative or social side [12; 19].

One more issue according to survey results is the problem of unregistered labor force in construction. It can be partly resolved by ID card implementation for all workers and employers in construction sector. In Finland, for example, all workers in construction must have such cards during workdays. Tax authorities can check the availability of the cards at any time [17].

Conclusion

Our survey of Belarusian construction companies confirmed wide exposure of the sector to tax evasion and corruption. The majority of the respondents agreed that some companies hire unregistered workers, pay wages in envelopes, or have hidden income. The most common answer to the main problems in the public procurement sphere was corruption. Based on international experience and national peculiarities, it is advisable to propose the following measures to reduce corruption and tax evasion in construction sector:

  1. Adoption of sustainable legislation.
  2. E-Government system development.
  3. Modernization of the electronic tender system to require no direct contacts between organizers and tender participants.
  4. Reduction of the possibilities of making payments in cash.
  5. Implementation of a price-quality ratio as one of the main criteria for choosing the winner of tenders.
  6. Introduction of ID cards for all employees and employers in the construction sector.

These and other measures are likely to significantly improve the business environment in the construction sector.

References

[1] Anderson, E. 2013. Municipal “Best Practices”: Preventing Fraud, Bribery and Corruption, International Centre for Criminal Law Reform and Criminal Justice Policy. Available on the Internet:http://icclr.law.ubc.ca/sites/icclr.law.ubc.ca/files/publications/pdfs/Municipal%20Best%20Practices%20-%20Preventing%20Fraud%2C%20Bribery%20and%20Corruption%20FINAL.pdf.

[2] Fazekas, M., Toth, I.J., King, L.P. 2013. Corruption manual for beginners: “Corruption techniques” in public procurement with examples from Hungary, Working Paper series: CRCB-WP/2013:01 Version 2.0, Budapest, Hungary. Available on the Internet: http://www.crcb.eu/wp-content/uploads/2013/12/Fazekas-Toth-King_Corruption-manual-for-beginners_v2_2013.pdf.

[3] Krasny, A. 2014. Georgia E-Government. Available on the Internet: https://www2.deloitte.com/content/dam/Deloitte/ua/Documents/public-sector/e-government/Electronic%20government%20of%20Georgia.pdf.

[4] Luzgina, A. International experience of the e-Government System development/ A. Luzgina //Journal of the Belarusian State University. Economics. – Minsk, 2017. – P.76-83.

[5] Luzgina, A., Laukkanen E., Larjavaara I., Viavode I., Volberts J. ,Corporate engagement in fighting corruption and tax evasion in construction sector”, forthcoming in “Entrepreneurship and sustainability issues”

[6] Naumov, A. 2014. Georgia E-experience for Belarus. Available on the Internet: http://e-gov.by/best-practices/elektronnyj-opyt-gruzii-dlya-belarusi.

[7] Official website of Transparency International. Available on the Internet: https://www.transparency.org/.

[8] Official website of Belarusian National Statistical Committee. Available on the Internet: http://www.belstat.gov.by.

[9] Official website of the European Commission. Available on the Internet: https://ec.europa.eu/commission/index_en.

[10] On procurements of goods (works, services) [Electronic source] // Decree of the President of the Republic of Belarus/ 20.10.2016 # 380. Rus.: О закупках товаров (работ, услуг) при строительстве, Указ Президента Республики Беларусь от 20.10.2016, №380. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=P31600380.

[11] On public procurements of goods [Electronic source] // Law of the Republic of Belarus/ 13.07.2012, # 419-З. Rus.: О государственных закупках товаров, работ услуг Закон Республики Беларусь от 13 июля 2012 г. № 419-З. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=h11200419&p1=2.

[12] On organization and conduct of the procurement of goods (works, services) procedures and settlements between customer and contractor in facilities construction [Electronic source] // Resolution of the Council of Ministers of the Republic of Belarus / 31.12.2014, # 88.: Rus: Об организации и проведении процедур закупок товаров (работ, услуг) и расчетах между заказчиком и подрядчиком при строительстве объектов, Постановление Совета Министров Республики Беларусь №88 от 31.12.2014. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=C21400088.

[13] Putnis, J.T., Sauka, A. 2016. Shadow economy index for the Baltic countries 2009 – 2016. The Center for Sustainable Business at SSE Riga. – 47 p.

[14] Pelipas, I., Tochitskaya, I. 2016. Problems of corruption in the assessments of small and medium enterprises. Available on the Internet:

[15] Procurement in construction, what has been changed since January 1, 2017. Available on the Internet: http://www.mas.by/ru/news_ru/view/zakupki-v-stroitelstve-chto-izmenilos-s-1-janvarja-2017-goda-852/

[16] Preventing corruption in public procurements. 2016. OECD Publishing. Available on the Internet: http://www.oecd.org/gov/ethics/Corruption-in-Public-Procurement-Brochure.pdf.

[17] Briganti, F., Machalska, M., Steinmeyer, Heinz-Dietrich, Buelen, W. 2015. Social Identity cards in the European construction industry, edited by Buelen W. Available on the Internet: http://www.efbww.org/pdfs/EFBWW-FIEC%20report%20on%20social%20ID%20cards%20in%20the%20construction%20industry.pdf.

[18] Zaiats, D. 2015. The authorities will strengthen the fight against the shadow economy [Electronic resource]. – Mode of access: https://news.tut.by/economics/465337.html.

[19] On public procurement and repealing Directive 2004/18/EC [Electronic resource]// Directive 2014/24/EU of the European Parliament and of the Council / 26 Februay 2014.  – Mode of access: https://news.tut.by/economics/465337.html.

[20] On making amendments and alterations to Instruction on the procedure of conducting cash transactions and the procedure of the cash settlement in Belarusian rubles on the territory of the Republic of Belarus // Resolution of the National Bank of the Republic of Belarus / 31.03.2014. #199. Rus: – О внесении дополнений и изменений в Инструкцию о порядке ведения кассовых операций и порядке расчетов наличными денежными средствами в белорусских рублях на территории Республики Беларусь. Mode of access: http://pravo.by/document/?guid=12551&p0=B21428983&p1=1&p5=0.

[21] Prozorro [Electronic source]. – Mode of access: https: //prozorro.gov.ua/en.

The Determinants of Renewables Investment

Posted on November 13, 2017 | Policy Brief

20171112 Determinants of Renewables Investment 01

On the 24th of October, SITE held the first of its series of Energy Talks, replacing what for one decade had been known as SITE Energy Day. For this first edition, SITE invited Thomas Sterner, Professor of Environmental Economics at the University of Gothenburg to give a presentation under the headline of “Technological Development, Geopolitical and Environmental Issues in our Energy Future”. To comment on the presentation, Leonid Neganov, Minister of Energy of Moscow Region, and Karl Hallding, Senior Research Fellow at the Stockholm Environment Institute (SEI), had been invited. This policy brief reports on the important subjects presented by our guests as well as the discussion that took place during the event.

From climate change concerns to climate change targets

Thomas Sterner began his presentation by addressing the well-known issue of climate change, a constantly current topic.

Different versions of Figure 1 (below) have been used extensively by those discussing climate change over the last decades, most notably by the previous US President Al Gore in his 2006 documentary “An Inconvenient Truth”. It shows the concentration of CO2 (carbon-dioxide) in the atmosphere over the past 400,000 years. There is wide agreement within the scientific community that the emissions of greenhouse gases (GHG), such as CO2, methane and nitrous oxides, have led to the shifting weather patterns and increased temperature over the past century (NASA, 2017).

Figure 1. Level of CO2 in the Atmosphere

Notes: The vertical red line is the Keeling curve, showing how the concentration has changed since 1958. Source: Allmendinger, 2007.

Predicting the impact of these emissions is far from an exact science: the temperature increases are likely to be unevenly spread across the world as shown in Figure 2. Some areas are likely to be particularly afflicted, especially coastal lowlands susceptible to flooding and semi-arid areas where droughts can become more likely. Unless current emission levels start to decrease, we are likely to observe severe results of climate change within 20 years, such as displacement and increased migration in the wake of extreme weather (NIC, 2016). For instance, adverse health effects in China, or decreasing productivity in South-East Asia, have already become apparent due to current increased temperatures (Kan, 2011; Kjellstrom, 2016).

Figure 2. Predicted Temperature Increase

Source: IPCC, 2013.

To tackle this issue and its negative economic impacts, many policy makers have agreed to replace fossil fuels with renewables. Renewables is the collective term of energy sources that have a neutral or negative net-effect of GHG emissions and are extracted through resources that are continuously replenished, e.g. solar, wind and hydro power, and biomass energy.

As the issue of climate change is a global one, the transition to renewables needs to be global too. International climate agreements have hence long been the accepted norm to approach climate change issues. The Paris Agreement is currently the guiding principle, in spite of the announcement of the Trump administration to withdraw the United States. Though instrumental in creating a momentum in the transition to lower levels of GHG emissions, it comes with many flaws. Its goal of a maximum average temperature increase of 2°C might be considered radical given current levels. However, the policy instruments that the target depends on – the Intended Nationally Determined Commitments (INDCs) – shift the responsibility to individual nations and remove the global responsibility. As Thomas Sterner pointed out, the first three words of this acronym remove indeed any binding force, and elementary game theory tells us that it will be hard, not to say unlikely, for all signatories to remain cooperative in achieving the target of 2°C.

Investing in renewables: from political choice to competitive choice

As stated above, investing in renewables is a necessary condition to achieve climate change targets. Indeed, there are some countries that have pushed the development of renewables with the aim to reduce the fossil fuel dependency to a minimum level in a very near future (see Figure 3). However, most of these investments are currently driven by political will. A natural question is whether renewables technologies can be competitive.

It is a fact that costs of renewables have been severely decreased in the last decade (Timmons et al., 2014). However, as Thomas Sterner mentioned, the cost of renewables and of fossil fuels are still very place and time specific and depends on the scale. Investments in renewables are growing and solar and wind power have both seen production capacities increasing markedly yearly over the last years (GWEC, 2016; IEA, 2017a). However, coming from an initial low level, it will take some time before we will be able to rely on them.

Even with massive investments and decreasing generation costs, the intermittent nature of most renewable energies will still impede the competitiveness of renewables. Solar and wind power are the technologies where most of the development has been centred (Frankfurt School-UNEP Centre/BNEF, 2017). They are highly weather dependent and electricity production from these sources cannot be secured all of the time. This makes countries dependent on backup technologies. In some countries, the obvious answers to these challenges have been hydro and nuclear power. Both technologies have their respective drawbacks though.

Figure 3. World’s Top 10 Investors in Renewable Energy in 2016

Notes: New Investments $BN, Growth on 2015. Source: Frankfurt School-UNEP Centre/BNEF, 2017.

Hydro power requires a geography that allows for dams, which in turn change the nature markedly around them and may not be available during drought periods. Nuclear energy has surrounding safety aspects that most recently came to light with the 2011 Fukushima Daaiichi nuclear disaster, leading Germany to decide to shut down all of its 17 reactors by 2022 (25 % of the country’s electricity production). Moreover, it may also be technically difficult to have nuclear as a backup technology given the associated ramping and start-up constraints.

Two further remarks on the intermittency problem can be made. First, this problem is likely to become more severe when policymakers push for large-scale electrification (c.f. EU Energy Roadmap established in 2011). For example, the full electrification of transport or heating sector will drive up the demand for and consumption of electricity. As this happens, the need for something to secure constant energy access will increase.

Second, only the development of technologies that allow electricity storage could solve this issue permanently. However, the current technological progress regarding batteries’ capacity cannot yet offer the solution (J. Dizard, 2017).

Oil price, a reference price

Another important aspect stressed by Thomas Sterner was to take into account the significant role of fossil fuel prices. Although identifying an optimal oil price for a fossil-free future is not a straightforward procedure, as discussed during the event.

The high price of oil during the late 00s and early 10s stimulated the development of alternative technologies. As awareness of climate change and its effects increased among policy makers and the general public, there was a momentum to push for the development of renewables.

As investments in renewables went up, so did investments in another less green technology: hydraulic fracturing, or fracking. In the 10 years between 2005 and 2015, the United States alone saw the extraction of shale gas and oil to increase six-fold. (EIA, 2016) In part to maintain a market share, OPEC countries exceeded their own set production limits and oil prices tumbled from around $100 per barrel to around $50 (Economist, 2014).

With roughly three years behind us of somewhat stable and low oil prices, the question is what the implications of this are. It makes it more difficult to phase out fossil fuels as demand for them goes up, depressing efforts put into the research and deployment of renewables. Energy efficiency also becomes less important, driving up waste and stopping investments in energy conservation.

On the other hand, with low oil prices, investments in the fossil-fuels industry are also less likely to take place. Keeping resources in the ground becomes more palatable as profit margins are pushed down. This, in turn, is likely to have a positive effect on environment by decreasing the level of GHG emissions.

The invited guests, Leonid Neganov and Karl Hallding spoke more in depth about two central countries that contribute in shaping global environmental policy.

The local conditions, Russia and China examples

As the world’s fourth largest supplier of primary energy and the largest supplier of natural gas to the EU (IEA, 2017b), Russia presents an interesting case to observe as a country supplying fossil fuels. Leonid Neganov, Minister of Energy of Moscow Region, commented on the current policy direction of the country. He explained that non-renewable, GHG emitting energy sources make up a majority, roughly 60% of the Russian energy balance. The rest is provided by more or less equal shares of nuclear and hydro power. New renewable technologies make up a miniscule share of an estimate 0.2% of the current total.

According to Neganov, in the coming 20 years, we should not expect to see too much of a change. Though total output is expected to increase, the share of GHG-neutral energy will remain more or less constant, though the share of renewables are set to increase to 3% according to the current drafts of Russian energy policy. A more pronounced transition to other energy sources are more likely in a longer perspective towards 2050, even though circumstances may naturally change over the coming decades.

Other available information also points to that Russia has decided to tackle the shift in consumption of its major market in Europe by widening its geographic reach. Massive infrastructure investments, such as the Altai and TurkStream gas pipelines, will enable Russia to more easily reach markets that are currently beyond any practical reach.

With the Altai pipeline, Russia will be able to provide China with natural gas at a much greater level than before. China being by far the largest producer of coal sees an opportunity to shift away from the consumption of a resource that during winters causes its major cities to periodically become enveloped in clouds of smog and at the same time also decrease its GHG emissions. The environmental benefits of natural gas as opposed to coal should not be exaggerated though. Thomas Sterner pointed out that methane, the main compound of natural gas, is a considerably more potent GHG than CO2. A total leakage of an estimated 1% negates the environmental benefits, he said.

Karl Hallding, Senior Research Fellow at SEI, particularly stressed the need to look at China. It is the supplier of half of the world’s coal, extraction levels remain high. (BP, 2017) Domestic consumption is decreasing but consumption of Chinese coal is, however, more likely to shift geographic location rather than to be left in the ground, said Hallding. Through massive infrastructure investments, such as the New Silk Road, and in energy production in Sub-Saharan Africa, China spreads its influence (IEA, 2016). By exporting emissions, the impact at the global level will not change.

References

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Ethnic Networks in Ex-USSR

Posted on November 6, 2017 | Policy Brief

20171106 Ethnic Networks in Ex-USSR Image 01

Do ethnic networks facilitate international trade when formal institutions are weak? Using data collected by ethnologists on the share of ethnic groups across countries, this study assesses the effect of ethnic networks on bilateral trade across the sphere of the former Soviet Union. This region provides a perfect setting to test for this effect as both forced re-settlement of entire ethnic groups during the Stalin era and artificially drawn borders in Central Asia led to an exogenous ethnic composition within countries. While ethnic networks do not seem to have played a role in inter-republic trade during the Soviet Union, they did facilitate trade in the years following the collapse of the Soviet Union, a transitional period when formal institutions were weak. This effect, however, eroded steadily from the early 2000s.

Economists and historians alike study the role of ethnic networks in international trade. Some prominent examples are the Greek commercial diaspora of the Black Sea in the 19th century (Loannides and Minoglou, 2005), the Maghribi traders in 11th-century North Africa (Greif, 1993), or the overseas Chinese all around the world in the last decades (Rauch and Trindade, 2002). Such networks facilitate trade by building trust relationships, enforcing contractual agreements in weak legal environments, matching buyers with faraway sellers that speak different languages, and by exchanging information on arbitrage opportunities.

In “Ethnic Minorities and Trade: The Soviet Union as a Natural Experiment”, forthcoming in The World Economy, we study the Soviet Union (USSR) to assess the role of ethnic networks in international trade. We argue that ex-USSR countries are particularly well suited for such a study. Indeed, the ethnic diversity of ex-USSR countries is exogenous, partly due to the creation of artificial borders cutting through ethnic homelands, and partly due to forced relocations (deportations) during the Stalin era, which brought ethnic groups to various remote regions of the USSR. This exogeneity adds power to our empirical strategy.

Ethnic Networks in the USSR

We first build a measure of ethnic networks based on the size of common ethnic groups using ethnologists’ data from the Ethnic Power Relations Dataset on the resulting ethnic groups across ex-USSR countries (Vogt et al., 2015; Bormann et al., Forthcoming). It covers all ethnic groups in every country of the world from 1946 to 2013. While there is some yearly variation in the data, we focus on the cross-section average for the pre-1991 period as per our identification strategy based on exogenous distributions.

Figure 1 gives an overview of the spatial distribution of ethnic groups, such as Russian, Kazakh, or Uzbek.

Figure 1. Ethnic Groups in the USSR

Source: Authors’ own ArcGIS mapping based on the EPR-ED dataset.

Russians are ubiquitous across the Soviet sphere. Countries with the largest ethnic Russian populations are Kazakhstan, Estonia, Latvia and Moldova. At the same time, Russia is very diverse. Almost all of the 60 ex-USSR ethnic groups are present in Russia, and ethnic Russians account for only 62% of the population. Most countries are ethnically diverse. Kazakhstan for example is home to Russians as well as Germans, Tatars, Ukrainians, Uzbeks and Uighurs.

From the information on ethnic populations within each country, we create an ethnic network index as the sum of products of common ethnic groups as a share of the country’s population. Figure 2 presents a matrix overview of the ethnic network index among country pairs with darker shades corresponding to higher scores. Some high scoring country pairs are Russia—Kazakhstan, Ukraine—Russia, Uzbekistan—Tajikistan, Kyrgyzstan—Uzbekistan, Latvia—Kazakhstan, and Ukraine—Kazakhstan.

Figure 2. Ethnic Networks Index

Source: Authors’ estimates. The index is the sum of products of common ethnicities as a share of the country’s population.

Effect of Ethnic Networks on Bilateral Trade in the USSR

Next, we evaluate the impact of ethnic networks on aggregate trade between the countries of the former Soviet sphere. We use trade data from two sources. First, the data on internal trade between Soviet republics from 1987 to 1991 are from the input-output tables of each Soviet Union republic as compiled by the World Bank mission to the Commonwealth of Independent States (Belkindas and Ivanova, 1995). Second, the Post-1991 to 2009 trade data are from the Correlates of War Project (Barbieri et al., 2009, 2016), which offers the best coverage of the trade in the region.

We follow the migrant network and trade literature and estimate a standard log-linear gravity equation controlling for importer-year and exporter-year fixed effects (Anderson and van Wincoop, 2003).

Figure 3 presents the results on the effect of ethnic networks on trade over time. We observe that there is no effect in the period before the end of the USSR, a positive effect after the breakup of the Soviet Union, and an erosion of this effect from 2000s on (omitting Russia from the sample does not alter the results).

These results can be explained with the fact that in the Soviet Union ethnic ties did not matter as official production and trade were centrally planned by the State Planning Committee, Gosplan, and by State Supplies of the USSR, or Gossnab, which was in charge of allocating producer goods to enterprises. Free trade was forbidden. However, once the Soviet system collapsed and before countries could establish more formal trade ties, the first reaction and fallback option for many people was to reach out to their co-ethnics (in the 1990s) to substitute for the broken chains of the centrally planned trade (Gokmen, 2017). The other reason is that the institutional framework was at its weakest in this transitional period, and hence, reliance on informal institutions such as ethnic networks may have been especially strong (Greif, 1993). Once systematic and formal trade ties could be established, more and more traders no longer had to rely on their ethnic networks and this could explain the decline in the effect in the 2000s.

Figure 3. The Effect of Ethnic Networks on Trade over Time

Source: Authors’ estimates. Estimate of the effect of ethnic networks on bilateral trade in a gravity model controlling for distance, contiguity, and importer and exporter fixed effects.

Conclusion

This study shows that ethnic minorities played a role in shaping trade patterns across ex-USSR countries, but only in the early years following the collapse of the Soviet Union. Thus, we argue that reliance on informal institutions, such as ethnic networks, in forming trade relations is especially strong when the institutional framework is at its weakest in the transition period. This message may hold, not only for transition countries, but also for other developing countries with poor institutions.

References

  • Anderson, J. E. and E. van Wincoop, 2003. “Gravity with Gravitas: A Solution to the Border Puzzle,” American Economic Review, 93, 170-192.
  • Barbieri, K., M. G. Omar, and O. Keshk, 2016. “Correlates of War Project Trade Data Set Codebook, Version 4.0.”
  • Barbieri, K., M. G. Omar, O. Keshk, and B. Pollins, 2009. “TRADING DATA: Evaluating our Assumptions and Coding Rules,” Conflict Management and Peace Science, 26, 471-491.
  • Belkindas, M. and O. Ivanova, 1995. “Foreign Trade Statistics in the USSR and Successor States,” Tech. rep., The World Bank, Washington, DC.
  • Bormann, N. C., L. E. Cederman, and M. Vogt, Forthcoming. “Language, Religion, and Ethnic Civil War,” Journal of Conflict Resolution.
  • Gokmen, G., 2017. “Clash of civilizations and the impact of cultural differences on trade,” Journal of Development Economics, 127, 449-458.
  • Gokmen, Gunes; Elena Nickishina; and Pierre-Louis Vezina, forthcoming. “Ethnic Minorities and Trade: The Soviet Union as a Natural Experiment”, The World Economy.
  • Greif, A., 1993. “Contract enforceability and economic institutions in early trade: The Maghribi traders’ coalition”, The American Economic Review, 525-548.
  • Loannides, S.; and I. P. Minoglou, 2005. “Diaspora Entrepreneurship between History and Theory”, London: Palgrave Macmillan UK, 163-189.
  • Rauch, J. E. and V. Trindade, 2002. “Ethnic Chinese networks in international trade”, Review of Economics and Statistics, 84, 116-130.
  • Vogt, M., N. C. Bormann, S. Regger, L. E. Cederman, P. Hunziker, and L. Girardin, 2015. “Integrating Data on Ethnicity, Geography, and Conflict: The Ethnic Power Relations Dataset Family,” Journal of Conflict Resolution, 1327-1342.

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Rewarding Whistleblowers to Fight Corruption?

Posted on October 23, 2017 | Policy Brief

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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

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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

20171008 On Economics of Innovation Subsidies in Russia Image 01

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

20170930 Fiscal Redistribution in Belarus Image 01

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

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Cross-Country Differences in Convergence in CESEE

Posted on June 19, 2017 | Policy Brief

An image of cars travelling up and down the highway next to tall buildings representing convergence in CESEE

Since 1989, there have been large differences in the convergence of the income levels of the former communist countries in CESEE with those in the US. Most Central European countries have seen a sharp rise in relative incomes, but many countries in former Yugoslavia and the CIS have not—indeed, some countries, including Moldova and Serbia, are now poorer than they were in 1989 (Figure 1).

Figure 1. Transition outcomes

01 Figure Transition outcomes. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

Figure 2. GDP level in Poland and Ukraine

02 Figure GDP level in Poland and Ukraine. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

The difference between Ukraine and Poland is particularly stark. In 1989, both had similar income levels, but Poland is now more than three times as rich (Figure 2). As a result, cross-country income differences in CESEE remain large. In 1989, the Czech Republic, Russia, Slovenia and Croatia had the highest income per capita in 1989, about 4 times as high as in Albania and Moldova, the poorest in the group. Twenty-six years later, the differences are even larger. GDP per capita in Slovenia is 6 times as high as in Moldova (Figure 3).

Figure 3. Cross-country income differences

03 Figure. Cross-country income differences. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

 What Explains Convergence Differences?

These differences in convergence do not seem to reflect data problems. True, GDP statistics in 1989 were not very good. It is hard to measure value added when prices are not quite right. Moreover, GDP at that time was probably not a good indicator or of consumer welfare. Much of what was produced was not wanted by consumers (e.g. military expenditures) and/or of low quality. Nevertheless, these issues apply to all post-communist countries in the regions—it is not clear that some countries suffered from data problems more than others.

Indeed, more direct measures of economic activity also suggest large initial output falls and large cross-country differences. Between 1990 and 1995 electricity consumption per capita fell by almost 40 percent in Ukraine and Moldova. By then electricity consumption in Poland had nearly recovered to the 1990 level (Figure 4).

Figure 4. An alternative measure of decline in economic activity

04 Figure. Alternative measure of decline in economic activity. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: IFA Statistics and IMF staff calculations.

Instead, several factors seem to have a played a role:

  • The speed of transition to a market economy
  • War and conflicts
  • Boom-busts
  • EU Membership
  • Whether transition has been completed

Countries that reformed early had a shorter and shallower post-transition recession. The lower the EBRD transition index in 1995 (i.e., the less the economy was reformed), the sharper the output decline between the beginning of the transition and 1995 (Figure 5).

Figure 5. Market reforms and post-transition recession

05 Figure. Market reforms and post-transition recession. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

Why was this? In late 1989, a fierce debate broke out over what came to be called gradualism versus shock therapy. Many gradualists argued that the structural flaws of the economy would frustrate attempts at liberalization, and therefore that reforms should be implemented in a gradual, sequenced way. But for others—including key figures such as Leszek Balcerowicz in Poland—understanding the nature of the problem meant the opposite: reform was a seamless web that could only succeed if all the changes happened together, because liberal prices, improved governance, and a stable economic and financial environment were needed to reinforce one another; little could be achieved with a partial reform. The evidence from the past 25 years has vindicated the seamless web theory of transition. There is no doubt that some reforms took much longer than anticipated, including privatization, both of banks and companies. But it seems clear that the countries that made sweeping changes, and that kept at reform and stabilization have done well.[2] Countries that followed a more gradual path suffered from the decline of the old industries and did not get the boost from the growth of new firms. And in some countries bouts of macroeconomic instability repeatedly undermined reforms and sapped political momentum.

Weaker growth in the early transition years was not compensated by faster growth later. Countries, where output declines were deeper in early 1990s, did not see more rapid growth in subsequent years (Figure 6).

Figure 6. Permanent output losses in the early transition

06 Figure. Permanent output loses in early transition. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

Wars and conflicts also played an important role. It is striking that the five countries with the lowest growth all had a war or serious conflict between 1990 and 2015 (Figure 7).

Figure 7. Wars and conflicts impact on long-term growth

07 Figure. Wars and conflicts impact on long-term growth. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

Avoiding boom-busts helped boost longer-term growth. Steady growth rates seem to be more conducive to higher long term growth than booms followed by busts. Between 2002 and 2008, Romania had capital inflows fueled boom and grew much faster than Poland, but thereafter it suffered a deep bust, and between 2002 and 2015, Poland has grown faster (Figure 8).

Figure 8. The hare and the tortoise

08 Figure. The hare and the tortoise. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

EU accession was a powerful catalyst for reforms and upgrading of institutional frameworks. CESEE countries that joined the EU were required to bring their regulations and institutions up to Western European standards. There is a striking difference in the level of EBRD transition indicators between EU countries and non-EU countries (Figure 9).

Figure 9. EU accession as a reform catalyst

09 Figure. EU accession as reform catalyst. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: EBRD and IMF staff calculations.

Thus, prospects of EU Membership have led to more reforms and, as a consequence, to stronger growth (Figure 10).

Figure 10. Market reforms and changes in income levels

10 Figure. Market reforms and changes in income levels. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: EBRD, Total Economy Database and IMF staff calculations.

Countries that upgraded their institutions to EU standards saw a decline in cross-country income differences. Countries that joined the EU in 2000s show clear pattern of convergence. The difference between Bulgaria and Slovenia has narrowed by 15 percent of Slovenia’s GDP since the former begun EU accession negotiations in 2000 (Figure 11, right panel). Similarly, a group of candidate and potential candidate countries, including Croatia (which joined the EU only in 2013) have converged as well (Figure 11, left panel).

Figure 11. Convergence within CESEE regions

11 Figure. Convergence within CESEE regions. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations. Note: The EU has recognized Bosnia and Herzegovina as potential EU candidate countries.

By contrast, there was no convergence among the European CIS-countries. Russia, the richest of CIS countries grew by only 0.6 percent annually since 1989, while output per capita declined in Moldova and Ukraine. Only Belarus achieved growth rates comparable to non-CIS countries, but its largely unreformed economy may have approached the limits of the current extensive growth model (Figure 12).

Figure 12. Convergence in the European CIS region

12 Figure. Convergence in European CIS region. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database and IMF staff calculations.

Countries that have a more completed transition are richer. There is a strong correlation between progress in market reforms and a country’s income level (Figure 13).

Figure 13. Market reforms and income level

13 Figure. Market reforms and income level. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: EBRD, Total Economy Database and IMF staff calculations.

Similarly, richer countries have a more vibrant private sector (Figure 14).

Figure 14. Market reforms and private sector share in the economy

14 Figure. Market reforms and private sector share in the economy. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: EBRD, Total Economy Database and IMF staff calculations.

Correlation does of course not mean causality but is it telling that there is no highly reformed poor country.

Convergence Post-2009 Crisis

Post-2009, catch-up has slowed down. Pre-crisis, convergence was rapid and widespread. In some countries, the GDP per capita gap to the US narrowed by more than 12 percentage points in 2003-08. Since 2010 only two-thirds of countries in the region have continued to catch-up with the US, while Ukraine and Slovenia saw a widening of income differences (Figure 15). And if we include the 2009 crisis, which was deeper in CESEE than in Western Europe, convergence has been even less.

Figure 15. Convergence pace pre- and post-crisis

15 Figure. Convergence pace pre- and post-crisis. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: WEO database and IMF staff calculations.

More recently, there have also been large differences across regions: while the CIS was in recession, the non-CIS countries doing much better.

  • The CIS countries suffered from falling commodity prices, and from the impact of sanction on Russia.
  • By contrast, the non-CIS countries saw a gradual acceleration of GDP growth, on the back of a pick-up of domestic demand in the euro area. Labor markets in many EU New Member States (NMS) are tightening rapidly, and unemployment is quickly approaching pre-crisis lows, though GDP growth rates are well below those in the pre-crisis years.

How can we boost Convergence going forward?[3]

GDP per capita is the product of GDP per worker (labor productivity) and the share of the population that works (the employment rate):

15.2 Formula calculation

Low GDP per capita can thus be the result of both low labor productivity and a low employment rate. In CESEE, both factors play a role:

  • In most CESEE countries, the employment rate is below that in Western Europe (Figure 18). Low employment rates are a particular problem in SEE and some CIS countries.
  • The labor productivity gap with Western Europe is still large, even though it has declined in the past twenty years.

Figure 16. Big differences in growth among regions

16 Figure. Big differences in growth among regions. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: WEO database and IMF staff calculations.

Figure 17. Labor markets in EU new member states

Figure 17. Labor markets in EU new member states. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Eurostat.

Figure 18. Labor utilization and productivity

18 Figure. Labor utilization and productivity. Cross-Country Differences in Convergence in CESEE. FREE Policy paper

Source: Total Economy Database, UN population statistics and IMF staff calculations.

To raise labor productivity more investment is needed.  The capital stock per worker in a typical CESEE economy is only about a third of that in advanced Europe. Domestic saving rare are too low in most the region; policies should, therefore, focus on institutional reforms that reduce inefficiencies and increase returns on private investment and savings.

Boosting total factor productivity (TFP) is important as well. CESEE countries have to address structural and institutional obstacles that prevent efficient use of available technologies or lead to an inefficient allocation of resources. The recent IMF CESEE report suggests the largest efficiency gains are likely to come from improving the quality of institutions (protection of property rights, legal systems, and healthcare); increasing the affordability of financial services (especially for small but productive firms), and improving government efficiency.

Conclusion

Since the fall of communism, there have been large differences in the convergence of income levels with the US among CESEE countries. Much of these differences reflect differences in policies. Countries that reformed more and earlier saw faster growth than countries that reformed less or later. Macro-stability also helped, and countries that avoided boom-busts tended to grow faster.

Continued convergence will require a higher investment, higher TFP, and higher employment rates. The capital stock per worker is still below that in Western Europe. Higher investment rates will require higher saving rates, lest large current account deficits emerge anew. Addressing structural and institutional obstacles would also help convergence, as it will support higher labor force participation and allow for a more efficient allocation of resources.

Notes and References

  • [1] Bas B. Bakker is the Senior Resident Representative and Krzysztof Krogulski an economist in the IMF’s Regional Office for Central and Eastern Europe in Warsaw. The views expressed in this paper are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
  • [2]This is not to say that the rapid and seamless approach was without problems, notably large losses of output and high unemployment in the short run. Thus, reform will always have to worry about the social safety net and, under some circumstances, may benefit from external assistance, which is where the IMF and others can come in.
  • [3]The IMF addressed this question in depth in the spring 2016 issue of “CESEE Regional Economic Issues.”

Disclaimer: Opinions expressed in policy papers and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Financing for Development: Two Years after Addis

Posted on June 12, 2017 | Policy Brief

20170611 Development Day

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.