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Increasing Resources for Families with Children Through the Tax System: Recent Reform Proposals from Poland

Posted on December 2, 2013 | Policy Brief

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This brief discusses the consequences of a recent reform proposal that aims to redistribute resources to low-income families with children through the income tax system in Poland. The proposed reform replaces the current child tax credit with additional amounts of the universal tax credit, and by changing the sequence in which tax deductions are accounted for, it increases resources of low-income families with children by about 1.7 billion PLN per year (0.4 billion EUR). The brief examines four possible ways of additional tax system modifications that would make the reform package neutral for the public finances, and presents distributional implications of the reforms.

The level and structure of financial support for families with children has become an important policy focus in Poland; a country that faces high levels of child poverty and one of the lowest fertility rates in Europe (Immervoll et al., 2001; Haan and Wrohlich, 2011; Eurostat, 2013). In this brief, we outline recent tax reform proposals that aim to increase financial support for low-income families with children through the tax system. A range of such potential reforms has been examined in Myck et al. (2013b); a report prepared for the Chancellery of the President of the Republic of Poland. One of the options became the key element of the President’s family support program Better climate for families proposed in May 2013. Below we discuss its main features and various options for financing the proposals.

The proposed modification of financial support for families would replace the current child tax credit with additional amounts of the universal tax credit conditional on the number of children, and increase tax advantages for families by changing the sequence in which tax credits are accounted for in a way that is favorable for families with children (Chancellery of the President of Poland, 2013). The main beneficiaries of this reform would be low-income families with children whose income is too low to take full advantage of the current child-related advantages. The overall cost of the reform would amount to about 1.7 billion PLN (0.4 billion EUR). In the final section of the brief we discuss potential ways of making the reform budget neutral.

The analysis has been conducted using CenEA’s micro-simulation model SIMPL on reweighted and indexed data from the 2010 Household Budget Survey (HBS) collected annually by the Polish Central Statistical Office (see Morawski and Myck, 2010, 2011; Myck, 2009; Domitrz et al., 2013; Creedy, 2004).

Financial Support for Polish Families in 2013

In Poland, financial support for families with children depends on the level of family income and the demographic structure of the household. The system consists of two main elements – family benefits on the one hand, and tax preferences for families with children on the other. Following Myck et al. (2013a), we define financial support for a family j (FSF_j) as the sum of family benefits received by the family (FB_j), and tax preferences that families with children collect in the PIT system is defined as the difference in the level of tax liabilities and health insurance contributions paid by the family (PITHI_jD0 – PITHI_jDn) supposing they have no children (D0) and on condition them having n number of dependent children (Dn):

FSF_j = FB_j + (PITHI_jD0 – PITHI_jDn) [1]

Figure 1a presents the current level of the financial support for single-earner married couples and Figure 1b presents the same for single parents with one and three children in relation to the level of gross earnings.

Family benefits

Family benefits, which include family allowance with supplements, childbirth allowance and nursing benefits, are means-tested and related to the number and age of dependent children in the family and specific family circumstances. Family benefits are granted only to low-income families and are subject to point withdrawal once the family crosses the income eligibility threshold (539 PLN of net income per person). For example, the stylized married couples in Figure 1 lose family benefits when their monthly gross income exceeds 2,060 PLN if they have one child and 3,435 PLN if they have three children (for single parents these thresholds equal 785 PLN and 1,825 PLN respectively).

Figure 1. Monthly level of financial support received by families with one and three children dependent on their age and family gross income in 2013 (PLN/month)

(a) Married couple with one spouse working

b) Single parent working

Note: FB – family benefits; CTC – child tax credit; joint taxation preferences: UTC – additional amount of universal tax credit; IB – shift of tax income bracket. In case of the single parent alimonies from the absent parent are assumed at the median value from 2010 data, which is 410.50 PLN for 1 child and 724.67 PLN for 3 children. Gross income of the single parent includes income from work only. Alimonies are taken into account for FB income means testing. Source: Myck et al. (2013a).

Tax preferences

Taxpayers with children can deduct a non-refundable child tax credit (CTC) from the accrued tax, with the maximum values of the CTC related to the level of universal tax credit available to all tax payers (UTC is 46.37 PLN per month). For each of the first two children in the family, taxpayers can deduct up to two values of the UTC (92.67 PLN per month), for the third child up to three values (139.00 PLN per month) and for the fourth and following children up to four values of the UTC (185.34 PLN per month). The CTC is not available for high-income parents with one child (whose annual taxable income exceeds 112,000 PLN per year).

Further tax advantages are available for single parents through joint taxation, which translates into substantial gains in particular for high-income parents. As Figure 1 shows, single parents whose gross income exceeds the second tax income bracket (15,745 PLN per month) gain up to 1,044.19 PLN per month if they have one child and 1,368.54 PLN if they have three children. With the same income levels, the system grants nothing to married couples if they have one child and 324.34 PLN if they have three.

In the current system, the CTC can be deducted from the accrued tax only after the full amount of UTC and the tax-deductible part of health insurance (HI) contributions have been exhausted. As a consequence, there is a large group of low-income families whose income is too low to take full advantage of the CTC. As Figure 2 illustrates, the higher the number of children is in a family, the lower is the proportion of families who take full advantage of the credit. Although the percentage of those using the full CTC is 76.1% for families with one child, it decreases to 67.6% for those with two children and is as little as 30.8% for families with three or more kids. Over 40% of the latter use only half of the CTC they are entitled to.

Figure 2. Use of maximum amount of CTC by number of children

Note: Proportions of families with taxable income satisfying other conditions for CTC. Source: Myck et al. (2013a).

Recent Reform Proposals

In a recent report for the Chancellery of the President of Poland, we have analyzed several options for the reform of the family-related elements of the tax system (Myck et al., 2013b). One of these has become the key element of the presidential reform proposal (Chancellery of the President of Poland, 2013). The reform assumes that the CTC is replaced with the amounts of the Universal Tax Credit conditional on the number of children in the family in such a way as to maintain the current maximum advantages offered to families through the CTC system. The main purpose of the reform is to reverse the tax deduction sequence so that tax advantages related to having children are deducted from the accrued tax before considering credits related to health insurance contributions. Such construction would enable low-income families to make greater use of child-related tax advantages, while leaving the situation of higher-income families unchanged.

Figure 3. Monthly tax advantages from the reform among families with 1-4 children (PLN/month)

Source: CenEA – own calculation based on SIMPL model and 2010 HBS data.

Figure 3 presents monthly levels of tax advantages resulting from the proposed reform conditional on the number of children in the family and the level of gross income. We note that families with children gain from the reform if their income exceeds 735 PLN per month. Tax advantages resulting from the proposed modifications are exhausted at different levels of gross income depending on the number of children (from 2,630 PLN for families with one child to 8,010 PLN for those with four children). The higher the number of children is, the greater is also the potential maximum gain – for example, families with four children and income of 4,010 PLN per month would gain up to 311.35 PLN per month.

The results of the analysis show that, overall, 2 million households with children would benefit from this reform (below referred to as System 1). The total annual change in households’ disposable income (equivalent to the total cost for public finances) would amount to 1.69 billion PLN (see Table 1 below).

Table 1. Average annual change in households’ disposable income by number of children in Systems 1-5 (billion PLN)

	No children	1 child	2 children	3+ children	Total
System 1	0,00	0,39	0,60	0,70	1,69
System 2	-0,45	-0,20	0,04	0,55	-0,08
System 3	-0,65	-0,09	0,17	0,59	0,02
System 4	-0,66	-0,15	0,23	0,59	0,01
System 5	-0,86	-0,04	0,31	0,63	0,04

Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).

Table 1 shows that most of the resources would be beneficial for families with three or more children (0.7 billion PLN per year), while families with one or two children would benefit about 0.39 billion PLN and 0.6 billion PLN per year, respectively.

The distribution of total income gains by income deciles is presented in Figure 4. The gains are clearly focused in the lower part of the income distribution. For example, families with children in the second income decile would receive a total of 0.4 billion PLN, while those in the bottom and third decile would recieve approximately 0.25 billion PLN. Only 0.04 billion PLN of the total cost would be distributed to families in the top income decile.

Figure 4. Distribution of total annual gains in households’ disposable income by deciles: Systems 1-5 (billion PLN)

Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).

Potential Ways of Financing the Reform

Concerns about the state of public finances naturally imply questions related to the potential ways of financing any additional tax giveaways. Myck et al. (2013b) presents four alternative modifications of the tax system that make the entire package of reforms neutral for the public finances. These are:

System 2 – CTC reform + limitations on joint-taxation preferences for married couples (both with or without children) and single parents;
System 3 – CTC reform + reduction of tax income threshold from 85,528 to 68,000 PLN per year;
System 4 – CTC reform + reduction of tax revenue costs from 1,335 to 475 PLN per year;
System 5 – CTC reform + reduction of tax-deductible part of health insurance from 7.75% to 7.45%.

The overall total outcomes of these proposals for household disposable income are illustrated in Table 1 and Figure 4. The implications in terms of the redistribution of the packages – with losses among childless households and gains among those with children – are clear under all of the proposed packages, although all of the reform combinations imply small losses also for families with one child. Total disposable income of childless households falls by 0.45 PLN per year under System 2 and by as much as 0.86 billion PLN under System 5. By shifting the majority of the costs to households without children, the latter is simultaneously the most generous for families with children since income of those with two children grows on average by 0.31 billion per year, while of those with more children see a growth of 0.63 billion PLN per year.

Figure 4 illustrates that in all of the revenue neutral reform packages, the households from the highest two deciles are the biggest losers. That the financing of the shift of resources to low-income families falls on households from the top income decile is particularly evident in the case of Systems 2 and 3 where total disposal income for these households fall by 1.64 billion PLN and 1.52 billion PLN, respectively. Since changes to revenue costs and deduction of HI contributions apply to almost all taxpayers, Systems 4 and 5 are less favorable for households from the lower deciles and generate losses for the upper part of the income distribution. However, a large part of cost is also born by households from the tenth decile (0.26 and 0.39 billion PLN, respectively).

While the combinations of tax changes presented above would be neutral with respect to the current system of taxes in Poland, it is worth noting that the policy of tax increases through the tax-parameter freezing implemented in 2009 has increased taxes by far more than the cost of the Presidential reform proposal. As we showed in Myck et al. (2013c), this policy increased taxes by 3.71 billions PLN per year, of which 2.21 billions was paid by families with children. The recent proposal could thus be thought of as a way of redistributing these resources back to families with children.

Conclusions

Financial support for families with children is an important element of government policy with implications for child poverty, labor-market participation among parents, as well as fertility (Immervoll et al., 2001; Haan and Wrohlich, 2011). In this brief, we outlined the results of a recent analysis of direct financial consequences of modifications in the Polish system of support for families through the tax system with the focus on a reform proposal presented by the Polish President in the program Better climate for families. The reform would benefit lower-income families with children at the cost of about 1.7 billion PLN. As a result, annual income of the families from the three bottom deciles would grow by 0.93 billion PLN. A high proportion of the gains (0.7 billion PLN) would go to families with three or more children.

We also presented four additional modifications of the tax system that would make the CTC reform revenue neutral. Reform packages that withdraw joint-taxation preferences and decrease the threshold of the income tax to a higher rate would be most effective in ensuring redistribution of support for low-income households. It is worth noting though, that the recent approach of the Polish government to the tax system has implied substantial increases in the level of income taxes through the freezing of income tax parameters, and these alone would be more than sufficient to finance the proposed tax changes.

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References

Creedy J. (2004). Reweighting Household Surveys for Tax Microsimulation Modelling: An Application to the New Zealand Household Economic Survey. Australian Journal of Labour Economics 7 (1): 71-88. Centre for Labour Market Research.
Domitrz A., Morawski L., Myck M., Semeniuk A. (2013). Dystrybucyjny wpływ reform podatkowo-świadczeniowych wprowadzonych w latach 2006-2011 (Distributional effect of tax and benefit reforms introduced from 2006-2011). CenEA MR01/12; Bank i Kredyt 03/2013.
Chancellery of the President of Poland (2013). Dobry klimat dla rodziny. Program polityki rodzinnej Prezydenta RP. (Better climate for families. Family support program of the Polish President.)
Eurostat online database 2013 – epp.eurostat.ec.europa.eu. Date of access: 28.11.2013.
Haan P., Wrohlich K. (2011) Can Child Care Encourage Employment and Fertility? Evidence from a Structural Model. Labour Economics 18 (4), pp. 498-512.
Immervoll H., Sutherland H., de Vos K. (2001). Reducing child poverty in the European Union: the role of child benefits. In: Vleminckx K. and Smeeding T.M. (eds.) Child well-being, Child poverty and Child Policy in Modern Nations. What do we know? The Policy Press: Bristol.
Morawski L., Myck M. (2010).‘Klin’-ing up: Effects of Polish Tax Reforms on Those In and on Those Out. Labour Economics 17(3): 556-566.
Morawski L., Myck M. (2011). Distributional Effects of the Child Tax Credits in Poland and Its Potential Reform. Ekonomista 6: 815-830.
Myck M. (2009). Analizy polskiego systemu podatkowo-zasiłkowego z wykorzystaniem modelu mikrosymulacyjnego SIMPL (Analysis of the Polish tax-benefit system using microsimulation model SIMPL). Problemy Polityki Społecznej 11: 86-107.
Myck M., Kundera M., Oczkowska M. (2013a). Finansowe wsparcie rodzin z dziećmi w Polsce w 2013 roku (Financial support for families with children in Poland in 2013). CenEA MR01/13.
Myck M., Kundera M., Oczkowska M. (2013b). Finansowe wsparcie rodzin z dziećmi w Polsce: przykłady modyfikacji w systemie podatkowym (Financial support for families with children in Poland: examples of modifications in the tax system). CenEA MR02/13.
Myck M., Kundera M., Najsztub. M, Oczkowska M. (2013c). Ponowne „mrożenie” PIT w kontekście zmian podatkowych od 2009 roku (PIT freezing in the context of tax reforms since 2009). Komentarze CenEA: 06.11.2013.

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* This brief draws on recent research at the Centre for Economic Analysis in the projects financed by the Chancellery of the President of the Republic of Poland and the Batory Foundation (project no: 22078). The analysis has been conducted using CenEA’s micro-simulation model SIMPL based on the 2010 Household Budget Survey data collected annually by the Polish Central Statistical Office (CSO). The CSO takes no responsibility for the conclusions resulting from the analysis. Any views presented in this brief are of the authors’ and not of the Centre for Economic Analysis, which has no official policy stance.

Can Public Enforcement of Competition Policy Increase Distortions in the Economy?

Posted on November 18, 2013 | Policy Brief

High office buildings facing sky representing Institutions and Services Trade

Authors: Vasiliki Bageri, University of Athens, Yannis Katsoulacos, Univeristy of Athens, and Giancarlo Spagnolo, SITE.

Competition law has recently been introduced in a large number of developed and emerging economies. Most of these countries adopted the common practice of basing antitrust fines on affected commerce rather than on collusive profits, and in some countries caps on fines have been introduced based on total firm sales rather than on affected commerce. Based on recent research, this policy brief explains how a number of large distortions are connected to these policies, which may facilitate competition authorities in their everyday job but at the high risk of harming the consumer and distorting industrial development. We conclude by discussing the possibility to depart from these distortive rules-of-thumb opened by recent advancements in data availability and econometric techniques, as well as by the considerable experience matured in estimating collusive profits when calculating damages in private antitrust litigation.

Competition policy has become a prominent policy in many developing economies, from Brazil to India. Indeed, the available evidence suggests that in countries where law enforcement institutions are sufficiently effective, a well designed and enforced competition policy can significantly improve total and labor productivity growth.

It is already well known that the private enforcement of competition policy can give rise to large distortions: since competition law is enforced by Judges and not by economist, it is easy for firms to strategically use the possibility to sue under the provision of competition law to protect their market position rather than the law being used to protect competition.

It is somewhat less known that a poor public enforcement of Competition Law by publicly funded competition authorities can also end up worsening market distortions rather than curing them. In the reminder of this policy brief we explain why, according to recent research, a mild and suboptimal enforcement of antitrust provisions – in the sense of fines that are too low to deter unlawful conduct (horizontal agreements and cartels in particular) and fines which are based on firm revenue rather than on the extra profits generated by the unlawful conduct, could significantly harm social welfare, even if we abstract from the direct cost the public enforcement of competition law imply for society.

Current Practice in Setting Fines

A very important tool for the effective enforcement of Competition Law is the penalties imposed on violators by regulators and courts. In this policy brief, we uncover a number of distortions that current penalty policies generate, we explain how their size is affected by market characteristics such as the elasticity of demand, and quantify them based on market data.

In contrast to what economic theory predicts, in most jurisdictions, Competition Authorities (CAs), but also courts where in charge, use rules-of-thumbs to set penalties that – although well established in legal tradition and in sentencing guidelines and possibly easy to apply – are hard to justify and interpret in logical economic terms. Thus, antitrust penalties are based on affected commerce rather than on collusive profits, and caps on penalties are often introduced based on total firm sales rather than on affected commerce.

A First Well Known Distortion Due to Legal Practice

A first and obvious distortive effect of penalty caps linked to total (worldwide) firm revenue is that specialized firms which are active mostly in their core market expect lower penalties than more diversified firms that are also active in several other markets than the relevant one. This distortion – why for God’s sake should diversified firms active on many markets face higher penalties than more narrowly focused firms? – could in principle induce firms that are at risk of antitrust legal action to inefficiently under-diversify or split their business to reduce their legal liability.

In a recent paper published in the Economic Journal, we examine two other, less obvious, distortions that occur when the volume of affected commerce is used as a base to calculate antitrust penalties.

A Second Distortion: Poorly Enforced Competition Law May Increase Welfare Losses from Monopoly Power

If expected penalties are not sufficient to deter the cartel, which seems to be the norm given the number of cartels that CAs continue to discover, penalties based on revenue rather than on collusive profits induce firms to increase cartel prices above the monopoly level that they would have set if penalties were based on collusive profits. Intuitively, this would be done in order to reduce revenues and thus the penalty. However, this exacerbates the harm caused by the cartel relative to a monopolized situation with similar penalties related to profits, or even relative to a situation with no penalties due to the distortive effects of the higher price and, in comparison to a situation with no penalties, the presence of antitrust enforcement costs.

A Third Distortion: Firms at the Bottom of the Value Chain May Pay a Multiple of the Fine Paid by Firms at the Top for an Identical Infringement

Firms with a high revenue/profit ratio, e.g. firms at the end of a vertical production chain, expect larger penalties relative to the same collusive profits that firms with a lower revenue/profit ratio would get. Our empirically based simulations suggest that the welfare losses produced by these distortions can be very large, and that they may generate penalties differing by over a factor of 20 for firms that instead should have faced the same penalty.

Note that this third distortion takes place also when at least for some industries fines are sufficiently high to deter cartels. This distortion means that competition is only enforced in industries that happen to be in the lower end of the production chain, and not in industries where the lack of competition is producing larger social costs. Note also that our estimation is based only on observed fines, i.e. on fines paid by cartels that are not deterred. Since cartels tend to be deterred by higher fines, this suggest that if we could take into account the fines that would have been paid by those cartels that were deterred (if any), the size of the estimated distortion would likely increase!

Concluding remarks

We argue that if one wants to implement a policy, one must be ready to do it well otherwise it may be better to not do it at all. This is particularly relevant for countries with weaker institutional environments where it is likely that political and institutional constraints will not allow for a sufficiently independent and forceful enforcement of the Competition Law.

It is worth noting that – in particular in the US but also increasingly so in the EU – the rules-of-thumb discussed above do not produce any saving in enforcement costs because the prescribed cap on fines requires courts to calculate firms’ collusive profits anyway. Furthermore, the distortions we identified are not substitutes where either one or the other is present. Instead, they are all simultaneously present and add to one another in terms of poor enforcement.

Where there are sufficient resources to allow for a proper implementation and where enforcement of Competition Law is available, developments in economics and econometrics make it possible to estimate illegal profits from antitrust infringements with reasonable precision, as regularly done to assess damages. It is time to change these distortive rules-of-thumb that make revenue so central for calculating penalties, if the only thing the distortions give us is savings in the costs of data collection and illegal profit estimation.

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Managed Competition in Health Insurance Systems in Central and Eastern Europe

Posted on October 28, 2013 | Policy Brief

This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.

A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).

This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.

The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.

Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia

At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).

The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).

However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).

In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).

Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions)

This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.

Data and Results

In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model. The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).

The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).

Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).

Table 1. Factors leading to decreased infant and under-five mortality in Russia

Notes: * indicates that the coefficient is statistically significant in a parametric regression

Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.

To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)

In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.

Discussion

The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.

In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.

Summary and Policy Implications

The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.

▪

References

Balabanova D, Roberts B, Richardson E, Haerpfer C, McKee V. 2012. Health Care Reform in the Former Soviet Union: Beyond the Transition. Health Services Research 47(2): 840-864.
Baranov IN, Sklyar TM. 2009. Problemy strakhovoi modeli zdravookhraneniya na primere Moskwy i Sankt-Peterburga (Problems of insurance model in health care: the example of Moscow and Saint Petersburg). In X International Conference on the Problems of Development of Economy and Society, Yasin E.G (ed), Moscow: Higher School of Economics, vol.2.
Besstremyannaya GE. 2013. Razvitie systemy obyazatelnogo meditsinskogo strakhovaniya v Rossijskoi Federatsii (Development of the Mandatory Health Insurance system in the Russian Federation) Federalizm 3: 201-212
Besstremyannaya GE. 2010. Essays in Empirical Health Economics. PhD thesis. Keio University (Tokyo).
Besstremyannaya GE. 2009. Increased public financing and health care outcomes in Russia. Transition Studies Review 16: 723-734.
Blam I, Kovalev S. 2006. Spontaneous commercialization, inequality and the contradictions of the mandatory medical insurance in transitional Russia. Journal of International Development 18: 407–423.
Culyer AJ (2005) The Dictionary of Health Economics, Edward Elgar.
Danishevski K, Balabanova D, McKee M, Atkinson S. 2006. The fragmentary federation: experiences with the decentralized health system in Russia. Health Policy and Planning 21: 183–194.
Gordeev VS, Pavlova M, Groot W. 2011. Two decades of reforms. Appraisal of the financial reforms in the Russian public healthcare sector. Health Policy 102(2-3): 270-277.
Hussey P, Anderson GF. 2003. A comparison of single- and multi-payer health insurance systems and options for reform. Health Policy 66: 215-228.
Jacobs R, Goddard M. 2002. Trade-offs in social health insurance systems. International Jthenal of Social Economics 29(11): 861-875.
Lawson C, Nemec J, Sagat V. 2012. Health care reforms in the Slovak and Czech Republics 1989-2011: the same or different tracks? Ekonomie a management 1, 19-33.
Lawson C, Nemec J. 2003. The political economy of Slovak and Czech health policy: 1989-2000. International Political Science Review 24(2): 219-235.
Medved J, Nemec J, Vitek L. 2005. Social health insurance and its failures in the Czech Republic and Slovakia: the role of the state. Prague Economic Papers 1:64-81.
Praznovcova L, Suchopar J, Wertheimer AI. 2003. Drug policy in the Czech Republic. Jthenal of Pharmaceutical Finance, Economics and Policy 12(1): 55-75.
Preker AS, Jakab M, Schneider M. 2002. Health financing reforms in Central and Eastern Europe and the former Soviet Union, in Funding Health Care: Options for Europe, Mossalos E., Dixon A., Figueras J., Kutzin J. (Eds.), European Observatory on Health Care Systems Series: Open University Press, 2002.
Rokosova M, Hava P, Schreyogg J, Busse R. 2005. Health care systems in transition: Czech Republic. Copenhagen, WHO Regional Office for Europe on behalf of the European Observatory on Health Systems and Policies.
Sheiman I. 1991. Health care reform in the Russian Federation. Health Policy 19: 45–54.
Sheiman I. 2006. O tak nazyvaemoi konkurentnoi modeli obyazatelnogo meditsinskogo strahovaniya (On so-called competitive model of mandatory health insurance). Menedzher Zdravoohraneniya 1: 52-58.
Sheiman I. 1997. From Beveridge to Bismarck: Health Financing in the Russian Federation’. In Innovations in Health Care Financing, Schieber G. (ed.), Discussion Paper 365, 1997, Washington DC: The World Bank.
Sinuraya T. 2000. Decentralization of the health care system and territorial medical insurance coverage in Russia: friend or foe? European Jthenal of Health Law 7:15–27.
Sparling AS. 2008. Income, drug, and health: evidence from Russian elderly women. PhD dissertation. University North Carolina at Chapel Hill, UMI Dissertations Publishing.
Tompson W. 2007. Healthcare reform in Russia: problems and perspectives. Working Papers 538, OECD Economics Department
Tragakes E, Lessof S. 2003.Russian Federation, Health Care Systems in Transition, The European Observatory, WHO, Europe.
Twigg J. 1999. Obligatory medical insurance in Russia: the participants’ perspective. Social Science and Medicine 49: 371–382.
Twigg, JL. 2001. Russian healthcare reform at the regional level: status and impact. Post-Soviet Geography and Economics 42: 202–219.
Zaborovskaya AS, Chernets VA, Shishkin SV. 2005. Organizatsiya upravleniya i finansirovaniya zdravoohraneniyem v subjektah Rossijskoi Federatsii v 2004 godu (Organization of management and finance of healthcare in Russian regions in 2004)
Zweifel P, Breyer F. The economics of social health insurance. In The Elgar Companion to Health Economics, Jones A. (ed.), Edward Elgar, 2006.
Wagstaff A. 2010. Social health insurance reexamined. Health Economics 19: 503–517.

Some More Reflections on RCTs

Posted on October 14, 2013 | Policy Brief

In preparation of next year’s elections, the Swedish government chose recently to replace the Minister for International Development Cooperation. During her long mandate, former Minister Gunilla Carlsson championed the importance of aid evaluation and result focus, and managed to move aid from a quiet consensus to become a hotly debated topic. She also closed down the aid evaluation agency SADEV, following the publication of critical reviews about the work of the agency. Now, an expert group is in charge of rethinking and redesigning development policy evaluation and planning. One of the tools under consideration is randomized control trials (RCTs). This is an area in which Swedish development cooperation has no previous experience. Here are some reflections on RCTs.

In recent years, the methods of development economics have been crucially altered by the introduction of randomized control trials (RCTs). The idea behind RCTs is that development policies can be evaluated similarly to clinical trials in medicine, where subjects are randomly assigned to receive a treatment or to function as a reference or control group. The main benefit of this approach is that the random assignment allows for an estimation of the effect of the treatment (that is, the policy in question), while avoiding unobservable confounding factors or selection issues (see more about the advantages of the method in Banerjee et al. (2008)).

The diffusion of experimental methods in development economics has undoubtedly been a revolution in the academic and, if not yet fully, in the policy world. In the blogosphere there has even been talk of awarding Sveriges Riksbank’s Prize in Economic Sciences in Memory of Alfred Nobel, informally called the Nobel Prize of Economics, to the MIT couple Banerjee – Duflo. Due to their young age and the closeness in time of their contribution, this would be a ”shock” prize meant to give a strong signal. Their creation, the Abdul Latif Jameel Poverty Action Lab (J-PAL), stands for a new approach to both scientific and policy work in development that is a fantastic contribution, and definitely has the connotation of seminal.

However, it might be too early for the profession to sanction a method that has much good to show for, but also potentially undesired consequences. In the camp of critics there are heavy weights such as Angus Deaton and Dani Rodrik of Princeton, and the World Bank’s Philip Keefer and Martin Ravallion. The core of their position is of course not to deny the merits of RCTs, but to advocate their use in the right way and, in particular, as one tool among many others, with important complementarities to the others.

Some points in this context are often made, well understood and widely accepted: the limits of the approach per se, in particular the problem of external validity (the question of how generally applicable are the findings from such studies); the conflict between short-run and long-run implications, especially with respect to some policy areas (support to institution-building among others), and the incentives of policy actors. Another brief in this series by Anders Olofsgård spells out these points very clearly and references to further readings for those interested.

One aspect I find to be missing in the debate is a reflection on what impact this new method has on the three main actors involved, namely the researchers and practitioners in development and their way of working, and the people living in the countries and regions where these studies take place. This will therefore be the focus of this brief.

The Impact on the Scholarly Profession

The creation of experimental infrastructures and the popularity of the RCT methodology have rubbed off on the rest of the empirical practice in development economics and beyond, with ever-increasing demands and expectations on the econometric identification of new studies. However, when it comes to what is possibly the main weakness of RCTs as compared to most observational studies, namely external validity, the corresponding demands and expectations on how this is dealt with seem to fall behind. As pointed out in Rodrik (2008), it is enough to compare the number of pages spent on describing the identification in an average observational study to that on external validity in an average RCT-based paper. If the purpose is to learn “what works in development”, as opposed to “what worked once for a set of 25 primary schools in Uttar Pradesh faced with high drop out rates” [1], it is natural to expect the researcher that really wants to serve this purpose to provide for a desired generality of her findings. With no generality, the findings may be of limited practical use to politicians and practitioners who need to choose a policy tool or make a decision in conditions, which are likely to differ from the exact setting of the study.

During a recent presentation by one of the most active and prominent RCT researchers, the researcher clearly stated at some point that: “[t]his intervention was never thought for scaling up as a policy.” That made me pause. But what is the purpose, then? In my meaning, these studies should fit into a “bigger-picture” understanding, or at least hypothesizing on how development works, what the binding constraints and open challenges are, what might contribute to overcoming them, and how do we proceed from there. Once some candidates are identified, RCTs might, depending on the setting, be used to evaluate and compare before and after the preferred policy is implemented. Unfortunately, this attitude is far from common, beyond what has become the standard of the ‘Introduction paragraphs’.

Quite often RCT studies are extremely precise and accurate on “the impact of X on Y”, even in cases of very small effects, and can be perhaps a bit vague or face bigger uncertainties on the ‘bigger’ question. This means that many, more general (and very relevant) questions are not addressed by development economists just because a RCT is not feasible. An example mentioned in a recent keynote lecture by David Laitin is the BetterBirth Project. This is a WHO program that seems to be making a big difference for infant and maternal health in India’s poorest states through a list of 29 easy, low-cost, low-technology and well-known practices. The main lesson drawn by observers at the Harvard School of Public Health is that people follow the list more accordingly when it is spread through ”human contact”. No mass media advertisement campaign, no punishment or incentive schemes, just ”nice” people visiting, explaining, and demonstrating the list, while – in the words of an interviewed nurse – ”smiling a lot”. At first sight, this seems like something that could be randomized. However, the treatment is so diffuse and fuzzy that the practical implementation would be very challenging. If it is the case that the person meeting the clinics’ personnel and spreading the information has to be somewhat of a mentor in order for the transition to happen, to be kind and pedagogic, repeat the visits indefinitely to make sure that the practices have been adopted, and do whatever else it takes to make them learn, this is very hard to observe with precision. To simply define X as ”presentation of the list in person”, to be compared to, for example, the ”diffusion of the list through an information campaign” would probably run the risk of severely underestimating the impact. This would be because it would bundle together different types of informers and different levels of human interaction. This means that there would be a high risk of zero or insignificant results from such a study. A RCT would need to be complemented by other investigations, for example surveys, in order to find out if there really was an effect and how it came about. All of the above is likely to undermine the publication chances for an academic paper on the issue, thereby discouraging development scholars to study this program.

There are two main ways of augmenting the RCT methodology in the direction of generalizability and external validity: the elbow-grease approach of replication and the resuscitation of the concern for theoretical mechanisms. Replication studies are not very appealing in the perspective of a scholar that aspires academic publications. Besides completely new clever designs that establish a link of causation in a specific case – and possibly for each of these corresponding studies that establishes the absence of such a link in different settings – journals have little interest in publishing more variations on the same theme. Replications with small variations should instead be highly attractive for development institutions and practitioners, precisely for the reason, mentioned above, that they want to learn about effectiveness of alternative strategies in as many different specific contexts as possible. [2] In an ideal world, development institutions and aid bureaucracies would work in close cooperation with universities and academic institutions, involving young researchers before their career-concern-stress phase (perhaps Ph. D. students?) in the design and evaluation of as many of their planned interventions as possible. Moreover, in an ideal world this would be enough reward for the young researchers. This wealth of replications would then favor the possibility of “taking stock” and really learning about some general truth. I do not, however, have a good recipe for making this happen.

Luckily, some scholars are in the meanwhile working on making the pendulum swing back from the purest empiricism to the involvement with theory. Here is a list of possibilities that are important to reflect about, starting from a given RCT:

– The macro problem. How does the found effect compare to the “bigger issue”, the one that most likely set the scene in the ‘Introduction paragraph’ of the study? Few studies go back to this point, after presenting their results. Numerical simulations or structural estimation of theoretical models might help answering this question. (See some examples in Buera et al. (2011) and Kaboski et al. (2011)).

– The alternative hypothesis. What is the particular intervention compared against? If the set of circumstances or policy-relevant parameters that might be varied are too big or too dense for replications, maybe a theoretical model can help to vary them in a smooth and continuous way?

– The strategic reaction. How are the involved economic agents likely to respond in case of an expansion in space, time or both, of the intervention? How would they have responded in the absence of the intervention?

The Impact on Development Practices

As stated above, RCTs may be a powerful tool for the learning and decision-making in development institutions, public or private. However, this assumes a seldom-questioned willingness to learn and change practices on their part. Brigham et al. (2013) show, through a RCT, that these organizations might be subject to confirmation bias. Brigham et al. sent out an invitation to microfinance institutions, offering partnership to evaluate their programs, randomly accompanying it with a survey of previous studies finding positive impact of microcredit, or a survey of studies finding no impact. The second treatment elicited barely half as many responses as the first one, which suggests that at least this type of organizations might not be so interested in learning whether what they do is effective or can be improved. Coupled with the mentioned publication bias, this might skew the distribution of reported, published and established findings even further.

The Impact on the Local Context

Individual studies can of course be affected by the so-called Hawthorne effect or experimenter effect. The phenomenon, by which the act of being experimented upon changes a subject’s behavior, was first observed and got its name in the 1920s in industrial psychology. Although it is clearly hard to establish, it has for decades been a central criticism of the ”participant observation” methodology in anthropology and ethnography. Also behavioral economists, that more recently started using experiments both in labs and in the field, are explicitly careful about it.

Depending on the definition of causality that the researcher has in mind, the fact that having knowledge about being treated impacts outcomes, might not be an issue at all for the measurement of the overall effect of an intervention. The overall effect should include also the (optimal) reaction of the agents (for example a change in behavior, the adoption of other complementary inputs, etc.) and this is actually considered one of the advantages of the method. However, this raises problems for the interpretation of the size of the effect and the analysis of the channels that bring it about. This point is made very clearly by Bulte et al. (2012), who compare a double-blind RCT with a regular one. If all or most of the effect simply comes from the participants knowing to be ”treated” and reacting to it, is the effect still going to be there when the intervention becomes a regular policy? The majority of both authors and critics mostly ignore this important question.

Beyond the perspective of a single study, a different concern comes to mind when considering how a substantial number of RCT studies are clustered geographically. The map below shows a snapshot of the J-PAL interventions in Africa and Asia, which are only a fraction, albeit substantial, of the total.

Figure 1. J-PAL Interventions in Africa and Asia

Reading study after study set in Kenya, or some Indian state, I wonder if people there are starting to get used to private organizations going around giving away assets, or used to temporary local government programs with funky benefit schemes. To my knowledge, no study has yet reflected upon the aggregate impact of experiments and randomized interventions in an area that has many. Might it be the case that exposure to many conditions eventually results in ”experimental fatigue”, or practice effects, which may influence the results of the studies and make the interpretation of the findings difficult?

Even more worrisome, given the frequency of and the resources involved in these interventions, perhaps we should expect an impact on the local political economy. As a parallel, I think about the agrarian reform and the later establishment of the welfare state in post-war Italy, and how they gave major local actors the ability to uphold their clientelistic systems. The newly established rights and entitlements, the various benefits and redistribution programs, were ”filtered” by the local elites and channeled through the traditional ties of family, kinship, friendship and neighborhood. According to comparative analyses of European welfare regimes, clientelism exists, in different forms and intensities, in all Mediterranean welfare states, and it appears to be linked to the process of political mobilization and the establishment of welfare state institutions in these nations.

A recent study by Ravallion et al. (2013) finds that unemployed fail to act on information about the National Employment Guarantee Scheme (NEGS) in India. They hypothesizes that the bottleneck lies with the local government institutions (Gram Panchayats). The GP are supposed to receive the applications and apply for central government resources for planning and implementation of projects, so as to guarantee 100 days of work per year to all adults from rural households who are willing to do unskilled manual labor at the statutory minimum wage. But perhaps – argue the authors – given the strict controls on corruption, the GP officials do not find anything in it for themselves, and hence do not proceed. Of course this is just one of the possible explanations, and moreover the NEGS is not a RCT. But in general the involvement of local official or unofficial power structures in contexts where this type of interventions are increasingly common could be interestingly related to the hypothesis on the ”Mediterranean welfare state” outlined above. The idea definitely deserves investigation.

Conclusions

The popularity of RCTs among development scholars is finally spreading to practitioners. This is mostly good news, there is much to gain and learn from this approach, especially in contexts where it is grossly underexploited, as has been the case in Sweden. However, a near-monopoly of this approach is though not granted, given its non-negligible limitations, often belittled in light of its numerous strengths. Spurring development “one experiment at a time” might take unnecessary extra time and efforts, and bring about other undesirable consequences. Both development scholars and practitioners should not forget the other arrows in their quiver.

References

Bannerjee, A. and E. Duflo (2008), “The Experimental Approach to Development Economics”, NBER Working Paper 14467.
Brigham, Matthew, Michael Findley, William Matthias, Chase Petrey, and Daniel Nelson. ”Aversion to Learning in Development? A Global Field Experiment on Microfinance Institutions”. Technical Report, Brigham Young University March 2013.
Buera, F. J., J. P. Kaboski, and Y. Shin (2011). ”The macroeconomics of microfinance.”
BREAD working paper.
Bulte, E., Pan, L., Hella, J., Beekman, G. and S. di Falco (2012). ”Pseudo-Placebo Effects in Randomized Controlled Trials for Development: Evidence from a Double-Blind Field Experiment in Tanzania.” Working Paper.
Kaboski, J. P. and R. M. Townsend (2011, July). ”A structural evaluation of a large-scale quasi-experimental microfinance initiative.” Econometrica 79, 1357–1406.
Olofsgård, A. ”What Do Recent Insights From Development Economics Tell Us About Foreign Aid Policy?” FREE Policy Brief Series, October 3, 2011.
Ravallion, M., et al. ”Try Telling People their Rights? On Making India’s Largest Antipoverty Program work in India’s Poorest State.” Department of Economics, Georgetown University, Washington DC (2013).
Rodrik, D. (2008). ‘The New Development Economics: We Shall Experiment, but How Shall We Learn?’. Harvard Kennedy School Working Paper No. RWP08-055.▪

[1] The example is fictitious. Any resemblance to real studies is unintended and purely coincidental.

[2] At least in theory – this point is discussed more in the next section.

Development Policy After the Millennium Development Goals: Where Do We Go From Here?

Posted on September 16, 2013 | Policy Brief

20130916 Development Policy After the Millennium FREE Network Policy Brief Image 01

This policy brief reports on a discussion of the Post-2015 Development Agenda held during a full day conference at the Stockholm School of Economics on August 23, 2013. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs and was the third installment of Development Day, a yearly development policy conference. The Millennium Development Goals established in year 2000 has been an essential concept for global and national efforts to promote economic, social and human development. Highlighting income poverty, health, education, gender equality and environmental sustainability, the targets have focused global efforts on a set of quantifiable and comparable measures of progress. The question for the development community as these goals reach their endpoint is how to build a successful agenda for the future beyond year 2015. To discuss this challenging question, the conference brought together a distinguished and experienced group of policy oriented scholars and practitioners from governments, International Financial Institutions, the business community as well as NGOs.

In September 2000, world leaders adopted the United Nations Millennium Declaration, committing their nations to a global partnership to reduce extreme poverty. The declaration defined eight time-bound targets expiring in 2015, the so-called Millennium Development Goals (MDGs). These goals specify areas of focus; eradicate extreme poverty and hunger, achieve universal primary education, promote gender equality and empower women, reduce child mortality rates, improve maternal health, combat HIV/AIDS, malaria and other diseases, ensure environmental sustainability, and develop a global partnership for development. They also set explicit targets such as halving the number of people living on less than US$ 1.25 a day and reducing maternal mortality by three quarters from 1990 to 2015. Some commendable success has indeed been realized; already in 2010 the worldwide goal to reduce by half the proportion of people living on less than US$ 1.25 a day was achieved. However, much less progress has been seen in some other areas, including maternal health, and there are countries for which none of the goals are expected to be achieved by 2015. Nevertheless, the use of quantifiable, comparable and time-bound targets to create awareness and direct political resources is generally regarded as a success. The question for the development community as 2015 quickly approaches is thus how to build a successful post-2015 development agenda that builds on what has worked but also incorporates areas identified as missing.

The process to establish a new agenda of course raises many questions and reveals some of the trade-offs involved. There seems to be a consensus that the Millennium Declaration and the MDG framework should serve as a starting point, but there are many details to pin down. For instance, there are important challenges not directly mentioned in the original eight goals such as political conflict, rising inequality and youth unemployment. Many also argue that environmental sustainability, though included, may deserve a more prominent role in the future agenda. On the other hand, loading the Agenda with more and more goals may also dilute the global effort across too many areas, and some scholars argue that the whole idea with specific goals is counterproductive based on an organic view of development ill-suited for social engineering from above. To protect credibility, it is also important to get a sense of what is realistic to aim for, and what responsibility to ascribe to the already developed world. Moreover, even if a consensus can be reached with regards to the goals, opinions on how to best reach those goals will most definitely vary widely.

To get the process towards a new agenda started, the UN Secretary General has launched several initiatives including task teams, special advisors and consultations, but also a High-level Panel of Eminent Persons co-chaired by the Presidents of Indonesia and Liberia, and the Prime Minister of the United Kingdom; also including as its member Gunilla Carlsson, Swedish Minister for Development Cooperation. The panel, led by executive secretary and lead author Homi Kharas, submitted a report to the Secretary General on May 31. The program of Development Day 2013 started with a presentation of the report by Dr. Kharas, and remarks from Minister Carlsson. This was followed by an academic session corroborating projections of the report and outlining its limitations, and two panel discussions on sustainable development and Sweden’s potential as a leader in this process. Below follows a short representation of the main arguments and debates of the day.

A New Global Partnership: Eradicate Poverty and Transform Economies through Sustainable Development

Homi Kharas, Senior Fellow and Deputy Director at the Brookings Institution, presented the main messages contained in the report in the first session. An analysis of the situation since year 2000 shows many positive signs such as high global economic growth; increased international connectedness; a reduction in global inequality; and a substantial drop in absolute poverty rates. However, there are also many challenges ahead; rapid population growth, political conflicts, and the fact that the majority of the extremely poor live in conflict zones, increasing urbanization, a deteriorating environment and dwindling aid flows. This, in turn, leads Dr. Kharas to conclude that ‘business as usual’ is no longer feasible, and a new framework replacing the MDGs is needed.

The report seeks to address these issues and is conceived to serve as a set of guidelines, new goals and targets for the UN Secretary General and for the UN member states for the post-2015 period. At the core of the report is a bold aspiration to eradicate absolute poverty by 2030 through a unified framework of sustainable economic growth, increased social equality and environmental sustainability, and a new global partnership paradigm. This universal agenda, in turn, is proposed to be reached via five paradigm shifts to the status quo, (i) universal inclusion and equality, (ii) environmentally sustainable development, (iii) a transformation of national economies for sustainable growth, (iv) peace and effective, transparent public institutions, and (v) a new and more inclusive global partnership. In the report these broad and major shifts are further delineated across 12 illustrative targets, which, if met, will directly affect more than two billion people across the world and would require about $30 trillion spent by the governments worldwide.

Dr, Kharas emphasized that the report was prepared in cooperation with 5000 civil organizations, 250 large international corporations, and thematic, regional and country consultations all over the world, with another one million people taking part in an online questionnaire. He stressed that this kind of broad cooperation and consultation is needed to implement the goals set by the report and especially to operationalize these goals at the level of each of the member states.

Gunilla Carlsson, Swedish Minister for International Development Cooperation and a member of the UN High-Level Panel, continued the discussion and commended the members of the Panel on the impressive amount of work put in the report. She also emphasized the universal character of the agenda presented in the report, largely applicable both to developing and developed countries.

Carlsson stressed what she identified as the core values of the report; eradication of extreme poverty, prevention of violence and conflict, and inclusive peace. She further underlined the importance of local and global partnerships across governments, business communities and civil society. Broader public-private partnerships are essential both for fostering innovation in development work and to guarantee sufficient amounts of financing. The exact design of such a framework, however, is still an open question, but she hopes Sweden can serve as a leading example.

Both Homi Kharas and Gunilla Carlsson also showed great optimism when asked about the potential to implement the substantive initiatives by 2030. They stressed that not only does the world at present have more resources and more aid flows than it ever have, but the international community, including both public and private actors, is also showing more willingness to help the developing countries integrate successful development models than ever before.

Comments and Reflections

Martin Ravallion, Edmond D. Villani Professor of Economics at Georgetown University, started the commentary and reflection session. He showed how there is a strong current trend of between-country convergence of inequality rates (more equal countries becoming more unequal, while more unequal countries are becoming more equal) and declining poverty rate. The latter decline is to a considerable extent driven by Chinese economic growth, but this is far from the only source. He also underlined that the rate of poverty reduction has increased since the adoption of the MDGs in the 2000s, but said it was too early to judge the success or failure of the MDGs on these grounds.

Based on current trends, Ravallion also presented some estimates of the possibility to achieve the core objective of the report, eradication of absolute poverty by 2030. From a broad range of alternatives, the best case scenario, based on 3% annual growth rates of the world economy, absence of major economic crises and at least not decreasing participation of the poor in the benefits of growth, estimated a fall in absolute poverty rates from about 19% at present to 3% by 2030. In a less optimistic scenario, but historically not unlikely, levels of inequality and poverty would fall at a much slower rate, causing 12% to 14% of the world population to live below the absolute poverty line by 2030. Thus, the conclusion is that total eradication of absolute poverty by 2030 is hardly achievable, but substantial progress can be made, and it depends critically on continued high levels of world economic growth.

Professor Ravallion also stressed that these projections were made possible through a recent revolution in data availability, something the High Level Panel was asking for. To a large extent, this is attributed to a massive data collection effort by the World Bank, which not only provided better coverage of countries around the world, but also allowed for deeper insights into the nature of extreme poverty, including re-calculations and harmonization of cross-country comparable Purchasing Power Parity consumption baskets. This revolution provided more reliable inputs for his prediction models and improved the precision of estimates considerably.

Owen Barder, Senior Fellow and Director for Europe at the Center for Global Development, further emphasized this importance of credible statistics. Barder was somewhat skeptical to the report’s claim to be bold and offering a new approach, arguing that it largely reiterated the goals (jobs for young people, partnership with the private sector, reform of the financial system, etc.) already in the Millennium Declaration from year 2000. He also argued that the claim of success for the MDGs is almost entirely made on the basis of paragraph 19 of the Declaration; the objective to reduce by half the number of people living in absolute poverty. Much less progress has been made on the other explicit objectives, and all other aspects emphasized in the Millennium Declaration but which were not necessarily a part of the MDGs.

Barder suggested that there is too little effort to consistently measure whether rich countries are playing their part in the global partnership. Against that background he presented some preliminary results on the last round of the Center for Global Development’s Commitment to Development Index, calculated on the basis of OECD counties’ participation in aid, trade, investments, migration, environment, security and technology transfers. Over the last 10 years, OECD countries demonstrated on average a modest increase from four to five points on a ten-point scale, with Sweden ranked third from the top with a score of 7.2 for 2011 and 6.8 for 2012. Interestingly enough, this deterioration in the index for Sweden is mainly due to deterioration in the security component of the index, in turn resulting from larger sales of arms to undemocratic regimes, and from decreasing aid and immigration. There is obviously variation across countries, but on average there is scant improvements during the 13 years since the Millennium Declaration. This led Barder to question whether the developed countries have contributed their share to the objective of ending poverty, or if too much of the heavy lifting is left for the developing countries.

Barder concluded the presentation by pointing out the difference in language used in the report, namely the imperative used in the parts of the report describing recommendations for the developing countries, and the subjunctive used for recommendations for the developed countries. Again, to him this difference signaled the need to re-emphasize the importance of political commitment and operational goals also for the already developed countries in the Post-2015 Agenda.

Johan Rockström, Executive Director at the Stockholm Resilience Centre, started out noting that the population of the world is estimated to increase to eight billion people by 2030 and to nine billion by 2050. This, in combination with the currently prevailing development paradigm that emphasizes short-term economic growth over long run sustainability, causing degradation of biodiversity and climate change, means that we are hitting the planetary ceiling of eco-capacity. This suggests that ‘business as usual’ is no longer an option, and a new development paradigm is needed.

To address this issue, Rockström formulated a set of goals for human development balancing the needs of the environment, the needs of society and the needs of the people, all within the Earth’s life-support system. He proposed a broader framework for thinking about these issues, the so-called Sustainable Development Goals (SDGs rather than MDGs), which rebalances the relative weight on environmental, human and economic development with relatively more emphasis on the first two. This approach unifies the MDGs with planetary necessities (material use, clean air, nutrient and hydrological cycles, biodiversity, and climate stability), and sustainable development goals (sustainable food and water security, universal clean energy, governance for sustainable societies, etc.).

Discussion Panels

The first panel of the day focused on issues of sustainable development and was started by Klas Waldenström, Senior Advisor on the Post-2015 Development Agenda at Sida. He argued that the main challenge to the new partnership paradigm discussed earlier, will be the creation of trust both across nations and across the private and public sectors. Referring to the experience of Sida, he cited the successful creation of a network of 25 private Swedish companies focusing on models of sustainable development. An important role of official foreign aid in these partnerships, he argued, was to blend direct financial transfers with a combination of political support and business sector outreach, thereby potentially leveraging the financial flows with alternative sources of capital.

David Fergusson, Deputy Director at the Office of Science and Technology at USAID, called for more and better data in order to be able to operationalize and evaluate the new strategies that hopefully will come out of the report. He also reiterated the importance of transformative solutions for sustainable development and the need to understand that ‘business as usual’ is no longer an option. He also referred to the successful cooperation between Sida and USAID as an example of international collaboration of a new kind, more of which will be needed in the future to overcome the status quo and achieve the goals put forward by the report.

Garry Conille, Special Advisor to President Ellen Johnson Sirleaf of Liberia and UNDP, discussed his experience of working with the MDGs and stressed that possibly the most challenging part was the negotiation between different stakeholders to reach a set of issues well-defined and contained enough to be operational. From his point of view, the major challenge is the operationalization of the rather opaque and broadly defined MDGs and how to find a proper allocation of resources across the many commendable ambitions. He therefore called for an effort to make the post-2015 agenda more practical.

The issue of operationalization was discussed further by Stefano Prato, Managing Director at the Society for International Development. He argued that with such large shifts proposed by the post-2015 agenda, it is perhaps difficult to understand how to work with the vision put forward by the panel. His suggestion for the Panel was to dig deeper into the challenging areas of the report but also to develop more applied recommendations for the member states and especially so for the private institutions desired as part of the new partnerships.

This need for operationalization was supported by Jakob Granit, Centre Director at the Stockholm Environment Institute. In his opinion, the broad vision as presented in the report is indeed difficult to work with, but he also suggested that progress on parts of the agenda can be instructive for how to go further also with the more challenging parts. He also emphasized the importance of a regional approach, building on existing networks of regional partnerships, and again stressed the importance of public-private partnerships to solve common international issues.

The second panel was devoted to the role Sweden can play in global sustainable development and the post-2015 agenda. The discussion was started by Ulla Holm, Global Director at Tetra Laval Food for Development Office. She presented some of Tetra Laval’s experiences of sustainable development work in Bangladesh, an example of a successful public-private partnership. In her view, one of the main pillars of sustainability is to prevent unnecessary food loss, and this can be achieved by building an integrated value chain that supports rural development in the long run. The crucial challenge on this path is the need for concurrent public and private investments, and how to overcome coordination problems and lacking trust across stakeholders. She therefore stressed the need to construct successful public-private partnerships on a large scale and in different areas, but also to make sure to document and scale up the existing models in order to replicate success in the most cost efficient way.

Erik Lysen, Director for International Affairs at the Church of Sweden, stressed the challenges in changing existing institutions and briefly discussed the main motives that could make such changes to occur. He also argued that some of the strongest motives that would actually provide the necessary motivation for change, namely fear, could not be desirable in the long run, but still viable in a context of post-2015 agenda if complemented with better social protection, institutes of civil society and a broader public discussion. Here, NGOs could act as watchdogs and catalysts, strengthening the desire for building new institutions and providing material and human support for their construction at the same time.

Stefan Isaksson, Head of Policy Analysis at the Department for Aid Management at the Ministry for Foreign Affairs, continued the discussion on the challenges of changing existing institutions. He described current efforts to remodel the Swedish aid management system in order to become a more effective bureaucracy. In his view, the major shift in thinking is that of understanding aid less as simply giving money away and more as an investment for a common future. This is needed to improve the selection process of aid projects and also to motivate better the need to make projects and their results measurable and accountable. To achieve this, broader collaboration and consultations across stakeholders is needed. He also mentioned that perhaps at present many aid projects are too conservative, that the failure rate is too low because it reflects an aversion to risk that partly defeats the purpose of official foreign aid. The private sector will always be reluctant to venture into areas with high risk even if the potential social rate of return is high, so for official aid to serve as a more effective complement to private flows, more risk tolerance may be needed.

The issue of understanding aid as investment was discussed in detail by Jonas Ahlen, Investment Manager at the Storebrand Kapitalförvaltning. He described current efforts in the area of sustainable investments, mainly centered in microfinance and agricultural loans. In his opinion, broader involvement in such practices from the private sector would facilitate a transition to sustainable practices, but would at the same time require changing existing regulations in home countries to incentivize and alleviate the risks. He also stressed the need for broader public-private partnerships in these areas and briefly described the new consultative practices established by the Ministry of Finance in Sweden to catalyze private capital participation in for instance infrastructure projects in Sub-Saharan Africa.

Finally, Homi Kharas added to the Sweden-centered discussion by stressing that there exists no systematic assessment of what public-private partnerships can do. In his opinion, possibly the most important role for Sweden is to create conditions that would facilitate public-private partnerships in development and aid. By developing and experimenting with forms of public-private partnerships, as well as with new ways of measuring and monitoring of performance of such partnerships, Sweden could create a case for broader involvement of private funding and thus accomplish perhaps the most difficult part of bridging the post-2015 with the experience and skills of the private sector.

Conclusions

In sum, the discussion at the Development Day 2013 clearly highlighted the importance of sustaining some of the positive trends seen lately for economic and human development but also highlighted how crucial it is to take environmental sustainability into account. There is a growing consensus that long run human development necessitates an understanding of the planetary boundaries, even though exactly what trade-offs this involves and where to put the relative weight on more short run economic development is still debatable. There was also a wide consensus around the importance to get all different parts of society involved and working in tandem. Foreign aid cannot be expected to pull the heavy load by itself. The challenges are far too wide and important. Instead, much hope was attributed to public-private partnerships, but there is a lot of work that remains to make sure these vehicles generate the hoped for solutions. The capital, experience and skills of the private sector are needed. On the other hand, getting the incentives right is not a trivial challenge. Finding models of partnerships that work and can be scaled up may be an area in which Sweden can set an example and lead the way for other nations striving to contribute to long run sustainable development.

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Trade Policy Uncertainty and External Trade: Potential Gains of Ukraine Joining the CU vs. the Signing Free Trade Agreement with the EU

Posted on June 12, 2013 | Policy Brief

This policy brief summarizes the results of recent research which predicts gains in Ukrainian exports from signing a deep and comprehensive free trade agreement with EU, and compares these gains with predicted gains from joining the Customs Union of Belarus, Kazakhstan, and Russia. We argue that the gains would be mostly due to elimination of uncertainty in trade policy of Ukraine with the CU and the EU countries. We find that European integration brings higher potential for export growth, and that it also shifts the structure of Ukrainian exports towards capital goods, reducing the share of raw materials in total export.

Trade Policy Uncertainty and Export

Trade policy uncertainty (TPU) is a powerful negative factor that prevents economy from the realization of its export potential. In a recent paper, Handley and Limao (2012) argue that since the exporting decision involves substantial fixed costs, TPU significantly affects investment and entry decisions in international trade. In particular, they show that preferential trade agreements (PTAs) are important even when the pre-PTA tariff barriers are low. Comparing pre- and post-EU accession patterns of Portuguese exports, they find that Portuguese trade increased dramatically after 1985. The increase was the largest towards the EU partners, suggesting that it was caused by the accession. Export expanded through considerable entry of Portuguese firms into EU markets, even in industries where applied tariffs did not change. Handley and Limao estimated that the tariff reduction, which averaged 0.66 percentage points, has been responsible for only 20 percent of the increase in exports to EU10 after the EU accession, while 80 percent of the increase was due to resolving TPU.

Handley and Limao further argue that the Portuguese example should be highly relevant for any small open economy, facing important trade policy choices. In this regard, Ukraine is facing a very hard choice of selecting its regional integration strategy – towards the EU or the Customs Union (CU) with Belarus, Kazakhstan and Russia, resulting in severe TPU. The options are mutually exclusive since the CU trade policy is not compatible with neither the WTO commitments of Ukraine, or with the parameters of the deep and comprehensive free trade agreement (FTA) between Ukraine and the EU, finalized in 2012. Average tariff protection within the CU in 2012 was 10 percent (Shepotylo and Tarr, 2012), while the average WTO binding tariff rates in Ukraine were only 5 percent; the parameters of the FTA with the EU are even less protective, which would cause even stronger disagreements regarding the tariff schedules. Moreover, technical and phyto-sanitary standards in the EU and the CU are different; therefore, it would be extremely hard to harmonize the Ukrainian standards with both of them.

Despite low tariff protection, uncertainty on the parameters of the long run trade policy of Ukraine with the CU and EU countries is extremely high. It is crucial for both foreign and domestic investors to understand in what direction the regional integration will proceed before making decisions on investing or exporting, since these decisions can incur substantial sunk costs. Suppose that a large European multinational firm were interested in including Ukrainian companies in its production chains only if Ukraine signs the FTA with the EU (integrate vertically). If Ukraine instead joined the CU, this presumed European company would rather be interested in horizontal integration and invest by building a plant for final assembly of products to serve the Ukrainian and CIS markets. For Russian companies the situation would be the reversed. They would be interested to integrate vertically if Ukraine is a member of the CU and integrate horizontally if Ukraine signed FTA with EU. However, since vertical and horizontal integration are quite different strategies, neither European nor Russian companies invest in Ukraine before the uncertainty is resolved. The same holds true for domestic companies which would like to extend their export activities to new markets. Since entrance to new markets is costly and requires some irreversible investment, it is optimal to wait until the policy uncertainty is resolved.

Modeling Trade Policy Options of Ukraine

In Shepotylo (2013), we investigate which integration scenario is more preferable for Ukraine under the assumption that TPU is fully resolved and Ukraine trades up to its potential. Based on export data in 2001-2011, we estimate the gravity model by Helpman, Melitz, and Rubinstein (2008) method, adjusted for panel data case and endogeneity of a decision to sign a PTA. Using this model, we predict bilateral exports of Ukraine under three counterfactual scenarios: a) Ukraine joined the Customs Union in 2009 (CU); b) Ukraine signed the FTA with the EU in 2009 (EU FTA); c) Ukraine joined the EU in 2009 (EU). The model predictions take into account the level of economic development, geographical location, industrial structure, and quality of government and regulatory agencies. It also accounts for macro trends, including the global trade collapse of 2008-2009.

The results are not intended for a short-term forecast, but should be rather used as indicators of the long-run effects. Their interpretation is as follows. Suppose that Ukraine has signed the FTA with the EU in 2009. Taking into account all observable characteristics of Ukraine, what would be the level of Ukrainian export of product k to country j, if Ukraine, in all other respects, would behave as a typical country-member of the FTA EU? That would involve removal of the trade policy uncertainty, stronger integration of domestic companies into the global supply chains, and increase in foreign direct investments from the EU countries.

Unlike the studies based on the Computable General Equilibrium (CGE) method, which assumes that the policy choice affects the economy only marginally through reduced tariff barriers, and that the underlying economic structure and expectations of the economic agents remain intact, the gravity model captures all changes that occur in the economy over the investigated period and extract the differences in export flows between any two counterfactual scenarios, given all background economic changes.

Results

Our main results are as follows. First, the actual exports of Ukraine are far below their potential, compared with performance of both the CU countries and the FTA EU countries. The expected long run gains in Ukrainian exports to all countries under the CU scenario are equal to 17.9 percent above the export level in 2009-2011. The corresponding number for the FTA EU scenario is 36 percent, and for the full EU scenario, 46.1 percent. Based on 2011, the export of Ukraine would have been 98 billion US dollars under the EU scenario, 91 billion US dollars under the FTA EU scenario, and 72 billion US dollars under the CU scenario. All these numbers should be compared with the actual 68 billion US dollars of Ukrainian export in 2011.

Figure 1. Ukrainian Export under the Different Scenarios

Second, any scenario predicts that Ukraine severely underperforms in its trade with both CIS and EU countries, while its export to the rest of the world is in line with the predictions of the model. These results are consistent with the theory that unresolved TPU in relationships with the CIS and EU countries severely hurts the Ukrainian export potential to these countries.

Table 1. Ukrainian Export under the Different Scenarios

Note: CIS – Commonwealth of Independent States; EU12 – countries that joined EU after 2003; EU15 – countries that joined EU before 2004; RoW – rest of the World

Third, CU integration would be more beneficial for the Ukrainian agriculture and food industry, while FTA EU or full EU integration would be more beneficial for textiles, metals, machinery and electrical goods, and transportation. Conditional on not worsening its market access to Russia, Ukraine would expand its trade in these sectors to all countries, including Russia and other members of CU.

Figure 2. Expected Increase of Ukrainian Export under the Different Scenarios

Finally, the CU integration would lead to a small increase in the share of capital goods from 17 percent to 20 percent of total exports. FTA EU would increase the share of capital goods to 28 percent, while full EU integration would increase it to 29 percent. In all scenarios, the share of raw materials would decline from 16 percent to 10-12 percent. The share of intermediate goods would decline from 48 percent to around 40 percent under the two EU scenarios and would only marginally decrease under the CU scenario. The share of consumer goods would remain stable around 20 percent.

Conclusions

Ukraine would be better off by signing a deep and comprehensive trade agreement with the EU and integrate into its production chains than joining the CU. Right now, Ukraine severely underperforms by exporting far below its potential. Evidence shows that high trade policy uncertainty plays a large role in Ukraine’s poor performance, since the gap between actual and potential exports are mainly due to low levels of export to the EU and CIS countries. Moreover, Ukraine should be interested in moving the integration process even further, because EU accession would bring even better results.

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References

Handley, K., & Limão, N. (2012). Trade and investment under policy uncertainty: theory and firm evidence (No. w17790). National Bureau of Economic Research.
Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading partners and trading volumes. The Quarterly Journal of Economics,123(2), 441-487.
Shepotylo, O., & Tarr, D. (2012). Impact of WTO accession and the customs union on the bound and applied tariff rates of the Russian federation. World Bank Policy Research Working Paper, (6161).

Can Anti-Smoking Campaigns Increase Obesity? Evidence from Belarus

Posted on May 20, 2013 | Policy Brief

Authors: Aliaksandr Amialchuk, University of Toledo, and Kateryna Bornukova, BEROC.

In this brief, we discuss the possible effects of an anti-tobacco campaign on obesity levels in Belarus based on results of Amialchuk et al (2012). Both smoking and obesity are among the main health concerns in Belarus. Negative correlation between smoking and body weight is well documented, but can anti-tobacco campaign cause an increase in obesity rates? Results of studies from developed countries provide mixed evidence. In Amialchuk et al (2012), we use household survey data from Belarus to establish the link between smoking and body mass index (BMI). We use cigarette prices and regional smoking prevalence as instruments for smoking, and find a negative effect of smoking on BMI. Moreover, using the quantile regression approach, we find that smoking has different effects on body weight for different BMI quantiles, with the largest negative effect in the upper part of the conditional BMI distribution. These findings suggest that anti-tobacco campaigns may slightly increase obesity rates, and campaigns should therefore ideally also include measures to promote a healthy lifestyle. On the other hand, the potentially modest weight gain from an anti-tobacco campaign is likely to be more than offset by the general improvements in health.

Smoking and Obesity in Belarus

Smoking prevalence in Belarus, like in many other transitional countries, is quite high. According to the Belarusian Household Survey of Income and Expenditure from 2010, the smoking rate was 26%, with a much higher prevalence of among men (49.3%) compared to women (9.5%).[1]

Despite the troubling levels of smoking prevalence, little has been done to combat smoking in Belarus. While most of the post-Soviet economies liberalized the tobacco industry, it remains under government control in Belarus. The profits of the state-owned cigarette producers, along with tobacco taxes, constitute an important part of Belarusian budget revenues. This might explain why the Belarusian government has not engaged in anti-tobacco campaigns in the past. However, Belarus is currently implementing Anti-Tobacco Plan for 2011-2015 in cooperation with the World Health Organization.

The Anti-Tobacco Plan includes a variety of anti-tobacco actions and measures. In particular, the government has plans to gradually increase tobacco taxes, introduce smoking-free zones and restrict smoking in public places, along with a massive informational campaign about the dangers of smoking and ways to quit. These measures have the potential to lead to a significant decrease in smoking prevalence. However, an unintended consequence of these policies might be an increase in overweight and obesity rates.

In fact, obesity is another important health problem of Belarus. In 1996-2008, (the period of analysis in Amialchuk et al (2012)), the mean BMI among adults was 26, which suggests that an average Belarusian adult is just on the borderline between healthy weight and overweight. In particular, 34% of adults are overweight, while approximately 15% of adults are obese. Moreover, the distribution of weight status has undergone substantial changes over time: the percentage of individuals in the right tail of the BMI distribution has increased over time, with the percentage of obese increasing faster than the percentage of overweight individuals.

The Link between Smoking and Obesity

The negative relationship between smoking and body weight is well-documented in the medical literature. This inverse relationship is mostly attributed to how smoking affects body weight by boosting metabolism and suppressing appetite. However, causality is usually difficult to establish: for example, a smoking person may also be more likely to eat unhealthy foods and care less about their health in general. Nevertheless, most of the previous studies have found a significant negative effect of smoking on body weight.

Since in many developed countries, the decrease in smoking prevalence coincided in time with the surge in both overweight and obesity rates, the question arises whether anti-smoking campaigns are in part responsible for the increase in obesity rates. However, the evidence on the effects of anti-tobacco campaigns on overweight/obesity rates in developed countries is mixed. Some studies do not find any significant effect on obesity (Nonnemaker et al, 2009).

Evidence from Belarus

As mentioned above, smoking behavior and BMI may be jointly determined, and to deal with the challenge of establishing causality, we utilize the method of instrumental variables analysis. We employ two instrumental variables in our estimation: (i) the mean number of cigarettes smoked per day in the same year-region-gender- and education group as the respondent, and (ii) the average yearly price per pack of cigarettes in the region where the respondent lives. Gilmore et al. (2001) identify important demographic and socio-economic differences in smoking rates, which dictates our use of gender and education categories (below secondary, secondary, university degree) to construct groups of observations that will be followed over time. The use of region as a grouping variable allows us to capture the social norm associated with smoking at the regional level. We exclude the individual’s own cigarette smoking when we create group-level means. Group-specific smoking prevalence is likely to be predictive of the individual’s own smoking preferences, but is unlikely to have a direct effect on individual’s weight status other than through the effect on individual’s smoking. After accounting for the fixed differences in average smoking among regions, gender, and education groups within each year, the source of variation that is available to identify the effect of the instrument on individual’s smoking is the differences in smoking prevalence among various interactions of year, region, gender and education categories.

We use lagged prices as instrument for current year cigarette consumption of the individuals in order to account for the addictive and inelastic nature of demand for smoking and the inability to quickly change smoking behavior after a price change. Furthermore, we use natural log of cigarette prices in order to account for the potentially non-linear effect on the number of cigarettes smoked. Cigarette prices are likely to influence an individual’s BMI only through its effect on smoking.

Other controls in our regressions include total personal income; household size; age; gender; single vs. married indicator; indicators of self-reported health status (good health, fair health, and poor health indicators); number of medical visits in the last 3 months; indicator for having been hospitalized in the last 12 months; indicator for whether health affects ability to work; sports practicing indicator; indicators for the educational attainment (university diploma, secondary education); and indicators for being currently employed, having ever worked, and being a student.

Our endogeneity-corrected estimates suggest that one additional cigarette per day would decrease BMI by roughly 0.23 units, and would reduce the probability of being overweight by approximately 2.5%. Furthermore, there is a small but significant effect on the likelihood of being obese: an additional cigarette smoked per day decreases the probability of being obese by 1.3%. Our results suggest an important implication that smoking is inversely related to body weight, and has some effect on obesity rates.

We also explore the difference in the effect of smoking on body weight across different quantiles of conditional BMI distribution. The largest effect is obtained for the 75th and 90th percentiles, and the smallest effects for the 10th and 25th percentiles. Smoking has a large effect on the body weight of individuals who are at the upper tail of the BMI distribution. These findings suggest that a reduction in smoking rate may lead to an increase in obesity rates by inducing weight gain among the population near the top end of the conditional BMI distribution.

While we found evidence of a possible increase in obesity rates resulting from the anti-tobacco campaign, it is important to remember that adverse health effects of smoking are numerous and the health benefits of smoking cessation are far in excess of the risk of weight gain. The current high prevalence of smoking and number of overweight individuals in Belarus constitute a major public health concern. Our results suggest that the prevalence of overweight and obesity might be exacerbated by the anti-tobacco campaign. From a policy perspective, an increase in obesity rates among the general population may be a reasonable concern for policy instruments targeted at reducing the overall smoking rates. It would therefore be wise to promote healthy eating habits and sports together with the anti-smoking campaign. However, the potentially modest weight gain from anti-tobacco campaign only is likely to be more than offset by the general health improvements associated with a decline in smoking rates.

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References

Amialchuk, A., K. Bornukova, M. Ali, 2012. Smoking and Obesity Revisited: Evidence from Belarus. BEROC Working Paper Series, WP no. 19
Gilmore, A.B., McKee, M., Rose, R., 2001. Prevalence and determinants of smoking in Belarus: A national household survey, 2000. European Journal of Epidemiology 17: 245-253
Nonnemaker, J., Finkelstein, E., Engelen, M., Hoerger, T., Farrelly, M., 2009. Have efforts to reduce smoking really contributed to the obesity epidemic? Economic Inquiry 47, 366–376

[1] The social norms explain difference in smoking rates of men and women. In younger population, however, gender differences in smoking rates are less pronounced.

Preferences for Redistribution in Post-Communist Countries

Posted on May 13, 2013 | Policy Brief

Public attitudes toward inequality and the demand for redistribution can often play an import role in terms of shaping social policy. The literature on determinants of the demand for redistribution, both theoretical and empirical, is extensive (e.g., Meltzer and Richard 1981, Alesina and Angelotos 2005). Usually, due to data limitations, transition countries are usually considered to be a homogeneous group in empirical papers on the demand for redistribution. However, new data on transition countries allow us to look more deeply into the variation within this group, and to look at which factors are likely to play a significant role in shaping a society’s preferences over redistribution.

The data we use are from the second round of the EBRD and WB Life in Transition Survey (LiTS) (EBRD Transition Report 2011). This is a survey of nationally representative samples consisting of at least 1000 individuals in each of the 29 transition countries.[1] In addition, and for comparison purposes, this survey also covers Turkey, France, Germany, Italy, Sweden and UK. Furthermore, in six of the countries surveyed – Poland, Russia, Serbia, Ukraine, Uzbekistan and UK – the sample consists of 1500 individuals.

Redistribution is, in general, a complex issue, which can take various forms and rely on different mechanisms. In this policy brief, we will only focus on two forms of public attitudes towards redistribution. The first is direct income redistribution from the rich to the poor and public preferences for or against this form of redistribution. The second is indirect redistribution through the provision of public goods, some of which favor certain groups of population over others. In particular, we will consider preferences over extra government spending allocations in the areas of education, healthcare, pensions, housing, environment and public infrastructure. Generally, we would like to explore in greater detail to what extent there are differences across countries in terms of public preferences over redistribution and what might explain differences both within and across societies.

Both survey rounds include questions regarding public preferences towards income redistribution, direct (from the rich to the poor) and indirect (through government spending towards certain public goods). Data for exploring public preferences for direct redistribution can be obtained from a question in the survey that asks respondents to score from 1 to 10 whether they prefer more income inequality or less. More specifically, in the LiTS 2010, the question is the following:

Q 3.16a “How would you place your views on this scale: 1 means that you agree completely with the statement on the left “Incomes should be made more equal”; 10 means that you agree with the statement on the right “We need larger income differences as incentives for individual effort”; and if your views fall somewhere in between, you can choose any number in between?

Note, however, that we use the reverse of this so that 10 represents greater equality and 1 represents wider differences. Bearing this in mind, figure 1 shows the average scores for redistribution preferences for a selection of the countries for 2010 and shows a sizeable variation ranging from 4.4 (more inequality) in Bulgaria to 7.87 (greater equality) in Slovenia. The mean for Russia is 6.92.

The data also allows for a comparison to be made between these preferences in transition countries and in the developed economies covered in the survey. For instance, Russians are on average close to Germans in their preferences for redistribution, while Estonians and Belarusians prefer less redistribution and are closer to the British, on average.

Figure 1. Preferences for Direct Redistribution

Indirect measures of attitudes towards redistribution can add further depth to these societies’ preferences. In particular, the indirect measures in the 2010 survey are derived from a question that asks respondents to rate from 1 to 7 their first priorities for extra government spending.

Q 3.05a “In your opinion, which of these fields should be the first priority for extra government spending: Education; Healthcare; Housing; Pensions; Assisting the poor; Environment (including water quality); Public infrastructures (public transport, roads, etc.); Other (specify)”?

The country averages for these indirect measures for 2010 are presented in Figure 2. The graph reveals a sizeable cross-country variation. For instance, 43.5% of respondents in Mongolia preferred channeling extra government money to education, while 48.7% of respondents in Armenia selected higher healthcare spending. Almost 39% of respondents in Azerbaijan chose assistance to the poor as the first priority for government spending, while the corresponding figure was only 8.3% in Bulgaria and 4% in the Czech Republic. More than 34% of the Russians choose healthcare as their first priority, another 20% choose education, 15% would like the money to be channeled to housing, 14.5% to pensions, 11% to support the poor, 3% to support environment, and only 2% to public infrastructure (2010).

These numbers highlight that there are sizeable differences across the transition countries regarding preferences for redistribution. Also, regarding the form of indirect redistribution in terms of preferences over how government budgets should be prioritized and allocated. Several groups of factors or determinants are typically listed in academic literature to help explain what drives public preferences over the degree and form of redistribution. In the first group of factors, there are various determinants at the individual level. Within the group of individual determinants, self-interest or rational choice of a degree of redistribution favorable to the individual with usual (individual) preferences are stressed. Alternatively, motives behind a preference for redistribution can be related to social preferences (preferences for justice or equity) and reciprocity. Within this general group of self-interest, attitudes towards risks can be stressed as a crucial factor behind demands for social insurance and hence for indirect forms of redistribution. Individuals’ prospects of upward mobility, expectations about their future welfare or ‘tunnel effect’ in shaping their views and preferences over redistribution are also underlined. Also, the commonly held beliefs about the causes of prosperity and poverty are considered to be important in shaping the public’s attitudes under the umbrella of social preferences.

The literature covers possible institutional determinants for preferences towards redistribution and emphasizes the role of the level of inequality in a society and typically relates to the median voter hypothesis in democracies. It is also stressed that welfare regimes (liberal, conservative) can play a role in shaping the level of public support for redistribution.

Figure 2. Preferences for Indirect Redistribution

A closer examination of the data and estimates of the factors shaping individuals preferences over redistribution in the 2010 survey, are consistent with motives involving strong self-interests of the respondents.[2] Those from richer households have less support for redistribution, with the result being robust to the measure of household income used. The past trend in household income positions is insignificant, while the higher the expected income position of household in the coming four years, the less supportive the respondents are of income redistribution (elasticity -0.1). Those who experienced severe hardships with the recent crisis tend to support redistribution more than those who had little problems or not at all (elasticity 0.13).

Furthermore, the role of preferences towards uncertainty is confirmed: the higher the (self-reported) willingness to take risks, the less likely the individual is to support or favor redistribution. Respondents with tertiary education are less inclined to support redistribution of income from the rich to the poor, compared to those with secondary education (elasticity is -0.4). Having a successful experience with business start-ups also decreases demand for income redistribution from the rich to the poor (elasticity -0.3). Those living in rural areas are more in favor of redistribution compared to metropolitan areas, while living in urban areas shows the same level of support for redistribution as those living in metropolitan areas. In each of these cases, it appears that those who would benefit the most from redistribution favor it more than those who view it as coming at their expense, or possible expense in the future.

Beliefs regarding the origins of success and poverty are also shown to be statistically significant and negative, as predicted: those who believe effort and hard work or intelligence and skills are the major factors for success are less supportive of income redistribution (elasticity -0.16). Those who consider laziness and lack of will power the major factors for people’s lack of success are also, consistently, less supportive of redistribution (elasticity -0.2).

It also turns out that better democratic institutions are correlated with a higher demand for redistribution. The result is robust across the measures used, i.e. it does not seem to depend on the particular measure used. The size of the effect is quite pronounced: a one standard deviation increase in the democracy measure increases demand for redistribution from 16 percentage points, when the voice and accountability measure is used, to 33 and 36 percentage points when controls of the executives and democracy index are used.

Furthermore, the better the governance institutions, as measured by the rule of law and control of corruption indexes, the higher is the demand for redistribution. However, the result is not robust to the various measures used. Government effectiveness appears to be insignificant (though with a positive direction), and the regulatory quality measure is insignificant but with a negative direction. The size of the effects is again quite pronounced. A one standard deviation increase in the rule of law measure increases demand for redistribution by 17 percentage points, and a one standard deviation increase in the control of corruption measure increases demand for redistribution by 27 percentage points.

The higher the level of inequality, the larger is the demand for redistribution as might be expected. This result is robust across all measures used. The size of the effect varies from 16 to 18 percentage points in response to a one standard deviation increase.

A regression analysis of preferences towards indirect redistribution also shows that self-interest motives are very pronounced, but there are traces of social preferences as well. In particular, younger people (age 18-24) would like to have more subsidized education and housing at the expense of healthcare and pensions in comparison with the age 35-44 reference group. Those in the age 25-34 group would like to redistribute public spending to housing and environment at the expense of education, pensions and public infrastructure. Respondents in the age 45-54 group would also like to redistribute additional spending from education but to pensions. The two groups of older people (age 55-64 and 65+) would like to shift extra spending from education and housing to healthcare and pensions. The group of age 65+ would also like to shift money from assistance to the poor.

Respondents with tertiary education (in comparison with holders of a secondary degree) favor extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assisting to the poor, thus revealing additional elements of social motivations. Respondents with primary education, when compared to holders of secondary degree, would like to redistribute public money from education to pensions and assistance to the poor. Respondents with poor health favor additional spending on healthcare and pensions at the expense of education.

High skilled (in terms of occupational groups) respondents would like to redistribute public money from pensions to education. Those with market relevant experience of being successful in setting up a business tend to support education and public infrastructure at the expense of housing and pensions, though the result lack statistical power.

Respondents from households with higher income support extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assistance to the poor; again pointing to the other elements of possible social motivations. Those with a self-reported positive past trend in income position tend to support spending extra money on the environment at the expense of assistance to the poor (the latter lacks statistical power). If the respondent lives in its own house or apartment, s/he tends to support redistribution from housing and assistance to the poor, to healthcare and pensions.

Respondents whose households were strongly affected by the crisis would like expenditure on environment and public infrastructure to be reduced. Those with higher self-reported willingness to take risks would redistribute extra public money to education at the expense of healthcare and housing.

Respondents who believe that success in life is mainly due to effort and hard work, intelligence and skills favor education at the expense of assistance to the poor and public infrastructure, suggesting they might view education as the key to escape poverty. Those who think that laziness and lack of willpower are the main factors behind poverty would, unsurprisingly, redistribute extra public money from assistance to the poor to healthcare.

Males (as compared to females) favor extra spending on education, housing, environment and public infrastructure at the expense of healthcare. The self-employed favor extra spending of public money to pensions at the expense of housing. There is no difference across respondents living in metropolitan, rural or urban locations.

A regression analysis shows that better democratic institutions are correlated with higher support for allocation of additional public spending to education and healthcare, environment and public infrastructure. The effects are larger for education and healthcare: one standard deviation in the democracy index increases the support for spending money on education by 3 percentage points, for healthcare by 3.1 percentage points, and only by 0.4 and 0.6 percentage points for environment and public infrastructure, respectively. This reallocation is at the expense of assistance to the poor (3.5 percentage points), housing (2.6 percentage points) and pensions (1.1 percentage points). The pattern is robust to the measure of democratic institutions used, though the marginal effects vary slightly depending on the measure.

The influence of governance institutions is similar. Respondents in countries with better governance institutions favor allocation of extra public money to education (3.2 percentage points in response to one standard deviation in government effectiveness), health care (2.9 percentage points), environment (0.9 percentage points) and public infrastructure (0.6 percentage points). The reallocation is at the expense of assistance to the poor (4.2 percentage points), housing (3.3 percentage points) and pensions (0.2 percentage points). The pattern is also robust to the measure of governance institutions with the marginal effects varying slightly depending on the measure.

The higher the level of inequality in a country, the higher the demand for spending extra public money for education at the expense of assistance to the poor, pensions and public infrastructure. A one standard deviation increase in the index, increases demand for spending extra public money on education by 3.8 percentage points, and decreases spending on assistance to the poor by 2 percentage points, pensions by 1.9 percentage points, and public infrastructure by 0.06 percentage points. The results are robust to the inequality measure used.

Overall, the analysis provides empirical evidence that transitional countries are not homogeneous with respect to preferences for redistribution, with sizeable variations in country averages and in public preferences. The study of individual determinants of preferences for redistribution confirms a dominant role of self-interest, with some indications of social sentiments as well. In addition to the usual measures used in individual level analysis, these data allow better control for both positive and negative personal and household experience. The study of institutional determinants also confirms the role of income inequality in shaping public attitudes. In particular, higher inequality is confirmed to increase the demand for direct income redistribution. A novel motive of the paper is the influence of democracy and governance institutions on demand for redistribution. Better democracy and governance institutions are likely to stimulate demand for income redistribution, revealing both higher societal demand for redistribution and appreciation of the potential capability of the government to implement redistribution effectively.

The study of individual determinants of indirect demand for redistribution adds to the overall picture and confirms not only the self-interest motives but also social preferences especially pronounced among people with tertiary education and in high income groups. Better democratic and governance institutions stimulate redistribution of public money towards education, healthcare, environment and public infrastructure, while weaker democratic and governance institutions increases demand for allocation of public money to assistance to the poor, housing and pensions.

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References

Meltzer, A., Richards, S., 1981. “A Rational Theory of the Size of Government”. Journal of Political Economy 1989, 914–927.

Alesina, A., Angeletos, G.M., 2005. “Fairness and Redistribution”. The American Economic Review, 95(4), 960-98

[1] The countries covered were: Albania, Armenia, Azerbaijan, Belarus, Bosnia, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Georgia, Hungary, Kazakhstan, Kosovo, Kyrgyzstan, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan.

[2] The basic empirical equation to study individual determinants of public preferences towards income redistribution is the OLS with country fixed effects (for direct redistribution) and multinomial regression with country fixed effects (for indirect measures). When studying the influence of institutions, the equations are transformed to replace country fixed effects with an institutional measure (one at a time). To control for the basic economic differences, average GDP per capita was included.

Optimal Economic Policy and Oil Price Shocks in Russia

Posted on February 18, 2013 | Policy Brief

Free Policy Brief Image - Russia and Oil — Out of Control

Significant oil price fluctuations are an important factor influencing real economic variables, especially in the countries with large dependency on export of natural resources. Under such fluctuations, it is natural to consider the possibility of economic policy to fine tune the real economy, achieve inflation stability, and to weaken the negative influence of oil price shocks. In terms of monetary policy, authorities realize the existence of many channels through which oil market is related to the real sectors and inflation. The Central Bank of Russia should analyze the necessity to react to oil prices and to change the effect of them on the real economic variables.

The most typical way of reaction to oil prices in the Russian Federation is accumulation of reserves at the Reserve Fund. The Stabilization Fund (was later in 2008 separated into the Reserve Fund and the National Welfare Fund) was created in 2004 based on the initiative of Mr. Alexey Kudrin, who was a Minister of Finance at the time. The idea of the fund is to direct the revenue from oil export to the budget, but only when the price of oil does not exceed a pre-specified level, and the residual income should be accumulated in the fund.

In addition, the Central Bank of Russia may respond with its refinancing rate to the changes of the oil price via an augmented oil price Taylor rule or indirectly without inclusion of a commodity quota into the monetary policy rule.

We consider whether the Central Bank of Russia should formally establish the policy of responding to the changes of the oil price. The key evaluation criterion for selecting the optimal response is the minimization of inflation and GDP fluctuations.

Taking into account the results of an applied Dynamic Stochastic General Equilibrium model estimated for the Russian economy, we suggest that the Central Bank, optimally, should include the oil price in its interest rate Taylor monetary rule. That is, it should react to oil price quotas but only in the case of stabilization fund absence. This suggested optimal monetary policy implies a positive direct response to oil price shocks; a 1% oil price increase (decrease) should trigger CBR to raise (decrease) the refinancing rate by 0.1%. In the case of stabilization fund presence, there is no need to respond to changes in the oil price since the former stabilizes the situation when the oil price fluctuates too much.

The main potential limitation of this study is the problem of model quality against the real data. In addition, other monetary policy instruments may be tested against the reaction to changes in the oil price.

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Transportation Infrastructure and Labor Market Integration: the Moscow Oblast Case

Posted on February 11, 2013 | Policy Brief

The model of city organization proposed by von Thünen in the beginning of the XIXth century, and then formalized by Alonso followed by Muth and Mills (see Ner (1986)), is one of the most “successful” models in economics in terms of practical applications. The model explains why the gradient of population density and land rents decline from the city center towards the periphery. In fact, almost all modern cities fit this pattern, i.e. the model invented two centuries ago is capable of describing today’s spatial structure of cities. Even though von Thünen’s original idea of a city center as a single “marketplace” is no longer realistic, a multitude of factors beyond this make central locations nevertheless attractive. If firms are located near each other, they can take advantage of a common labor pool, easier access to consumers and suppliers, shared infrastructure, and knowledge spillovers, to name but a few advantages. Access to the center brings tangible economic benefits to both labor and capital and these benefits exceed possible losses due to increased competition, and so the von Thünen mechanism still works today, albeit through different channels.

In cities, there are generally two types of spatial organizations possible with respect to household income. If the advantages of amenities in a city center are not very strong, rich people tend to choose to locate in suburbs in order to consume higher quality housing. Such patterns are typical in US cities. If the advantages of a center are strong, the rich choose to live in the center. (Brueckner et al. (1999)) Due to historical circumstances, such patterns are typical of European or Russian cities. In these cases we observe a declining gradient of income; the further we move from the center, the further residents’ average income falls.

There are two forces at work shaping this declining gradient of wage. First, poor people sort themselves into suburban locations. Second, residents of the suburbs who want to take advantage of the labor market in the center face a barrier involving commuting costs. Many of them forgo high-wage opportunities that require tedious everyday commuting and therefore remain poor as a consequence.

An apparent policy solution to reduce income inequality would be to reduce transportation costs. The higher transportation costs are, the steeper the gradient of income. Fast and convenient transportation promotes the integration of local labor markets, gives the residents of the suburbs more, and often better, job opportunities, and works toward equalization of income across the agglomeration. Moreover, as transportation costs decline, the geographic area of agglomeration grows, which opens new opportunities for real estate development as well as new possibilities for rural residents to commute and participate in large labor market.

We conducted a study at CEFIR (Mikhailova et al. (2012)) comparing the spatial patterns of average wages in the Moscow agglomeration with several agglomerations in Western Europe. We considered municipal-level data for Moscow Oblast and for 25 agglomerations in Sweden, Germany, and Netherlands. In the sample of municipalities that are served by suburban train system, we estimated how average wages in a given municipality respond to different lengths of travel times to the city center.

Figure 1 shows the estimated wage-travel time relationship for Moscow Oblast and Figure 2 for the selected European cities.

Figure 1. Average Wage and Travel Time to the City Center, Moscow

Figure 2. Average Wage and Travel Time to the City Center, Europe.

The residents of the Moscow agglomeration are at a clear disadvantage according to the data shown above. Residents of Moscow Oblast, even those who live in relative proximity to the city, loose drastically in terms of average wage. Doubling the travel time (say, from 20 min to 40 min, which is the range most commuters fit into) results in a 25% drop in the average wage for residents in Moscow Oblast compared to only a 5% drop in Europe. The wage in a municipality, from which it would take 90 minutes to travel to the city center, is almost half of the average wage inside Moscow’s Ring Road whereas in Europe 90 minutes translates into a 10% loss of in average wages.

A 90 minutes travel time could be considered as a realistic limit to the size of an agglomeration. This is roughly the maximum distance over which a typical working commuter would be willing to travel each day in each direction. A 90 minute commute in Europe represents approximately a 100 kilometer distance. In Moscow Oblast, however, it is only 63 km. So, Moscow Oblast loses in the effective “reach” of suburban transportation: people who live further than roughly 60 km from the center cannot practically commute.

Even for the same commuting time, the difference in wages between center and suburban municipality is much smaller in Europe (see Figures 1 and 2). This means that a commute for the same time length (in terms of railroad transport) presents a larger barrier for the residents of Moscow Oblast. This is obviously an over simplification of the situation since taking into account only commuting times as the measure of costs we ignore many other critical factors such as price (relative to income), the convenience of schedule and travel comfort, alternative modes of transportation, etc. Suburban trains in Moscow Oblast run infrequently, they are overcrowded, and alternative transportation modes (car or bus) face considerable delays due to road congestion. All of these additional factors serve to reduce the labor market opportunities of the Moscow Oblast residents and make wage inequality even deeper.

Figure 3 presents wage-distance gradients for the Moscow agglomeration under different scenarios using a hypothetical “European” gradient to show what could be the case if changes were made to reduce barriers to transportation bringing the Moscow agglomeration in line with European standards. The graphs end at a distance that corresponds to a typical 90-minute commuting time under various scenarios ranging from the status quo to the best case, where Moscow Oblast replicates European standards. The red curve represents the upper bound estimate of the possible effect of investments to improve the transportation infrastructure to bring Moscow regional transportation network in line with the quality of a typical European agglomeration. The residents of Moscow region could gain up to 24% more in terms of current average wages if this were to take place. The purple curve, however, presents a more modest scenario assuming that the structure of Moscow regional transportation network remains the same, but the travel time were to be cut by 20%. Even in this case, the gains to Moscow Oblast residents are about 3% of wages which is very significant economically for an area populated by 5.5 million people.

Figure 3. Wage Distance Gradient

Note: BLUE – Estimated actual wage gradient for Moscow Oblast; Red – European wage gradient applied to Moscow Oblast data, simulation; Purple – a Moscow Oblast gradient given 20% cut in the travel time, simulation.

Further, it is important to note that to take advantage of labor market integration residents do not necessarily all have to commute to work to the center. The mere possibility of commuting creates arbitrage opportunities in the labor market and puts upward pressure on wages. As a result, it is important for economic policy to constantly improve transportation infrastructure even if the private benefits of increased usage are modest.

In the end, our analysis did not touch on the other benefits from transportation infrastructure. Apart from labor market integration, improvements in transportation infrastructure promote real estate development (Baum-Snow (2007), Garcia-López(2012)) and expand the market for goods and services. We leave these questions for further research.

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References

Baum-Snow, Nathaniel (2007) “Did Highways Cause Suburbanization?” The Quarterly Journal of Economics 122(2): 775-805
Brueckner, Jan K., Jacques-François Thisse, and Yves Zenou (1999) “Why is central Paris rich and downtown Detroit poor?: An amenity-based theory.” European Economic Review 43.1: 91-107.
Garcia-López, Miquel-Àngel (2012) “Urban spatial structure, suburbanization and transportation in Barcelona”, Journal of Urban Economics, Volume 72, Issues 2–3, September–November, Pages 176-190
Mikhailova, T, V. Rudakov and N. Zhuravlyova (2012) “Economic effects from the Moscow Oblast suburban railroad infrastructure development” («Экономические эффекты от развития инфраструктуры пригородного железнодорожного сообщения в Московской области»), project report, CEFIR.
Ner, J. B. (1986). The structure of urban equilibria: A unified treatment of the Muth-Mills model. Handbook of regional and urban economics: Urban economics, 2, 821.