Tag: Latvia

Latvia Stumbling Towards Progressive Income Taxation

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The 2016 budget includes measures aimed at increasing the progressivity of the Latvian income tax system. In this brief we report some exercise on the impact of these measures using the Latvian EUROMOD tax-benefit microsimulation model. We show that by their design, the reforms are aimed at a reduction in income inequality and an increase in the progressivity of the tax system. However, there are risks that the behavioural response of the tax payers will subvert the intended impact of the reforms.

Ever since it was introduced in 1994 the Latvian personal income tax has been applied at a flat rate, albeit varying over time, mitigated only by a small untaxed personal allowance. Partly as a result of this, the Latvian tax-benefit system redistributes less original income than most other EU countries. Is this all about to change? The 2016 budget currently being debated in the Parliament contains two proposals aimed at introducing more progressivity in the personal income tax. These are the introduction of a “solidarity tax” aimed at high earners and the introduction of an earnings differentiated non-taxable allowance. The stated aims of these measures are to reduce inequality and help low wage-earners.

Description of the Reforms

Solidarity Tax

The solidarity tax foresees that income above 48,600 EUR per year will be taxed at a rate of 10.5% (employee’s part), plus 23.59% (employer’s part). The new tax will affect a very small share of wage earners. According to Finance ministry’s estimate, this tax will affect 4.7 thousand persons, whose income in 2015 exceeded this threshold, or 0.59% of all employed individuals (Finance Ministry, 2015).

Differentiated Non-Taxable Personal Allowance

The differentiated non-taxable personal allowance will be introduced gradually between 2016 and 2020. The basic idea is to make the allowance dependent on income: individuals receiving income below a certain threshold are eligible for the maximum possible allowance, then the allowance gradually declines with income until it is zero. The system will be introduced gradually in the sense that the minimum allowance will not reach zero until 2020 – it will be gradually reduced from 85 EUR in 2016 to 0 EUR in 2020.

The way the system will be implemented foresees that during a fiscal year, all individuals will be taxed applying the minimum non-taxable allowance (e.g., 85 EUR in 2016). At the beginning of the next year, people eligible for a higher tax allowance will have the opportunity to apply for a tax refund, by making an income declaration, and to get the overpaid tax back.

Simulations of Reforms: Inequality

Below we present simulation results from EUROMOD, which is an EU-wide tax-benefit microsimulation model (for more details see Jara and Leventi, 2014). The results show the first-round effect of the simulated policies, i.e., they show the pure effect of the proposed reforms abstracting from any behavioural responses that these reforms might induce. We simulate the effect of five reform scenarios: two scenarios of differentiated non-taxable allowance (one scenario reflects the system that is planned to be introduced in 2016, the second scenario represents the system that is planned to be introduced in 2020), one scenario that simulates introduction of the solidarity tax, and two scenarios that combine the solidarity tax with the new non-taxable allowances. We compare these reforms with the baseline system, which describes the tax-benefit rules that are in place in 2015.

It is important to note that we assume in the simulations that everyone who is eligible for a tax refund under the new non-taxable allowance rules does in fact apply for the refund, which means that we estimate the maximum possible effect from the introduction of the higher tax allowances.

Table 1 summarizes the effect of the proposed reforms on income inequality as measured by the Gini coefficient. All the proposed reforms reduce income inequality, but the solidarity tax achieves higher equality by reducing incomes in the top decile. The non-taxable allowance mainly affects people in the middle of the income distribution, as the bottom deciles contain proportionally fewer employed individuals, while in the top deciles the allowance, which is set in absolute terms, makes a smaller share of the income – hence, a weaker effect. Pensioners, who mainly belong to the lower deciles of the income distribution, do not gain from a higher allowance, because of a special taxation regime for pensions that already provides for a higher personal allowance. All major benefits (unemployment benefit, social assistance, child-related benefits) are not subject to personal income tax, hence benefit recipients also do not gain from the proposed changes (see Figure 1).

Table 1. Gini Coefficient Associated with the Reforms

Baseline ST* 2016 allowance 2020 allowance ST + 2016 allowance ST + 2020 allowance
Gini 0.361 0.358 0.360 0.357 0.357 0.355

 Source: authors’ calculations using EUROMOD

Note: ST – solidarity tax

Figure 1. Deviation of Equivalised Disposable Income from the Baseline Scenario, %

Figure1 Source: authors’ calculations using EUROMOD

Figure 1 also shows that the losers from the solidarity tax are in the highest decile, though it should be borne in mind that enterprises are also losers because they now have to pay part of the solidarity tax. The solidarity tax generates no direct gainers.

Impact on Progressivity

The progressivity of a tax or system is typically measured by the Kakwani index. The Kakwani index (Kakwani, 1977) can vary between −1 and 1 and the larger the index, the more progressive is the tax. A positive index indicates that the tax is progressive and a negative index indicates it is regressive. Table 2 shows the calculated Kakwani index for all major direct taxes (which include personal income tax, social contributions and the newly introduced solidarity tax) and separately for personal income tax (PIT) for each of the postulated scenarios. The results suggest that all of the proposed reforms increase the progressivity of the tax system.

Table 2. The Kakwani Index for the Six Scenarios

Baseline ST* 2016 allowance 2020 allowance ST + 2016 allowance ST + 2020 allowance
All income taxes* 0.034 0.040 0.048 0.058 0.054 0.064
PIT 0.07 0.07 0.10 0.12 0.10 0.12

 Source: authors’ calculations using EUROMOD

Note: ST – solidarity tax; income taxes include personal income tax, social contributions and the newly introduced solidarity tax

Qualifications and Risks

The above results capture the so-called first round impact of the tax changes. In practice people will react to the changed incentives by changing behaviour and thereby changing the impacts. For example, the higher net reward for working in low wage jobs may increase the supply of workers willing to work in such jobs thereby possibly having a bigger positive effect on the incomes of low income households than implied by the simulations.

Perhaps more significant is the potential effect of the solidarity tax on the behaviour of high earners and of the enterprises that employ them. This effect is captured by the concept of the elasticity of taxable income – defined as the change in taxable income in response to a change in the marginal tax rate. The taxable income elasticity concept takes into account all the behavioural aspects of the taxpayer in response to a change in the tax rate. As well as labour supply responses it includes other responses e.g. switching the form in which income is received as well as simple tax evasion (Saez et al., 2012). It is the switching of the form in which income is received, away from wage income towards other less-taxed forms of income that can be expected here. Thus according to an internal Latvian Employers Confederation employer survey, if the solidarity tax is implemented one third of employers will consider using legal tax optimization tools such as dividends or the microenterprise tax to avoid paying the tax. Here, employers are important as well as employees, because employers will pay the larger share of the tax. If this happens on a significant scale (high elasticity of taxable income) then the intention of the solidarity tax will be subverted.

There are also risks with the differentiated personal allowance. If the burden of annual reporting of income is too high then many may simply not do it and suffer the loss of income or find a way of recouping through shadow earnings.

Concluding Remarks

The Latvian authorities should be applauded for grasping the nettle of progressive taxation but perhaps only with one hand for the way they have chosen to do it. Thus, the solidarity tax creates an incentive for both employers and employees to find ways of avoiding it and find they surely will. A tax accountant once said of the 80% supertax applied to high earnings in pre-Thatcher UK that it was a ‘voluntary tax’. This is also the likely fate of Latvia’s solidarity tax.

The differentiated personal allowance will clearly benefit low earners, if they claim it. In fact it will also benefit people earning well over the average wage. But will the low earners claim? Very few people in Latvia have ever filed an income declaration and we fear that many low earners will not do so now.

Thus at the top end progressivity is likely to be largely avoided and at the bottom end may not be fully claimed.

References

  • Finance Ministry (2015). “Solidaritātes nodokli maksās tikai personas ar algu virs 48 600 eiro gadā,” available at http://www.fm.gov.lv/lv/aktualitates/jaunumi/nodokli/51253-solidaritates-nodokli-maksas-tikai-personas-ar-algu-virs-48-600-eiro-gada
  • Kakwani, Nanak C. (1977). “Measurement of Tax Progressivity: An International Comparison”. Economic Journal 87 (345): 71–80
  • Jara, X. and Leventi, C. (2014). “Baseline results from the EU27 EUROMOD (2009-2013),” EUROMOD Working Papers EM18/14, EUROMOD at the Institute for Social and Economic Research.
  • Saez, E., J. Slemrod, and S. H. Giertz, (2012). “The Elasticity of Taxable Income with Respect to Marginal Tax Rates: A Critical Review.” Journal of Economic Literature, 50(1): 3-50

The Political Economy of the Latvian State Since 1991: Some Reflections on the Role of External Anchors

This brief discusses the role of external anchors or goals such as WTO accession, NATO and EU accession in Latvia’s development strategy since 1991. On the one hand the external goals ‘depoliticised’ many potentially contentious areas of Latvian life. On the other hand, some developments would not have happened or would not have happened as fast without the constraints imposed by the external goals. For example liberalisation of the citizenship laws was prompted by NATO accession and the balance was tipped when the rejection of Latvia from fast-track EU accession talks in December 1997 led Latvia to abandon its quota or ‘windows’ naturalisation system. Most recently, Eurozone accession was an externally defined exit strategy from the austerity episode induced by the economic and financial crisis. Today there are no big external goals left to guide policy making. Home grown problems such as inequality require home grown solutions. But even now an external dependency persists. For example a long needed reform of the financing model of higher education has had to wait for a World Bank report published in September 2014 for action to be taken.

On January 1st, 2015 Latvia assumed the Presidency of the European Union. This milestone represents a certain level of maturity of the Latvian state and offers an opportunity for reflection on some aspects of how politics and political economy have evolved in Latvia between 1991 and today.

After Latvia regained independence in 1991, it faced (at least) two political economy challenges: one was to disentangle the economy from the Soviet system in which it had been deeply integrated, and the second, perhaps more difficult challenge, was to create an independent nation state. At a formal level, the solution to the latter challenge appeared straightforward – assume continuity of the Latvian state. Effectively this meant reinstating the pre-war constitution, which was indeed done for the most part. Symbolically this continuity was signalled by, for example, calling the first post-Soviet parliamentary elections held in June 1993 the elections for the 5th Saeima (parliament). The elections for the 4th Saeima had taken place more than 60 years earlier in October 1931.

At a practical level the challenges were more complex – Latvia had had no practical experience of statehood for nearly fifty years and mistakes were made. For example, Latvia initially diplomatically recognised Taiwan rather than the Peoples Republic of China.

There was a presumption that newly independent Latvia should become a market economy but little consensus on how this should be achieved. This is in contrast to Estonia where a group of ‘young market economy Turks’ were able to implement a kind of zero option i.e. zero tariffs, fast privatisation, etc. In Latvia there were strong protectionist sentiments and the initial privatisation was a muddled process.

Advice and advisers were abundant in post-independence Latvia. In the early 1990s, Latvia was awash with international advisers: the IMF and the World Bank were both present, the Germans were advising on a constitution for the Bank of Latvia, the British were active in public administration reform, the Danish advised on research and higher education and so on. Advice was often conflicting with different advisers promoting their own visions of structures as models that Latvia should adopt e.g. on legal and education systems. Today, we see something akin to this in the Eastern Partnership countries such as Moldova and Ukraine.

There was a general sense of the desirability of a ‘return to Europe’ but no plan or strategy. Nevertheless, even without a conscious plan a strategy emerged – namely a strategy of external anchors.

The external goals or anchors that emerged included the following:

  • World Trade Organisation, 1998
  • NATO, 29 March 2004
  • European Union, 1 May 2004
  • Eurozone, 1 January 2014

The most important effect of the external anchors was that they ‘depoliticised’ many potentially contentious areas of Latvian life. This has been particularly important given the fragmentation that has historically dominated Latvian politics. Thus, in the interwar period, no less than 32 different political parties were represented in the Saeima. In the early post-Soviet parliaments, similar tendencies were observed with newly created parties being the winners in terms of the number of seats in the first four elections. The election of 2006 was the first in which the previously largest party returned as the largest party. Between the first post-Soviet election in 1993 and the 2014 election, there have been no less than 17 governments which mostly have been uneasy coalitions of 3 or 4 partners with divergent views and interests. In this context the benefit of external anchors is self-evident.

The external anchors each contributed in different ways: WTO accession contributed to modify the protectionist sentiments that were rife in the early years of independence. Rather curiously, Estonia, which adopted a radical free trade policy right from the first days of independence, had more difficulties in achieving their WTO membership than ‘protectionist’ Latvia. Estonia was obliged to implement additional economic regulations in order to conform to the rules of the WTO and the EU (to which it was committed to join as its WTO application proceeded), and as a consequence, Estonian WTO accession was delayed to 1999. The WTO accession process also gave Latvia’s fledgling Foreign Ministry invaluable experience of multi-lateral negotiation.

Apart from the obvious security benefit, NATO membership was conditional on the creation of the Latvian anti-corruption Bureau (KNAB) and on the liberalisation of citizenship legislation, the latter because NATO was concerned about the prospect of a member state with a large number of non-citizen residents.

EU accession represents the biggest and most significant anchor. The requirement of candidate countries to accept the EU acquis communautaire took huge swathes of economic and social legislation out of the political arena. While the economic criteria for accession presented few difficulties of principle for Latvia – most people were in favour of a market economy – the requirement of respect for and protection of minorities presented problems for many Latvian politicians and liberalisation of the citizenship law was resisted until after 1997 when the rejection of Latvia from fast-track EU accession talks in December 1997 prompted a rethinking of Latvia’s intransigent position on the quota or ‘windows system’.

It is hard to over-estimate the impact of EU accession on Latvia. What would Latvia be like today if it were not a member state of the EU? There are sufficient tendencies even now in Latvia to suggest we would observe something like a tax-haven, off-shore economy, probably with weak democratic institutions. EU accession has saved the Latvian people from something like such a fate.

Even later in Latvia’s largely self-inflicted financial and economic crisis of 2008-10 it was the ‘Holy Grail’ of accession to the Eurozone that politically anchored Latvia’s famous austerity programme.

What of today? The ‘big’ external anchors are used up, and Latvia today:

  • Is the fourth poorest country in the EU with GDP per capita in 2013 at 67% of the EU average (only Croatia, Romania and Bulgaria are poorer);
  • Is a particularly unequal society – Latvia has some of the worst poverty and inequality indicators in the EU;
  • Has a shadow economy at 23.8% of GDP (data on 2013; Putniņš and Sauka (2014)); and
  • Has an internationally uncompetitive higher education system.

These and other problematic aspects of Latvian life and society are home grown and it is hard to imagine external anchors that can improve poverty or inequality, that can reduce the size of the shadow economy, or which can improve the quality of the Latvian higher education system.

Nevertheless, Latvian policy makers seem to be addicted to the external anchor concept and often find difficult to progress without it. The recent experience of reform of the financing of higher education illustrates. Latvia has historically had a funding mechanism for universities and other higher education institutions based entirely on student numbers. The lack of a link between funding and quality has resulted in a Latvian higher education system that is strong on enrolment but low on quality e.g. as measured by peer-reviewed publications. At some level this has been understood and there has been much talk of reform. Although various reports and evaluations have been published, there has been little progress on concrete reform until the Ministry of Education commissioned the World Bank in December 2013 to produce a report on funding models for Latvia. The final report was delivered in September 2014 and action has now been taken to adopt the World Bank recommended three-pillar model where the funding criteria will now include performance and innovation.

Of course, the new model will not solve all the problems of Latvian higher education – far from it – but it illustrates the pervasive nature of policy makers seeming dependency on external anchors.

References

  • Putniņš, Tālis & Arnis Sauka (2014). “Shadow Economy Index for the Baltic Countries. 2009-2013,” The Centre for Sustainable Business at SSE Riga, May 2014.

Equity and Efficiency in the Latvian Tax-Benefit System

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There is a trade-off between two major objectives of a tax-benefit system: equity and efficiency. The tax-benefit systems that redistribute a lot of income tend to generate disincentives to work. The tax-benefit systems that create good incentives to work and earn, are less effective in mitigating poverty, social exclusion and deprivation. In this brief we argue that, when contrasted to other EU countries, the Latvian tax-benefit system is less effective in achieving either of the objectives.

Equity-Efficiency Trade-Off

There is a fundamental trade-off between the two principal objectives of a tax-benefit system – income redistribution and efficiency. On the one hand, income redistribution is desirable as it helps to mitigate socially undesirable market outcomes such as poverty and deprivation. On the other hand, more income redistribution is often associated with higher distortions to labour supply and work effort.

There is no universal prescription as to how much a government should redistribute. The answer to this question depends, among other factors, on the relative value that society (government) assigns to the welfare of different population groups, and on the individuals’ labour supply elasticity.

However, a given degree of income redistribution can be achieved at a different cost of efficiency. In this brief, we analyse the degree of income redistribution generated by the tax-benefit system and work incentives in Latvia in the context of other EU countries. In our analysis, we use the European microsimulation tax-benefit model EUROMOD (Sutherland and Figari, 2013) version G2.0, EU-SILC data, and the analysis framework developed by Jara and Tumino (2013).

Income Redistribution in the EU

EU countries differ substantially in terms of inequality of original income and in terms of the degree of redistribution generated by the tax-benefit system (see Figure 1, data on 2007 and 2013). The Gini coefficient of equivalised household original income (which consists of income from employment and self-employment, property income, private pensions, private transfers and other relatively minor components) ranges from around 0.4 (Cyprus, Netherlands) to almost 0.55 (Romania in 2007, Ireland in 2013).

Inequality of original income in Latvia in 2007 was at the EU average level (Gini coefficient of 0.47), but the degree of income redistribution generated by direct taxes, benefits and pensions was the lowest in the EU. As a result, the inequality of disposable income in Latvia in 2007 was the highest in the EU (Gini coefficient of 0.37). Part of the answer as to why the degree of income redistribution in Latvia is so low is a relatively small contribution of pensions to redistribution – it is almost half of that observed in the EU on average, despite the fact that the share of public pension recipients in the total Latvian population in 2007 was above the EU average. Another important factor was the very minor role of means-tested benefits: in the EU on average, means-tested benefits generate a reduction in Gini coefficient by about 0.02, while in Latvia the corresponding figure is just one tenth of this.

Figure 1. Gini coefficients of original equivalised household income and degree of redistribution generated by tax-benefit systems in the EU in 2007 and 2013

fig1afig1b

Source: EUROMOD statistics, authors’ calculations.

In the course of the crisis and the following recovery, the degree of redistribution in Latvia increased (see lower panel of Figure 1). An important factor behind the increase was growing number of pension recipients and an increase in the average size of pensions (both in absolute terms and relative to employment income). The increase in the number of pension recipients was not a result of changes in eligibility criteria, but was due to population ageing and the fact that more people applied for other types of pensions. The growth in the average size of pension was due to generous indexation of pensions in 2008 and compositional changes, as pensions of new pensioners until 2012 were larger than the average pension. Another reason for a growing degree of redistribution was an increase in the size and the number of recipients of means-tested benefits (mainly Guaranteed Minimum Income (GMI) benefit). This was a result of reforms in the provision of the means-tested benefits and of falling incomes from employment, which made more people eligible for the social assistance programmes. Nevertheless, despite the increase in recent years, the degree of income redistribution in Latvia remains one of the lowest in the EU.

Work Incentives

The existence of a trade-off between income redistribution and better work incentives suggests that tax-benefit systems that ensure less income redistribution are likely to generate better work incentives. Jara and Tumino (2013) have demonstrated the existence of this trade-off in the EU countries in 2007-2010 by identifying a negative and statistically significant correlation between Gini coefficients and Marginal Effective Tax Rates (METR). The METR is a measure that is commonly used to quantify work incentives at the intensive margin. It shows what proportion of a small increase in earnings (which results from e.g. an increase in the supplied hours of work) is lost as a result of extra tax payments or foregone benefits that the person is no longer eligible for after the increase in earnings. The negative correlation identified in Jara and Tumino (2013) suggests that countries with less income redistribution (i.e., higher Gini coefficients) tend to have better work incentives (lower METRs).

In Latvia, the mean METR in 2013 was 32.2%, only slightly below the EU average (34.5%), and much higher than the average in Estonia (22.8%) and Lithuania (27.4%), despite a lower degree of income redistribution (EUROMOD statistics). Another feature of the Latvian tax-benefit system is that it is characterised by especially high METRs for poor individuals. Thus, in 2013, 94% of individuals who faced METRs in excess of 50% belonged to the two bottom deciles of distribution of equivalised disposable income. This is different from many other European countries, where distribution of high METRs is either more even across deciles or rising towards the top end of income distribution (Jara and Tumino (2013), data for 2007).

The main reason for high METRs faced by the poorest population groups in Latvia is the design of means-tested benefits (GMI and housing benefits), which generates 100% METRs for the recipients of these benefits. Namely, for each additional euro earned, the amount of benefit is reduced by one euro, which leaves the net income unchanged. This adversely affects employment incentives for the poorest individuals and increases the poverty risk.

Figure 2 illustrates mean METRs by deciles of equivalised disposable income in Latvia and shows the contribution of taxes, benefits and social insurance contributions (SICs) to the mean METRs. It clearly demonstrates that high METRs in the bottom deciles result mainly from the contribution of benefits, which disappears in the fourth decile. The contribution of SICs is slightly smaller in the bottom decile, which is due to the fact that the proportion of employed individuals is smaller in the bottom decile. For the same reason, and also because of basic tax allowances, the contribution of direct taxes is smaller in the bottom deciles, but then the contribution of taxes levels off, reflecting the Latvian flat tax rate.

Figure 2. The contribution of direct taxes, benefits and social insurance contributions (SIC) to METRs in Latvia by deciles of equivalised disposable income in 2013

fig2

Source: authors’ calculations using EUROMOD-LV

In their study on the incentive structure created by the tax and benefit system in Latvia, the World Bank (2013) pointed out the problem of bad work incentives generated by Latvian means-tested benefits. Our results, which are based on a population-representative database of incomes, also identify means-tested benefits as the major contributor to high METRs in the lowest deciles of the income distribution. Another concern expressed by the World Bank (2013) was that the problem of informal employment (either in the form of undeclared wages or work without a contract) can be exacerbated by high participation tax rates and METRs.

Conclusion

The Latvian tax-benefit system is characterized both by a relatively low degree of income redistribution and relatively weak work incentives, as measured by METRs. Recipients of means-tested benefits (GMI and housing benefits) are faced with 100% METRs, as benefits are withdrawn at the same rate as household income rises. This creates disincentives to increase labour supply for low-paid/low-skilled individuals, and hence creates a risk of poverty traps. Evidence from the literature suggests that the labour supply of low paid workers is particularly sensitive to the incentives generated by the tax-benefit system, hence reforms that would bring down METRs in the bottom deciles could yield positive results in terms of employment of low paid/low skilled workers.

A potential reform is to introduce either a gradual phasing out of the means-tested benefits, or to exclude a certain amount of employment income from the income test for the means-tested benefits. Such reforms would be targeted at the bottom end of the income distribution, help combat poverty, improve the incentive structure of the Latvian tax-benefit system, and positively affect the labour supply of low-skilled/low-paid workers.

References

  • EUROMOD statistics on Distribution and Decomposition of Disposable Income, accessed at http://www.iser.essex.ac.uk/euromod/statistics/ using EUROMOD version no. G2.0, retrieved on October 14, 2014
  • Jara, H. Xavier & Alberto Tumino (2013). “Tax-benefit systems, income distribution and work incentives in the European Union,” International Journal of Microsimulation, Interational Microsimulation Association, vol. 1(6), pages 27-62.
  • Sutherland, Holly & Francesco Figari (2013). “EUROMOD: the European Union tax-benefit microsimulation model,” International Journal of Microsimulation, Interational Microsimulation Association, vol. 1(6), pages 4-26.
  • World Bank (2013). “Latvia: “Who is Unemployed, Inactive or Needy? Assessing Post-Crisis Policy Options”. Analysis of the Incentive Structure Created by the Tax and Benefit System. Financial Incentives of the Tax and Benefit System in Latvia,” European Social Fund Activity “Complex support measures” No. 1DP//1.4.1.1.1./09/IPIA/NVA/001

Entrepreneurship in Latvia and Other Baltic States: Results from the Global Entrepreneurship Monitor

Entrepreneurship in Latvia Policy Brief Image

This policy brief summarises the results and implications of an upcoming Global Entrepreneurship Monitor (GEM) 2012 Latvia Report: a study on the entrepreneurial spirit and the latest trends in entrepreneurial activity in Latvia. The results suggest that Latvia is a rather entrepreneurial country (it rates second out of all EU countries by the share of population in early-stage entrepreneurial activity). GEM also finds that Latvian early-stage entrepreneurial activity is counter-cyclical. Early-stage entrepreneurship and self-employment have been important supports for those who were hit by the crisis in 2008-2009. Latvian entrepreneurs are measured to have strong international orientation and growth ambitions. The majority of them are young and middle-age males; in turn, females and the older age group (55-64) represent an “untapped entrepreneurial resource” potential to be addressed by policymakers.

And Then There Were Eighteen? Will Latvia Join the Euro Zone in 2014?

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Latvia’s government is zealously preparing for accession to the Euro Zone. Prime Minister Valdis Dombrovskis is expected to request the European Central Bank (ECB) and European Commission (EC) prepare their respective convergence reports on Latvia’s readiness to enter Economic and Monetary Union (EMU) within the next two months. The expectation is that Latvia will join on 1 January 2014. Indeed, the three-party coalition government has long been readying for the technical changeover to the euro. The Cabinet of Ministers adopted a detailed national euro changeover plan in September 2012 and appointed a high-level steering committee to manage the process. The government has launched a controversial multi-million euro advertising blitz aimed at winning over Latvia’s skeptical public.[1]  Parliament passed the law on euro adoption in a 52-40 vote on 31 January 2013.

What could possibly go wrong? Although unlikely, a referendum or the collapse of the Dombrovskis coalition government could yet derail Latvia’s euro ambitions.

Latvia and Europe

All Latvian governments have steered a steady pro-Western course in the two decades since the fall of the Soviet Union. International recognition was followed by membership of the Council of Europe, World Bank and the other minor and major international organizations that make up the international community. However, the big attractions were the Western clubs – NATO and the European Union. Membership of both was achieved in the two ‘big bang’ enlargements of 2004. In all the giddy excitement of finally joining the Western world and seemingly slipping away from Russia’s bear-hug, Latvia initially aimed to quickly join the Euro Zone, setting a target of 1 January 2008.

However, the government proved half-hearted in its efforts, preferring to enjoy the low-hanging fruit of a cheap credit-driven booming economy rather than balance the budget. Both government and public entered a period of rabid consumption and spending that resembled nothing so much as sailors in a pub after a year at sea. Unsurprisingly, Latvia rapidly slipped far away from meeting the Maastricht criteria on inflation. Accession to the Euro Zone was quietly dropped from the political discourse.

However, euro adoption returned as a frontline government initiative after the dramatic economic collapse of 2008, and the advent to power of Valdis Dombrovskis, the Baltic Angela Merkel. Dombrovskis will soon have been in power for four years, a lifetime in Latvian politics where, prior to Dombrovskis, the average prime minister served for less than a year.[2] He has overseen harsh austerity measures of tax hikes and spending cuts, but remains surprisingly popular (not least because his party was in opposition during the post-2004 economic bubble years). He has twice been re-elected to office, proving once again that Latvians favour monochrome technocrats over colourful populists.

Despite a return to growth (in 2012 Latvia recorded the highest GDP growth in the EU), the government has maintained tight control over spending. Indeed, it has even perhaps been over-zealous, with both the IMF and EU recently chipping in with criticism of the social spending cuts that Latvia has made to its 2013 budget.[3] Nevertheless, Latvia is now applauded as a model of austerity and frequently used as a positive contrast to Greece.[4]

Moreover, Latvia is now on the cusp of meeting the Maastricht criteria for accession to the Euro Zone. A January 2013 IMF staff report argued that Latvia meets the public debt and budget deficit criteria, although inflation and interest rates may be a hurdle depending on the EU member states used for the reference value calculation (will Greece be treated as an outlier?).[5] The informal political signals from both the EC and ECB are clearly positive. However, euro accession could still be derailed by either a referendum or a change of government.

Let the People Decide?

The biggest potential hurdle remains the threat of a public referendum. The EC and ECB will not contemplate Latvia’s accession to the euro zone with the Damocles Sword of a referendum hanging over the process. Moreover, public support for the euro remains low, with just 8% of the public wanting the euro introduced quickly and 41% being absolutely opposed to the currency.[6] A vote would be a real throw of the dice.

A citizen’s initiative aiming to delay euro adoption, by demanding a vote on the timing of accession, was submitted to Latvia’s electoral authority (by the awkwardly named Latvia’s Social Democratic Movement for an Independent Latvia, a fringe party that has never been elected to parliament) in late 2012. The Central Election Commission must make a final decision on whether to allow the initiative to go ahead by February 3. However, the legal opinions provided by scholars, the Latvian ombudsman’s office and the Latvian parliament’s legal advisers indicate that the initiative is likely to be rejected because:

  • Latvians effectively voted to join the euro when voting on accession in 2003;
  • The Council of Ministers is the only institution authorized to choose the date of accession to the euro zone, thus any initiative specifying a date (or conditions that need to be met) is not legal;
  • The text of the initiative conflicts with the constitution.[7]

While the ruling could be challenged in Latvia’s Constitutional Court or a reworded initiative submitted to the Central Election Commission, the weight of the legal opinions already delivered indicates that these efforts would be unlikely to succeed. At worst, the uncertainty could delay euro adoption past January 1, 2014 (and the Latvian legal system can certainly be ponderous at times). The same is true of any parliamentary attempt to initiate a referendum by having a one-third minority of deputies force the president to sit on the euro adoption law while citizens sign an initiative.[8] Indeed, legal opinions cited by the President state that because euro introduction is a treaty obligation, a majority of parliamentarians (51 of 100) would need to sign any initiative attempting to call a referendum. The opposition will not be able to rustle up a majority of parliamentary deputies (although the legal haggling could delay the date of euro adoption).

Coalition Collapse?

The other risk is a collapse of the government coalition. While the Reform Party and the prime minister’s Unity Alliance are firm supporters of euro adoption, the third coalition member – the radical right populist National Alliance is more torn. Its rank and file membership is largely against the euro, primarily for nationalist reasons (they see the Latvian Lat as a symbol of sovereignty and national identity). One NA parliamentarian even broke coalition ranks and voted against euro adoption. A motley conglomeration of far right radical groups and nationalist intellectuals has begun speaking out against the ‘commercialization’ and ‘westernization’ of Latvia, and sees the euro adoption battle as the opportunity to draw a final line in the sand. They are likely to put the National Alliance’s ministers and parliamentary deputies under severe pressure.

Indeed, the National Alliance already played the ‘euro card’ in November 2012, successfully extracting budgetary concessions for pet projects from Prime Minister Dombrovskis. They may well play it again, as they seek a greater number of ministerial portfolios. However, as Dombrovskis pointed out, opening up of the coalition agreement could well lead to the collapse of a government already creaking at the edges.

Conclusion: After Dombrovskis

There is strong political resolve to lever Latvia into the Euro Zone. Moreover, the unusual confidence emanating from both government officials and the Bank of Latvia indicates that certain reassurances have been made in Brussels and Frankfurt. Indeed, Latvia’s glowing current reputation as the poster child of austerity gives it a once-in-a-decade political momentum. Latvia’s entry into the euro on schedule on January 1, 2014 is more likely than not.

However, looking to the future, one pertinent question needs to be addressed. Which Latvia will we see in the Euro Zone? The grey, serious, disciplined almost Teutonic Latvia of Valdis Dombrovskis? Or the reckless drunken sailor, that has marked much of Latvia’s post-communist era?

Naturally, Dombrovskis holds the key to this question. He is expected to leave domestic politics after the October 2014 parliamentary election, probably to cash in his international political capital with a well remunerated European post (the timing is right for a 2014-2019 European Commissioner portfolio). At best, if re-elected, he might be persuaded to stay on to oversee Latvia’s presidency of the European Union in 2015.  In any case, while Latvia has been reborn as a paragon of economic virtue under his watch, these assets have not been institutionalized. Dombrovskis will leave behind the same old fractured, frail and quarrelsome parties, politicians and oligarchs that he inherited. Recent international criticism of disequilibrium in government welfare and tax policies hints that political backsliding has already begun.

Latvia is at its strongest when its political, economic and administrative elite units in pursuit of some concrete target. Independence from the Soviet Union, then NATO and EU accession, followed by harsh austerity measures and now even Euro Zone accession were achieved far quicker than many observers had believed possible. International conditionality has made up for the absence of ideology and ideas as moral and political compasses in Latvian politics. However, when left to their own devices, Latvian politicians have tended to run amok. After Latvia enters the Euro Zone it will be left without an all-encompassing political plan. Quite frankly, that is rather worrying.

References

 


[1] See the Latvia euro changeover site. Available at:  http://www.eiro.lv

[2] Pettai, Auers and Ramonaite (2011), ‘Political Development’ In Marju Lauristin (ed.), Estonian Human Development Report 2010/2011: Baltic Way(s) of Human Development: Twenty Years On. Tallinn: Eesti Koostoo Kogu. 144-163.

[3] Aaron Eglitis (2013), ‘EU joins IMF in criticizing Latvian cuts to tax, social spending’. Bloomberg news.

[4] Anders Aslund, an ardent cheerleader of Latvia’s austerity programme, puts the country’s success down to ‘front loading’ reforms, particularly fiscal adjustment . See Anders Aslund (2013) ‘Why austerity works and stimulus doesn’t’.

[5] IMF Staff Report No. 13/28 (January 2013). Also see Swedbank Analysis (1 August 2012). ‘Fulfilling the Maastricht Criteria – mission possible for Latvia and Lithuania?’

[6] Although another 42% had a positive attitude towards the euro, but did not want to see it hurriedly introduced. See DNB Banka (November 2012), ‘Latvijas Barometrs: Eiro ieviešana Latvijā’.

[7] The legal opinions can be found on the Central Election Commission’s homepage.

[8] See Article 1, paragraph 3 in the law on referendums and initiatives.

Latvian Unemployment is Cyclical

20121210 Latvian Unemployment is Cyclical Image 01

In terms of output decline and increase in unemployment, the economic recession in Latvia that started during the 2008-09 financial crisis was one of the most severe in the world. Using modern methods of statistical analysis, we demonstrate that the changes in unemployment should be attributed primarily to cyclical, rather than structural factors. This answer brings important implications for anti-crisis policy in Latvia and elsewhere in the world: it suggests that the surge in unemployment was largely a consequence of Latvia’s austerity policy, and that today, broader economic measures to support further economic recovery can be effective. 

During the 2008-2009 recession Latvia experienced the EU’s largest and fastest increase in unemployment. This is illustrated in Figure 1 where it can be seen  that the unemployment rate rose by approximately 14 percentage points from a low of 6.2% in early 2008 to 20.4% at the end of 2009. However, labour market recovery has not been equally  rapid, with unemployment in 2011 and the first half of 2012 settling at around 16%. This corresponds to a decline of less than 5 percentage points from the peak. The most recent quarter has seen an improvement with the unemployment rate falling to 13.5%. Partly, the decline can be attributed to seasonal factors (seasonally adjusted unemployment rate declined by less; from 15.7% to 14.2%). However, if discouraged workers are counted, the reduction in unemployment was smaller and the rate of unemployment still stood at 16.8% in the 3rd quarter.

This observed persistence in unemployment is seen by many as a signal of the structural nature of the shocks that hit the economy during the recession and of the further intensification of structural problems.

Figure 1. Unemployment Rate (Age Group 15-74), Seasonally Adjusted, (%)[1]

 Fig1

Note: Discouraged workers are those economically inactive who mentioned loss of hope to find a job as the main reason for not looking for a job.

Source: Central Statistical Bureau of Latvia, authors’ calculations.

For example, Krasnopjorovs (2012)[2] argues that there is a structural mismatch in the Latvian labour market, which mainly takes the form of a skills mismatch and concludes that the “employment rate now is similar to that observed in “normal times” of 2002-2004, [which] suggests a rather small [if any] negative output gap and a large share of structural unemployment in total unemployment”. Likewise, the Ministry of Finance of Latvia (2012)[3] argues that in the medium term, supply and demand mismatches will intensify. Thus, raising the risks of structural unemployment and, while not explicitly reporting their NAIRU estimates, the reported estimate for the output gap in 2012 is just -0.2% of potential GDP, but for 2013, a positive output gap of 0.7% is forecast.

The European Central Bank (2012)[4], when discussing inflation prospects in Latvia, identifies the situation in the labour market as a potential source of risk, as “labour shortages in certain sectors have appeared, suggesting that unemployment is likely to be close to its natural rate”. The European Commission’s (2012)[5] estimate for the NAIRU in 2012 is 14.6%, which is very close to the actual unemployment rate. The IMF (2012)[6] is the least categorical in characterising the nature of Latvian unemployment, arguing that “lack of skilled labor could become a constraint to growth and put pressure on wages unless the long-term unemployed re-enter the labor market”, at the same time forecasting that “[a] negative output gap and high unemployment should keep core inflation (…) low, and contribute to a gradual decline in headline inflation”.

Other commentators, e.g. Krugman[7] have argued that Latvian unemployment is largely explainable by cyclical factors.

Which explanation is correct is important both for current policy purposes and for the interpretation of past policy. Thus, “if cyclical factors predominate, then policies that support a broader economic recovery should be effective in addressing long-term unemployment as well; if the causes are structural, then other policy tools will be needed”.[8] On the other hand, “higher structural unemployment alters the role of short-run stabilization policies, including monetary policy, by increasing the possibility that expansionary policies will trigger inflation at higher rates of unemployment than otherwise”.[9]

In what follows, we evaluate the extent to which the recent evolution of Latvian unemployment can be interpreted as structural and provide some policy implications. We use three alternative approaches and all three point in the same direction: overwhelmingly both the increase in unemployment and its recovery are explainable by cyclical factors.

Decomposition of the Unemployment Rate into Structural and Cyclical Components

Our first approach is to directly decompose unemployment into structural and cyclical components. This is based on the following intuitive reasoning: when structural change occurs, unemployment is a result of changes in the composition of the labour market, i.e. the skill requirements of the jobs available today no longer match the skillset of the workers who are searching for jobs. On the other hand, when cyclical factors dominate, we would expect similar increases in unemployment across all sectors and locations. Using a formalised version of this approach, we conclude that changes in Latvian unemployment during the recession can be explained by changes in the unemployment rates in particular sectors and occupations, while the shares of the sectors and occupations in labour supply have been practically unchanged.

Following Lazear and Spletzer (2012)[10], we decompose the changes in the unemployment rate into structural and cyclical components, where the first component comes from changes in unemployment rates in a particular group assuming an unchanged structure, while the second component represents compositional changes in the structure of labour supply.

In order to implement this analysis, we use the most disaggregated categories of the sector of previous employment and occupations, which are obtainable from quarterly micro level LFS data. This covers 10 sectors of production and 9 occupations. We use a broad definition of unemployment and include discouraged workers to account for the nominal reduction in unemployment, which occurs just because people stop looking for a job. At the time of writing, data is only available for 2007-2011; hence, our analysis does not cover 2012.

Figures 2 and 3 show the decomposition of unemployment rate changes by sectors of production and by occupations.

Figure 2. Decomposition of Year-on-Year Changes in Unemployment Rate by Sectors of Production, Including Discouraged Workers, (% points)
Fig2
 
Note: Includes only those unemployed who stopped working less than 8 years ago, for those who stopped working more than 8 years ago data on the previous sector of employment is not available; includes only those who indicated the sector of previous employment.

Source: Central Statistical Bureau of Latvia, authors’ calculations.

The sectoral decomposition suggests that the increase in unemployment in 2009-2010 can be fully attributed to cyclical factors – the structural component was small and even negative. The negative structural component is explained mainly by a reduction in the share of industry and construction in labour supply, which were sectors characterised by relatively high rates of unemployment.

Figure 3. Decomposition of Year-on-Year Changes in Unemployment Rate by Occupations, Including Discouraged Workers, (% points)

Fig3

Note: Includes only those unemployed who stopped working less than 8 years ago, for those who stopped working more than 8 years ago data on the previous occupation is not available; includes only those who indicated previous occupation.

Source: Central Statistical Bureau of Latvia, authors’ calculations.

The occupational decomposition also suggests that changes in the rate of unemployment have been largely cyclical. The positive structural component in 2010Q1 can be explained by an increase in the share of civil servants, service workers, as well as shop and market sales workers. The positive structural component in 2010Q4 and 2011Q2 is a result of an increased share of craft and related trades workers, and elementary occupations.

In sum, the shares of both sectors and occupations in the economy have remained largely unchanged with unemployment changes explained by sectoral or occupational changes in unemployment rates.

Evaluating mismatch

A second approach is to directly estimate labour-market mismatch. Structural unemployment is usually defined as resulting from a mismatch between the labour demand and the skillset and locations of those looking for jobs. “[M]ismatch is defined as a situation where industries differ in their ratio of unemployed to vacancies”.[11] Using this approach our estimates show no significant mismatch between available vacancies the skills of workers.

To assess changes in the matching during the crisis, we calculate relative standard deviation of the number of unemployed per vacancy across sectors:

fig4a

where x(i) is number of unemployed per vacancy in sector[12] i (including discouraged workers) and x¯ is average number of unemployed per vacancy across sectors.

Figure 4. Relative Standard Deviation of Unemployed per Vacancy across Sectors
Fig4

Source: Central Statistical Bureau of Latvia, authors’ calculations.

Figure 4 presents the results of the relative standard deviation estimation. RSD increased in the beginning of the recession, but it has been declining since early 2009 indicating no increase in the degree of mismatch.

Estimating the Beveridge Curve

The third method uses the search and matching approach as developed by Pissarides (2000)[13] where the emergence of structural unemployment is signalled by deterioration in the efficiency of labour-market matching. Again, the conclusion is that except during the boom, when matching appears to have improved, Latvian unemployment cannot be explained by changes in the efficiency of matching.

We follow the Beveridge curve approach proposed by Barlevy (2011)[14] who follows Petrongolo and Pissarides (2001)[15] in assuming that matches in the labour market can be described by a Cobb-Douglas function, in which the number of matches depends on the unemployment rate, the vacancy rate, the productivity of the matching process, and elasticity of the number of matches with respect to the unemployment rate. The flow into unemployment is defined by the separation rate into unemployment; while the flow out of unemployment is given by the matching function. Equating the two flows yields the Beveridge curve which, given a constant separation rate, defines a negative relationship between vacancies and the unemployment rate.

Figure 5 plots the Beveridge curve for Latvia over 2005 – 2012Q2. We first observe that the Beveridge curve appears to have shifted downwards in 2007, pointing to an improvement in matching (an increase in the productivity parameter) as the economy approached the top of the boom. This is consistent with the idea that employers facing labour shortage became less “picky” in their hiring decisions. Starting from 2010, as the unemployment rate gradually declined there appears to have been a movement back along the Beveridge curve though perhaps with a minor outward shift.

Figure 5. Unemployment Rate (incl. Discouraged Workers) vs. Vacancy Rate in 2005-2012q2, Seasonally Adjusted
Fig5

Source: Central Statistical Bureau of Latvia, authors’ calculations.

Estimating the parameters of the Beveridge curve permits assessment of changes in matching. To estimate A, we divide the sample into three periods and fit the Beveridge curve for these three periods: 2005-2006 (beginning of the boom), 2007-2009 (the peak and the recession) and 2010-2012 (the period of gradual reduction in unemployment). Apart from data on unemployment and the vacancies, we need to know the separation rate. Barlevy (2011)[16] argues that the relevant separation rate is likely to be fairly stable over the cycle – he assumes a constant separation rate of 0.03 for the U.S. (one can think of this separation rate as the flow of people from employment to unemployment in “normal” times). In the absence of concrete evidence to the contrary, we also assume a constant separation rate. However, this assumption is not crucial for our analysis, since we are interested in the change in A and not the level of A.

Figure 6 shows the fitted Beveridge curves, as well as the seasonally adjusted data over the period ranging from 2005 up to the second quarter of 2012.

Figure 6: Fitted Beveridge Curves and Actual Unemployment Rate (incl. Discouraged Workers) vs. Vacancy Rate in 2005-2012q2, Seasonally Adjusted
Fig6

Source: Central Statistical Bureau of Latvia, authors’ calculations.

Our estimates of the parameters are presented in Table 1. The results show that A declined in 2010-2012, suggesting a slight deterioration in matching, yet A estimated on 2010-2012 data is slightly higher than A estimated on 2005-2006 data, the period which probably comes closest to the definition of “normal” times in our sample.

Table 1. Estimated Parameters of the Beveridge Curve

Table1

Source: Authors’ calculations.

Using estimated  and the formula for the steady-state vacancy rate, we are able to calculate implied changes in A over the whole period under consideration. To do this, we employ two alternative estimates of : (1) , the estimate on 2005-2006 data, which can be viewed as  estimate for “normal” times and (2) , average of  estimates for the three periods.

Figure 7 illustrates the results of the estimation. These suggest that A declined from its peak in the beginning of 2008, in turn suggesting that matching has deteriorated as compared to the boom years. However, A started to grow in the end of 2011 and is currently above its level in 2005-2006. More importantly, our results suggest that there was no notable deterioration in matching since mid-2009, i.e. neither the increase in unemployment in the recession nor the subsequent recovery have been accompanied by significant intensification of labour market mismatches.

Figure 7: Implied A estimate

Fig7

Source: Authors’ calculations.

Finally, our estimates of the Latvian Beveridge curve imply that changes in matching efficiency have been practically absent (except in the boom). Hence, changes in unemployment can largely be explained by cyclical factors.

Conclusion

Our analysis indicates no significant change in structural unemployment in Latvia during the 2008-2009 recession and afterwards. First, decomposition of the unemployment rate into structural and cyclical components illustrates the dominant role of the cyclical component. Second, direct estimation of mismatches also shows no evidence to support a structural explanation of the change in the Latvian unemployment rate. Finally, our estimates of the Beveridge curve during the period suggest that the efficiency of matching did not deteriorate during the recession and afterwards.

Accordingly, we conclude that in the course of the crisis not only did Latvia fall well below its long-term output trend, but Latvia is still operating below potential. This has implications for the assessment of Latvia’s internal devaluation policy. To put it in Blanchard’s (2012)[17] words: “Is it a success? The economic and social cost of adjustment has been substantial. Output further contracted by 16% in 2009, and is still 15% below its 2007 peak. Unemployment increased to more than 20% and still stands at 16% today, far higher than any reasonable estimate of the natural rate. Was there another, less costly, way of adjusting, through floating, and a slower fiscal consolidation? The truth is we shall never know”. The evidence presented here does not directly help to evaluate alternatives – still, it confirms that the chosen course was extremely costly and that today broader economic measures to support further recovery can be effective.

References

  • Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011
  • Bernanke (2012), “Recent Developments in the Labor Market,” remarks to the National Association for Business Economics, March 26, 2012
  • Blanchard (2012), “Lessons from Latvia”, June 2012
  • Daly, Hobijn, Sahin, and Valletta (2012), “A Search and Matching Approach to Labor Markets: Did the Natural Rate of Unemployment Rise?,” Journal of Economic Perspectives 26(3), Summer 2012, pp. 3-26
  • Daly, Hobijn, and Valletta (2011), “The Recent Evolution of the Natural Rate of Unemployment,” IZA Discussion Paper No. 5832, July 2011
  • European Central Bank (2012), “Convergence report”, May 2012
  • European Commission (2012), Autumn 2012 Forecast Exercise, Estimates of output gap and of potential output and their determinants, https://circabc.europa.eu, November 2012
  • IMF (2012), “Republic of Latvia: First Post-Program Monitoring Discussions”, July 2012
  • Krasnopjorovs (2012), “What is missing in Krugman’s structural unemployment story?”, blog on Bank of Latvia website, June 2012.
  • Krugman, The Conscience of a Liberal, blog on New York Times, http://krugman.blogs.nytimes.com/?s=latvia
  • Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012
  • Ministry of Finance of Latvia (2012), “Convergence programme of the Republic of Latvia 2012-2015”, April 2012
  • Petrongolo and Pissarides (2001), “Looking into the Black Box: A Survey of the Matching Function,” Journal of Economic Literature, 39(2), June 2001, pp. 390–431
  • Pissarides (2000), Equilibrium Unemployment Theory (Second Ed.). Cambridge, MA: MIT Press

[1] Figure 1 uses data unadjusted for the results of the census  carried out in Latvia in the first half of 2011 which showed  that the population and the workforce was less than previously thought. This has implications for the calculation of all labour market statistics but the official statistics not yet been revised for years before 2011. Accordingly, for consistency over time, we use unadjusted data.

[2] Krasnopjorovs (2012), “What is missing in Krugman’s structural unemployment story?”, blog on Bank of Latvia website, June 2012

[3] Ministry of Finance of Latvia (2012), “Convergence programme of the Republic of Latvia 2012-2015”, April 2012

[4] European Central Bank (2012), “Convergence report”, May 2012

[5] European Commission (2012), Autumn 2012 Forecast Exercise, Estimates of output gap and of potential output and their determinants, November 2012

[7] Krugman, The Conscience of a Liberal, blog on New York Times

[8] Bernanke (2012), “Recent Developments in the Labor Market,” remarks to the National Association for Business Economics, March 26, 2012

[9] Daly, Hobijn, and Valletta (2011), “The Recent Evolution of the Natural Rate of Unemployment,” IZA Discussion Paper No. 5832, July 2011

[10] Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012

[11] Lazear and Spletzer (2012), “The United States Labor Market: Status Quo or a New Normal?,” NBER Working Paper Series, No. 18386, September 2012

[12] Here we use data on vacancies from the Central Statistical Bureau (data from enterprise surveys), since this data is more representative of the whole economy than the data on registered vacancies from the State Employment Agency. The latter is likely to be biased towards vacancies for low-qualified workers, as employers opt for different search methods for higher level positions. This is supported by the fact that, e.g. in 2012 vacancies for craft and related trades workers, plant and machine operators, and assemblers, as well as elementary occupations accounted for 50-60% of all vacancies registered with the State Employment Agency, while in the Statistical Bureau data these vacancies accounted for only about 20% of all vacancies.

[13] Pissarides (2000), Equilibrium Unemployment Theory (Second Ed.). Cambridge, MA: MIT Press

[14] Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011

[15] Petrongolo and Pissarides (2001), “Looking into the Black Box: A Survey of the Matching Function,” Journal of Economic Literature, 39(2), June 2001, pp. 390–431

[16] Barlevy (2011), “Evaluating the Role of Labor Market Mismatch in Rising Unemployment,” Economic Perspectives, 35(3), July 28, 2011

[17] Blanchard (2012), “Lessons from Latvia”, June 2012

The Distributional Impact of Austerity Measures in Latvia

20180114 Individual Retirement Timing Image 02

For a country of its size, Latvia was mentioned in the last decade’s macroeconomic discourse remarkably often: first, for its exceptional growth up to 2007, then – for a dramatic GDP contraction in the aftermath of the 2008 financial crisis, and for the so-called “internal devaluation” policy that was the cornerstone of Latvia’s recovery strategy. Now, when GDP recovery is underway for 9 quarters, Latvia is held up as an example of a country that paved its way out of the crisis with decisive and timely budget austerity measures. The size of budget consolidation package was remarkable, reaching almost 17% of GDP in 2008-2011. Today, when there is so much talk about austerity in the context of the Eurozone debt crisis, Latvian consolidation experience is of particular interest. In this brief, we are looking at the distributional impact of selected implemented austerity measures, using a microsimulation tax-benefit model EUROMOD. Our results suggest that the impact of these measures is likely to have been progressive, meaning that rich population groups are bearing a larger part of the burden.

From Boom to Recession

The “Baltic Tigers” – a term coined to praise the Baltic countries for their dynamic development in the 2000s, especially after their accession to the EU in 2004. During 2004-2007, average annual GDP growth in the Baltics exceeded 8% (in Latvia average growth was 10%). The growth was to a large extent driven by an externally financed credit bubble, leading to overheating of the Baltic economies: inflation was skyrocketing, unemployment was at historically low levels, and current accounts posted double-digit deficits. Before the outbreak of the crisis, the Latvian economy was in the most vulnerable position: Estonia was better situated thanks to prudent fiscal policy implemented in the “good” times, whereas Lithuania was less exposed thanks to its private sector being relatively less indebted.

The growth slowdown in Latvia began in 2007 and was initially triggered by the government’s adopted “anti-inflation plan” and the two of the biggest banks’ actions aimed at restricting credit expansion. Altogether, this initiated a decline in real estate prices. By December 2007, the average price of a square metre in a standard-type apartment in Riga had fallen by 12% from its peak in July (Arco Real Estate, 2008). Construction, retail trade and industrial production growth slowed down in the second half of 2007. GDP quarter-on-quarter growth approached zero by end-2007 and turned negative in the 1st quarter of 2008. In August 2008, the second largest Latvian commercial bank, domestically owned Parex Bank, faced deposit run and was unable to finance its syndicated loans, and in November 2008, the Latvian government took the decision to nationalize the bank. By the 3rd quarter of 2008, GDP quarter-on-quarter contraction exceeded 6%. The budget revenues lagged behind the expenditures, resulting in a gradually growing budget deficit, which reached about 5.5% of GDP in the 3rd quarter of 2008 (see Figure 1).

Figure 1: Year-on-year growth of general government budget total revenues, tax revenues and expenditures, %; seasonally adjusted budget balance, % of GDP

Source: Eurostat, authors’ calculations

In circumstances where the fiscal position was quickly deteriorating but world financial markets were frozen, the Latvian government was forced to seek financial assistance from international lenders. After tough negotiations in November and December 2008, Latvia received a 7.5 billion euro (about 1/3 of GDP) bailout facility from the IMF, the European Commission, the World Bank and the Nordic countries. Latvia received the funding in a series of tranches, with the transfer of each tranche being subject to implementation of a strict reform package agreed with the lenders.Given that introduction of the euro in 2014 remained the Latvian government’s target, one of the key elements of the reform programme was maintaining the lat’s peg to the euro. Therefore, the Latvian government had to accept especially strict and wide-ranging budget consolidation measures.

Budget Consolidation

The total size of budget consolidation achieved in 2008-2011 was impressive: overall, the fiscal impact of the reforms is estimated at 16.6% of GDP (Ministry of Finance of Latvia, 2011). Under the pressure of international lenders, budget consolidation was front-loaded and was achieved astonishingly fast – the fiscal impact of the reforms implemented in 2009 reached almost 10% of GDP, whereas the impact of 2010 and 2011 year measures was much smaller – 4.1% and 2.6%, respectively (see Figure 2).

Figure 2: Size of the implemented consolidation measures and budget deficit outturn, % of GDP*

* Budget deficit in 2011 is the Bank of Latvia’s autumn forecast
Source: Ministry of Finance, Bank of Latvia, Eurostat

Yet the way the consolidation was done was rather chaotic. The 2009 consolidation was mainly implemented by expenditure cuts, including strong wage and employment reductions in the public sector (public pay and employment cuts were continued in the following years, wages were cut by 15-20% in each round and most bonuses were abolished). On the revenue side, the government stuck to the goal of shifting tax burden from labour to consumption, thus the consolidation was mainly achieved by raising indirect taxes, while the personal income tax was reduced. Another line followed by the government at the time was to strengthen support to those affected by the crisis, for example, the duration of unemployment benefits was increased.

Nevertheless, by the time preparation of the 2010 budget started, it became clear that in circumstances of continuing GDP fall and peaking unemployment (in 2009, GDP fell by 17.7%, and the rate of unemployment reached 17.1%), the reduction in labour taxes could not be sustained while the social budget could not bear the burden of growing expenditures. Consequently, the reduction in the personal income tax was reversed (the tax rate was raised even above the pre-crisis level). To consolidate the social budget, the government implemented an across the board cut by introducing ceilings on the size of many benefits. In 2011, the tax burden on labour was further increased by raising the rate of mandatory social security contributions.

Budget consolidation was done under the pressure of the crisis and the reform package was designed in a great rush. What also may not be disregarded, is that the three years – 2009, 2010 and 2011 – were election years in Latvia: in 2009, there were local government elections, in 2010 – parliamentary elections and in 2011 – parliamentary re-elections . Elections have arguably affected the composition of implemented austerity measures. Thus, in June 2009, just ten days after local government elections, amendments to the Law on State Pensions were passed, which stipulated that old-age pensions should be cut by 10%, but pensions to working pensioners should be cut by 70%. This decision caused a strongly negative public reaction and on December 21, 2009, the Constitutional Court ruled that the government’s decision was unconstitutional arguing that the state must guarantee peoples’ right to social security. In the following budget consolidation rounds, even in the face of convoluted IMF recommendations to find a constitutional way of ensuring sustainability of the pension system (IMF, 2010), the government remained strictly opposing any pension cuts.

The mix of implemented reforms is crucial not only because it determines the effectiveness with which the budget consolidation is achieved. What is equally important is that the mix of reforms affects the distribution of costs of the crisis and shapes the economic recovery path. The consequences of the crisis – the dramatic rise in unemployment and wage reductions in the private sector – had a strong impact on incomes, yet policy makers can do little to directly affect this process. On the other hand, policy makers can offset or aggravate those effects by implementing reforms, such as those that made up the austerity packages. In this brief, we assess the distributional impact of selected austerity measures, which were implemented in 2009 – 2011.

Modelling Approach and Limitations

We use the Latvian part of the tax-benefit microsimulation model EUROMOD and follow a similar approach as that taken by Callan et al (2011). We limit our analysis to reforms in direct taxes, social contributions, and cash benefits . In particular, the following austerity measures are included in the analysis:

  • removal of income ceiling for obligatory social insurance contributions (in 2009);
  • increase in the rate of social insurance contributions for employees, employers, and self-employed (June 30, 2011);
  • reduction of tax exemptions (July 1, 2009);
  • increase in the rate of personal income tax (2010);
  • introduction of benefit ceiling for unemployment benefits (2010), maternity, paternity, and parental benefit (November 3, 2010);
  • cuts in state family benefit (2010);
  • cuts in child birth benefit (2010);
  • reduction in the amount of parental benefit by limiting eligibility to non-working parents only (May 3, 2010);
  • making stricter income assessment criteria for guaranteed minimum income (GMI) and reducing amount of the GMI benefit for some groups (2010).

We assess the distributional impact of these austerity measures by comparing two alternative scenarios:

  1. the baseline scenario – simulation of 2011 tax-benefit policy system (with austerity measures implemented), and
  2. the counter factual scenario – simulation of tax-benefit policy system that would have emerged in 2011 in the absence of austerity measures.

If a policy was changed as a part of the austerity package (e.g. income tax increase), we implement a pre-austerity policy (e.g., reduce the income tax to its pre-austerity level). However, if the changes in the policies were regular (e.g. an increase in minimum wage that was planned long before the discussion of austerity measures had started) or not related to austerity measures (e.g. increase in duration of unemployment benefit) we include them in the counterfactual scenario, as well as in the austerity package scenario. By defining the counterfactual scenario in this manner we focus on the impact of austerity measures only holding other things equal.

Despite Latvia is one of the countries where the size of the austerity package was especially large, the distributional effect of the implemented measures has not been analysed neither before nor after the policies had been implemented. Until recently Latvia didn’t have a national microsimulation model which could be used to assess the impact of taxes and benefits on household income. This paper is the first attempt to do this.

However, our analysis is subject to some drawbacks. First, EUROMOD’s input data is based on the European Union Statistics on Income and Living Conditions 2008 (with the income data referring to 2007). We adjust 2007 incomes up to 2011 using updating factors based on the aggregate evolution of such incomes according to national statistics. However, we do not adjust for the changes in the labour market that happened during this period. Therefore, we estimate the effect of austerity measures on data that represent the population with pre-crisis labour market characteristics (e.g. relatively low number of unemployed people).

Second, the analysis is limited to the direct impact of the implemented measures, disregarding the secondary effects such as e.g. behavioural responses of people on the implemented policies.

Results

The simulation results suggest that the impact of the analysed austerity measures was progressive with top income groups being the most affected (see Figure 3). The six countries considered in Callan et al (2011) show different degrees of progressivity: Greece demonstrated a clearly progressive impact, while Portugal was the only country where the effect was regressive. The result for Latvia is likely to be a consequence of introduced ceilings on contributory benefits, as well as the increases in income tax and social insurance contributions. While income tax in Latvia is flat (except for a relatively small untaxed personal allowance), the lowest income deciles contain proportionately more unemployed people and pensioners.

Figure 3: Percentage change in household disposable income due to austerity measures by income deciles

Source: based on own calculation using EUROMOD

Higher progressiveness was observed for households with children (see Figure 4), which is explained by the introduction of ceilings on child-related contributory benefits. At the same time, the impact on the households with elderly was more even.

Figure 4: Percentage change in household disposable income due to austerity measures for different types of households by income quintiles



Source: based on own calculation using EUROMOD

While the introduction of austerity measures made all income groups poorer, progressivity of the impact reduced income inequality. The Gini coefficient of the counter factual scenario is 1 percentage point higher than that of the base scenario. After implementation of the austerity measures, the poverty line decreases because the median income decreases. As a result, poverty rates using relative poverty lines decreased. The poverty rate of the elderly was affected the most, because pension income was not cut and pensioners became relatively better off as compared to other population groups. However, if measured against the fixed poverty threshold, the poverty rate increased in all population groups (see Table 1).

Table 1: Poverty rates and Gini coefficient before and after implemented austerity measures

Source: based on own calculation using EUROMOD

Concluding Remarks

The austerity measures analysed in this paper have had a progressive impact, with the richest population groups likely to be bearing most of the costs. This result should be interpreted with caution. It should be taken into account that we do not model all of the austerity measures that were implemented in 2009-2011. E.g., we do not model the impact of changes in VAT rates, which is likely to have been quite strong and regressive.

Latvia is a society with extremely high income inequality. For example, the income quintile share ratio calculated by the Eurostat (S80/S20), which measures income inequality, in 2009 was the second highest in the EU (6.9 as compared with an EU average of 4.9). It is unlikely that the progressive impact identified in this paper will significantly reduce income inequality gap in Latvia relative to other European countries.

References

  • Arco Real Estate (2008). Real estate market overview (Sērijveida dzīvokļi, 2008. gada decembris)
  • Callan, Tim, Chrysa Leventi, Horacio Levy, Manos Matsaganis, Alari Paulus & Holly Sutherland (2011). “The distributional effects of austerity measures : a comparison of six EU countries”, Social situation observatory, Research note 2/2011.
  • International Monetary Fund (2010). Republic of Latvia: Second Review and Financing Assurances Review Under the Stand-By Arrangement, Request for Extension of the Arrangement and Rephasing of Purchases Under the Arrangement and Request for Waiver of Nonobservance and Applicability of Performance Criteria. IMF Country report No. 10/65, March 2010.
  • Ministry of Finance of Latvia (2011). Budget consolidation in 2008-2011 (Veiktā budžeta konsolidācija laika posmā no 2008.-2011. gadam)

Baltic Shadow Economies

Policy Brief Image of Two Shadows from Walking Men Representing Shadow Economies

This policy brief summarises the results and implications of a recent study of the size and determinants of the shadow economies in Estonia, Latvia, and Lithuania. The results suggest that the shadow economy in Latvia in 2010 is considerably larger than in neighboring Estonia and Lithuania. While the shadow economy as a percentage of GDP in Estonia contracted from 2009 to 2010, it expanded in Latvia and Lithuania. An important driver of shadow activity in the Baltic countries is the entrepreneurs’ dissatisfaction and distrust in the government and the tax system. Involvement in the shadow economy is more pervasive among younger firms and firms in the construction sector. These findings have a number of policy implications, which are discussed at the end of this brief.

Background and Aims

Anecdotal evidence suggests that the shadow economies in the Baltic countries and other emerging Central and Eastern European countries are substantial in size relative to GDP. This is an important issue for these countries because informal production has a number of negative consequences.

First, countries can spiral into a ‘bad equilibrium’: individuals go underground to escape taxes and social welfare contributions, eroding the tax and social security bases, causing increases in tax rates and/or budget deficits, pushing more production underground and ultimately weakening the economic and social basis for collective arrangements. Second, tax evasion can also hamper economic growth by diverting resources from productive uses (producing useful goods and services) to unproductive ones (mechanisms and schemes to conceal income, monitoring of tax compliance, issuance and collection of penalties for non-compliance). Third, informal production can constrain entrepreneurs’ ability to obtain debt or equity financing for productive investment because potential creditors/investors cannot verify the true (concealed) cash flows of the entrepreneur. This can further impede growth. Finally, shadow activities distort official statistics such as GDP, which are important signals to policy makers.

The aim of our study is to measure the size of the shadow economies in Estonia, Latvia, and Lithuania, and to analyse the factors that influence participation in the shadow sector. We use the term ‘shadow economy’ to refer to all legal production of goods and services that is deliberately concealed from public authorities. The study also makes a methodological contribution by developing an index of the size of the shadow economies as a percentage of GDP. It is foreseen that the index will be published regularly.

Although an index invites comparisons, and maybe even ‘competitions’ between countries, the purpose here is not to create a ‘Baltic championship’ on shadow economies. The index should primarily be seen as a tool to promote discussion on the size and role of the shadow economy and to provide a metric which can be used to measure the degree of success in fighting the shadow economy.

Method of Measuring the Shadow Economies

Estimates the size of the shadow economies are derived from surveys of a stratified random sample of entrepreneurs in the three countries (591 in Latvia, 536 in Lithuania and 500 in Estonia). The rationale for this approach is that those most likely to know how much production or income goes unreported, are the entrepreneurs who themselves engage in the misreporting and shadow production.

Survey-based approaches face the risk of underestimating the total size of the shadow economy due to non-response and untruthful response given the sensitive nature of the topic. We minimise this risk by employing a number of surveying and data collection techniques shown in previous studies to be effective in eliciting more truthful responses (e.g., Gerxhani, 2007; Kazemier and van Eck, 1992; Hanousek and Palda, 2004).

These approaches include framing the survey as a study of satisfaction with government policy, gradually introducing the most sensitive questions after less sensitive questions, phrasing misreporting questions indirectly, e.g., asking entrepreneurs about the shadow activity among ‘firms in their industry’ rather than ‘their firm’, and, in the analysis, controlling for factors that correlate with potential untruthful response, such as tolerance towards misreporting. We aggregate entrepreneurs’ responses about misreported business income, unregistered or hidden employees, as well as unreported ‘envelope’ wages to obtain estimates of the shadow economies as a proportion of GDP.

There are three common methods of measuring GDP: the output, expenditure and income approaches. Our index is based on the income approach, which calculates GDP as the sum of gross remuneration of employees (gross personal income) and gross operating income of firms (gross corporate income). Computation of the index proceeds in three steps: (i) estimate the extent of underreporting of employee remuneration and underreporting of firms’ operating income using the survey responses; (ii) estimate each firm’s shadow production proportion as a weighted average of the two underreporting estimates with the weights reflecting the proportions of employee remuneration and firms’ operating income in the composition of GDP; and (iii) calculate a production-weighted average of shadow production across firms. Taking weighted averages of the underreporting measures rather than a simple average is important for the shadow economy index to reflect a proportion of GDP.

Size of the Shadow Economies

Table 1 indicates that the shadow economy as a proportion of GDP is considerably larger in Latvia (38.1%) compared to Estonia (19.4%) and Lithuania (18.8%) in 2010. Only Estonia has managed to marginally decrease the proportional size of its shadow economy from 2009 to 2010 – a statistically significant decrease of 0.8 percentage points. In contrast, the proportional size of the shadow economies in Lithuania and Latvia has increased by an estimated 0.8 and 1.5 percentage points, respectively.

Table 1. Shadow economy index for the Baltic countries

 

Note: This table reports point estimates and 95% confidence intervals for the size of the shadow economies as a proportion of GDP. The third column reports the change in the relative size of the shadow economies from 2009 to 2010.

Form of Shadow Activity

Figure 1 illustrates the average levels of underreporting (business profits, number of employees and salaries) in each of the countries in 2009 and 2010. The average levels of underreporting in all three areas are in the order of two to three times higher in Latvia compared to Lithuania and Estonia. In Latvia and Lithuania, the degree of underreporting of business profits and salaries (‘envelope’ wages) is approximately twice as large as the underreporting of employees. The exception to this trend is the relatively low amount of underreported business profits in Estonia, likely to be a result of low corporate tax rates. Bribery in Latvia and Lithuania constitutes a similar fraction of firms’ revenue, approximately 10%, whereas in Estonia bribery is less pervasive and constitutes around 6% of firms’ revenue.

Figure 1. Simple averages of underreporting and bribery among Estonian (EE), Lithuanian (LT) and Latvian (LV) firms in 2009 and 2010.

 

Determinants of Involvement in the Shadow Economy

The literature on tax evasion identifies two main groups of factors that affect the decision to evade taxes and thus participate in the shadow economy. The first set emerges from rational choice models of the decision to evade taxes. In such models individuals or firms weigh up the benefits of evasion in the form of tax savings against the probability of being caught and the penalties that they expect to receive if caught. Therefore the decision to underreport income and participate in the shadow economy is affected by the detection rates, the size and type of penalties, firms’ attitudes towards risk-taking and so on. These factors are likely to differ across countries, regions, sectors of the economy, size and age of firm, and entrepreneurial orientation (innovativeness, risk-taking tendencies, and pro-activeness).

Empirical studies find that the actual amount of tax evasion is considerably lower than predicted by rational choice models based on pure economic self-interest. The difference is often attributed to the second, broader, set of tax evasion determinants – attitudes and social norms. These factors include perceived justice of the tax system, i.e., attitudes about whether the tax burden and administration of the tax system are fair. They also include attitudes about how appropriately taxes are spent and how much firms trust the government. Finally, tax evasion is also influenced by social norms such as ethical values and moral convictions, as well as fear of feelings of guilt and social stigmatisation if caught.

Our study uses regression analysis to identify the factors that are statistically related to firms’ involvement in the shadow economy. The results indicate that the size of the shadow economy is smaller in Estonia and Lithuania relative to Latvia, after controlling for a range of factors.

Tolerance towards tax evasion is positively associated with the firm’s stated level of income/wage underreporting. Satisfaction with the tax system and the government is negatively associated with the firm’s involvement in the shadow economy, i.e. dissatisfied firms engage in more shadow activity, satisfied firms engage in less.

This result is consistent with previous research on tax evasion, and offers an explanation of why the size of the shadow economy is larger in Latvia than in Estonia and Lithuania; namely that Latvian firms engage in more shadow activity because they are more dissatisfied with the tax system and the government as illustrated in Figure 2. Analysing each of the four measures of satisfaction separately we find that shadow activity is most strongly related to dissatisfaction with business legislation, followed by the State Revenue Service, the government’s tax policy, and finally the government’s support for entrepreneurs.

Figure 2. Average satisfaction of firms with the tax system and government in 2010.

Note: These questions use a 5-point scale: 1=“very unsatisfied”; 2=“unsatisfied”; 3=“neither satisfied nor unsatisfied”; 4=“satisfied”; and 5=“very satisfied”. SRS is State Revenue Service.

Another strong determinant of involvement in the shadow economy is firm age, with younger firms engaging in more shadow activity than older firms. This effect dominates relations between firm size and shadow activity. A possible explanation for the relation is that young firms entering a market made up of established competitors use tax evasion as a means of being competitive in their early stages. The regression results also provide some evidence that after controlling for other factors, firms in the construction sector and firms that have a pro-active entrepreneurial orientation tend to engage in more shadow activity.

Policy Implications

First, the relatively large size of the shadow economies in the Baltic countries, and their different expansion/contraction trends, cause significant error in official estimates of GDP and its rates of change, because although statistics bureaus in each of the countries attempt to include some of the shadow production in GDP estimates they do not capture the full extent. Not only is GDP used in key policy ratios such as government deficit to GDP, debt to GDP, but also the rate of change is used as a key indicator of economic performance and therefore guides policy decisions. When the shadow economy is expanding (as in Latvia and Lithuania) official GDP growth rates underestimate true economic growth and when the shadow economy is contracting (as in Estonia) official GDP growth rates overstate true economic growth. At a minimum, policy makers need to be aware of these biases in official statistics, but ideally, statistical bureaus would implement more rigorous methods to estimate and incorporate shadow production in official statistics.

Second, our results suggest that to reduce the size of the shadow economies in the Baltic countries by encouraging voluntary compliance, a key factor that needs to be addressed is the high level of dissatisfaction with the tax system and with the government. Addressing this issue could involve actions such as making tax policy more stable (less frequent changes in procedures and tax rates), and increasing the transparency with which taxes are spent.

Finally, our estimates of the size of the shadow economies suggest that there is significant scope for all three governments to increase their revenues by bringing production ‘out of the shadows’. Investment in programs aimed at reducing the size of the shadow economies could be rather profitable for the Baltic governments, because even a small influence on entrepreneurial behaviour could result in significant revenue increases.

References

  • Gerxhani, K. (2007) “‘Did you pay your taxes?’ How (not) to conduct tax evasion surveys in transition countries”, Social Indicators Research 80, pp. 555-581.
  • Hanousek, J., and F. Palda (2004) “Quality of government services and the civic duty to pay taxes in the Czech and Slovak Republics, and other transition countries”, Kyklos 57(2), pp.237-252.
  • Kazemier, B., and R. van Eck (1992) “Survey investigations of the hidden economy”, Journal of Economic Psychology 13, pp. 569-587.

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