SOCIAL DISCOUNT RATES AND WELFARE WEIGHTS FOR PUBLIC INVESTMENT DECISIONS UNDER BUDGETARY RESTRICTIONS THE CASE OF CYPRUS

Transcription

1 SOCIAL DISCOUNT RATES AND WELFARE WEIGHTS FOR PUBLIC INVESTMENT DECISIONS UNDER BUDGETARY RESTRICTIONS THE CASE OF CYPRUS DAVID EVANS ERHUN KULA Working Paper n SETTEMBRE 2009 JEAN MONNET CHAIR Economics of European Integration DIPARTIMENTO DI SCIENZE ECONOMICHE AZIENDALI E STATISTICHE Via Conservatorio Milano tel (21522) - fax (21505) E Mail: dipeco@unimi.it VIII Milan European Economic Workshop, June 11 th - 12 th 2009 Università degli Studi di Milano EIBURS project, European Investment Bank

2 1 Social discount rates and welfare weights for public investment decisions under budgetary restrictions the case of Cyprus Authors: Dr David Evans and Dr Erhun Kula Affiliation and address: Dr D. Evans, Business School, Oxford Brookes University, Oxford, UK Dr E. Kula, Faculty of Business Administration, Bahcesehir University, Istanbul, Turkey Abstract: This paper focuses on the estimation of key welfare parameters for incorporation into social cost-benefit analysis with special reference to Cyprus and its unique regional problems. In particular, the theory and application of social discount rates and regional welfare weights are considered from the perspective of the European Commission as both supra-national planner and provider of major funding for investment in the EU-12 area. The aim is to provide answers to three main questions. Firstly, should different discount rates be applied in the appraisal of projects impacting on the Turkish and Greek regions of the island? Second, if different discount rates apply, then what approach should be taken in the discounting of costs and benefits for projects impacting on the entire island? Finally, what is the best method to estimate regional welfare weights for Cyprus and how should these weights be applied in social cost-benefit analysis in order to take proper account of the considerably lower average standard of living in North Cyprus. This particular case-study serves to highlight a practical procedure, with suitable theoretical underpinnings, for the calculation and incorporation of regional welfare weights in social CBA more generally and especially with regard to Europe. Keywords: Cost-benefit analysis, social discount rates, regional welfare weights, Cyprus. JEL codes: D60, D61, H24, R13. Acknowledgements: Paper presented at the VIII Milan European Economy Workshop, June 11 th and 12 th, 2009, University of Milan, in the framework of the EIBURS project, sponsored by the European Investment Bank. The authors are grateful to Professor Massimo Florio and Professor Per-Olov Johansson for their comments on an earlier draft of this paper. The usual disclaimer applies.

3 2 Introduction Cyprus is a unique new member state of the EU in the sense that it is divided. Although the EU sees Cyprus as one, the Island has two different economies, monies, tax structures, judicial powers and security arrangements. This situation raises challenges for economists, as well as policy makers, who are interested in estimating national parameters for public spending under budgetary restrictions. Table 1 provides recent data highlighting the essential differences between the two main regions of the island with respect to population, size of economy, and average living standards. The Table shows that North Cyprus, the Turkish part of the island, has a population of about 260,000, while South Cyprus, the Greek region, has a population of around 780,000. On average, living standards in the South are almost 80% higher than in the North, so the Turkish region is decidedly poorer. This large difference in living standards, together with the Greek/Turkish regional divide, means that Cyprus serves as a good case study for illustrating how best to take explicit account of both regional efficiency and equity issues in CBA with particular regard to social investment in the European Union. Table 1 GDP AND POPULATION DATA FOR N. AND S. CYPRUS, NORTH CYPRUS SOUTH CYPRUS POPULATION 257, ,700 GDP INDEX PER CAPITA GDP ECONOMIC GROWTH 6.1% 2.4% Data source: N. Cyprus- Main Economic and Social Indicators, , Office of National Planning, Nicosia S. Cyprus- Republic of Cyprus Statistical Service, 2008 Notes: a) Real GDP and Per Capita Real GDP indices are expressed in Purchasing Power Standards (PPS): S. Cyprus = b) Economic growth for 2006 is expressed on a per capita GDP basis. Project donor agencies such as the European Commission, World Bank and European Investment Bank would want to make sure that the money allocated to the Island is well used in infrastructure and other projects. The selection of these projects is highly sensitive to cost-benefit parameters such as shadow prices, social discount rates and a set

4 3 of distributional welfare weights. For whole island projects, national parameters encompassing the two sections of the community are needed to ensure that investment projects are value for money. While no published guidance on CBA is issued by the governments of North and South Cyprus, the European Commission issues guidelines on the appraisal of projects for all member states. These guidelines are updated periodically and made available to practitioners of cost-benefit analysis. The latest EC Guide highlights the importance of both the social discount rate and distributional welfare weights in applied CBA (see European Commission (2008), especially the technical annexes). To what extent a member country should comply with these guidelines is debated in the European Union but all agree that project selection must be based upon sound and consistent cost-benefit methods. It is desirable for Cyprus, as well as other new EU member countries, to adopt practices and policies which ensure that proposed projects are viable, especially when they are seeking external funds. So far, no research has been done to estimate cost-benefit parameters covering both sections of the community in the Island of Cyprus. This project aims to estimate appropriate social rate(s) of discount and regional welfare weights for the whole of Cyprus and to consider how best to explicitly incorporate these efficiency and equity criteria into the appraisal of social projects with a particular view to informing CBA practice more generally for the European Union. Research Questions There are 3 main questions to be addressed in this paper: (a) Should different social discount rates be applied in the CBA of projects impacting on North and South Cyprus, respectively? (b) If different discount rates are relevant for the two broad regions of the island, then what approach should be taken in the discounting of costs and benefits for projects impacting on Cyprus as a whole and how should it be put into practice? (c) What is the best method to estimate welfare weights for the Greek and Turkish regions of Cyprus and how should these weights be applied in CBA? These research questions are concerned firstly with the estimation of appropriate social discount rate(s) for Cyprus to be applied in social cost-benefit analysis and secondly with the measurement of distributional welfare weights, especially in a regional context. Also,

5 4 there is the question of how best to combine these efficiency and equity criteria in order to produce explicit measures of inter-temporal equity-adjusted regional discount factors for direct incorporation in CBA. Of course, this work relating to the measurement of key social welfare parameters for Cyprus can help provide relevant CBA guidance for all member countries of the European Union. Social discount rate 1 Theoretical approaches to measurement Much of the funding of investment for EU member countries out of the EC Structural Funds Budget for is directed towards long-term infrastructure projects with investment horizons of 30 years or less. As such, the theoretical context for social discounting involves only ordinary long-term investment horizons rather than the distant future. While investment for the very long-term may require a time-declining discount rate based on either uncertainty in the discount rate itself (Weitzman, 1998 and 2001) or uncertainty in the future rate of economic growth (Gollier, 2002), discounting for periods up to 30 years involves only the application of a constant discount rate. For example, the British Treasury recommends the application of a constant social discount rate of 3.5% for project horizons of up to 30 years, and thus normal exponential discounting practice applies, but a declining step rate for very long-term projects and therefore hyperbolic discounting for these (see HM Treasury, 2003). There are many different possible approaches to the measurement of discount rates for application in social cost-benefit analysis for ordinary long-term projects with investment horizons of up to 30 years; for example, the social opportunity cost of capital, market rates of interest based on the Efficient Market Hypothesis and the social time preference rate (STPR). Historically, there has been a great deal of debate about the appropriateness of these different measures and Spackman (2004 and 2007) discusses the key issues in depth. Many economists, including Spackman (ibid) and Pearce and Ulph (1999), believe that the STPR is the best measure of the social discount rate from a theoretical perspective. This faith in the STPR is now reflected in the guidance on social CBA issued by several national governments (e.g. Britain and France) and most crucially in the latest CBA Guidance for EU member states issued by the European Commission (2008).

6 5 The theoretical derivation of the STPR is based on the work of Ramsey (1928) and involves the inter-temporal optimisation of social utility with respect to consumption. The details of its formal derivation can be found, for example, in Feldstein (1964). An iso-elastic social preference function (see equation (8) below) is commonly assumed to apply over a broad range of income which means that one of the key component parameters of the STPR, the elasticity of marginal social utility of income (e), remains constant when income (consumption) changes. Given this iso-elasticity assumption, then the formula for the STPR can be expressed as follows: (1 + STPR) = (1 + p)(1+g) e (1) So, Ln(1 + STPR) = Ln(1 + p) + e Ln(1 + g) (2) Finally, a good linear approximation to equation (2) is, STPR = p + eg (3) Where p = utility discount rate; e = elasticity of marginal social utility of consumption (income) with respect to consumption (income); g = projected average annual rate of growth in real per capita consumption (income). The parameter p can be split into 2 separate components, the pure time preference rate (d) and life chances (l); see Pearce and Ulph (1999). The former component reflects impatience and myopia, while the latter takes mortality into account. In fact, a decent proxy for l is a country s recent crude annual death-rate. Catastrophic risk, as opposed to life chances, constitutes this latter element in some treatments of the utility discount rate (see, for example, HM Treasury (2003) and Stern (2006)) although it is clear that the British Treasury has in fact based its figure for catastrophe risk of 1% per annum on the estimate of l provided by both Pearce and Ulph (1999) and OXERA (2002).

7 6 There are a number of alternative approaches to estimating e. The most common of these are: A) Derivation of e from estimates of income and compensated price elasticities of demand for preference independent goods (e.g. food). The essential theory is covered in Fisher (1927), Frisch (1959) and Fellner (1967). The formula for e is as follows: e = y(1- wy)/p (4) Where y = income elasticity of demand; p = compensated own-price elasticity of demand; w = budget share of the preference independent product group. B) Derivation of e from lifetime consumption behaviour with e measured as the reciprocal of the inter-temporal elasticity of substitution in consumption. The underlying theory is covered in Blundell et al (1994) and more concise treatments can be found in Cowell and Gardiner (1999) and Pearce and Ulph (1999). The formula for e is as follows: e = -1/[dLnC t /dln(1 + r t )] (5) Where C = consumption; r = rate of interest. C) Revealed social values approach based on government policy measures e.g. taxation. The relevant theory is covered in Stern (1977) and Cowell and Gardiner (1999). This approach suggests that an implied e measure may be inferred from a government s aversion to income inequality as expressed, for example, through the structure of income tax rates. If it is reasonable to assume that the government s social valuation of income is based on the principle of equal absolute sacrifice of satisfaction, then a mildly progressive tax structure would indicate an e value of just above unity. The formula for e based on income tax rates, assuming both an iso-elastic preference function and equal absolute sacrifice of satisfaction, is as follows: e = Log(1-t(Y))/Log(1 (T(Y)/Y)) (6) where t = marginal rate of income tax; T = total tax liability; Y = taxable income.

8 7 Each of these 3 approaches has its strengths and weaknesses but using at least 2 of them does permit a cross-check on e estimates at the empirical stage. For critical reviews of these various approaches to the determination of e, see Evans (2005 and 2008) and Creedy and Guest (2008). For Cyprus, we intend to use approaches A and C to estimate this component of the STPR. There are considerable empirical difficulties with the lifetime consumption approach, especially since the de-regulation of financial markets which has resulted in a falling differential between retail borrowing and saving rates and a much greater variety of loan and savings products with different terms and conditions attached. In relation to the average annual growth of per capita consumption (g), estimates can be based on long-term projections from macro-economic growth models. However, in the case of Cyprus such projections, covering sufficiently lengthy future periods of at least 20 years, are not available. For developed countries some indication may be given by considering historical growth performance over several business cycles. However, past growth rates offer no guidance for the new EU member states, especially given their higher required future growth rates in the interests of economic convergence. In considering target economic growth rates for Cyprus then measures of living standards in recent years, relative to the EU-15, based on per capita real GDP expressed in Purchasing Power Standards, need to be taken into account. The average standard of living in the Republic of Cyprus is much higher than in the Turkish region in the North and therefore the latter s growth requirements are considerably higher. Indeed, different growth requirements are likely to be the most convincing reason for applying different social discount rates in the CBA of projects impacting on the two broad regions of the island. 2) Empirical findings for other countries Assumptions made about the utility discount rate (p), especially whether or not to include the pure time preference component (d), and the methods used to estimate the elasticity of marginal social utility of consumption (e), have had some influence on empirical measures of the social time preference rate for different countries. In relation to e there is evidence to suggest that estimates are, to some extent, method dependent. See, for example, Evans (2005 and 2008).

9 8 Kula (1984) estimated STPR values of 5.3% and 5.2%, respectively, for the United States and Canada, and in a later study Kula (2004) estimated a value of 5.3% for India. Evans and Sezer (2002) obtained an STPR estimate of just over 4% for the UK, while Percoco (2008) estimated a value of 3.8% for Italy. Each of these studies used the approach based on the demand for preference independent goods (see theory section) to estimate e. Percoco (ibid) also obtained the same estimate for e using the tax-based method (see theory section). In a wide-ranging study covering member countries of the European Union, Evans and Sezer (2005), using average death rates to measure countries utility discount rates and a tax-based method to estimate e values, obtained STPR results ranging between 2.3% for Denmark and 5.6% for Ireland. For most of the EU-15 countries, the discount rates were in the 3-5% band. Variation in growth rates was the most important contributory factor explaining these differences in EU member countries social discount rates. In another study by Evans and Sezer (2004), using the same approach, estimates of STPRs for major non-european countries, USA, Japan and Australia, were all in the 4-5% band. For new EU member states, and thus Cyprus, the latest European CBA Guidance (see European Commission, 2008) suggests the relevance of an STPR of 5.5% which, due to the higher growth requirements of the new member countries in the interests of longterm economic convergence, is two percentage points higher than the STPR deemed appropriate for the EU-15. These suggested rates are based on the work of Florio (2006) with the 3.5% rate for the EU-15 being approximately equal to the average of the individually estimated rates for each of the EU-15 countries by Evans and Sezer (2005). Of course, EC Guidance on CBA recognises that local variations in the STPR may be appropriate, hence the need for estimating suitable rates for North and South Cyprus. Welfare weights 1) Theory Distribution issues have always been important in cost-benefit analysis. To what extent should governments and donor agencies give priority to projects that are benefiting the relatively poor? Welfare weights could become a useful tool to find some answers to this question. If distribution issues are to be explicitly addressed in project selection then the use of welfare weights in cost-benefit analysis would be beneficial. We intend to calculate

10 9 regional welfare weights for both Greek and Turkish parts of the Island; weights that can be applied in CBA to take direct account of important distributional impacts. The theoretical derivation of welfare weights is commonly based on the properties of the Bergson-Samuelson social welfare function (BS), suitably adapted for use in a regional context. This function aggregates the utilities of individuals or average representatives of clearly defined socio-economic groups with the utility functions exhibiting both positive and declining marginal utility of income. It is the latter that is of direct concern in this paper, where the groups are different regions (other possible groupings may reflect ethnicity, age, gender and religion). In a regional context, the BS can be expressed as follows: SW =n A U A (Y A ) +n B U B (Y B ) + n J U J (Y J ) (7) Where U = Utility of average regional representative (subscripts A-J represent different regions); Y = Representative average income for the region; n = Number of individuals or adult equivalents in each region (A-J). Despite its limitations and weaknesses, see Cowell and Gardiner (1999), the BS is commonly applied in the construction of welfare weights to address equity issues in social project appraisal: see, for example, Weisbrod (1972), Squire and Van der Tak (1975), Dreze and Stern (1987 and 1990), Kula (2002 and 2007), Evans et al (2005) and Sezer (2006 and 2007). Also, the possible application of social welfare weights to take account of distributional impacts is discussed in the CBA guidance provided by both the British government and the European Commission (HM Treasury, 2003, and European Commission, 2008). The underlying utility functions (U i ), or social valuation functions from the Social Planner s perspective, are generally assumed to be iso-elastic and there is some empirical evidence to support the assumption in the case of developed countries; see, for example, Blue and Tweeten (1997) and Evans (2005).The representative iso-elastic social utility, or social valuation, function for each region is as follows: U i (Y i ) = (Y i 1-e 1)/1-e) (8)

11 10 Where Y i = representative average income for region i; e = elasticity of marginal social utility of income (expressed as a positive number). The theory regarding the estimation of e has already been discussed (see theory on the social discount rate). The appropriate regional income levels may simply be based on per capita regional income, suitably adjusted for any regional differences in the cost of living. For the application of regional welfare weights to North and South Cyprus, indices of per capita real GDP expressed in Purchasing Power Standards (PPS) can be used. While data limitations may force the issue regarding the use of per capita income measures, the use of equivalised income, based on the OECD-modified equivalence scale, would be preferable; see Haagenars et al (1994). Another refinement in the income measure would be to take inter-regional differences in income inequality into account. This could, in principle, be achieved by using measures of Equally-Distributed Equivalent Income (EDEI); see Kolm (1969) and Atkinson (1983). The formula for EDEI is as follows: EDEI = ( p j Y j (1-e) ) 1/(1-e) (9) Where p j = proportion of group members in equivalised income class Y j In equation (9) the parameter e is interpreted as a measure of the government s or supranational authority s aversion to income inequality. The higher the value of e then the greater the degree of aversion to income inequality, meaning that for any given measure of relative income dispersion and average level of income, EDEI could be much lower than mean income. So, EDEI measures take account of inter-regional differences in the relative dispersion of income as well as inter-regional differences in mean income levels. For example, if two regions have similar levels of per capita income but one has a greater degree of inequality with respect to household income (after adjusting for differences in household size and composition), then the EDEI for this region will be lower by an amount that reflects both the higher income dispersion and the extent of aversion to income inequality. Inspection of equation (9) reveals that if there were no aversion to income inequality, then e would be zero and EDEI would simply equal mean income. However, a positive and non-trivial value for e is to be expected in practice.

12 11 In the case of a unitary value for e, then inspection of equation (9) reveals that it breaks down; each of the income terms within the brackets is reduced to unity and the exponent outside the brackets becomes infinitely large. This fact necessitates a switch to the following logarithmic function which should be applied only when e =1: Log EDEI = p j Log Y j (10) For values of e that are fractionally below or above unity in equation (9), then the resulting EDEI figures will very closely approximate the EDEI value obtained from equation (10). Thus, for all practical purposes, switching to equation (10) when e = 1 can be avoided by simply setting e = 0.99, for example, and then using equation (9). The required regional welfare weights can be calculated by taking ratios of marginal social utilities (MU i ) based on the iso-elastic social valuation function given by equation (8). Taking the first derivative of equation (8) yields the required marginal utility expression, MU i = Y -e i. Assuming just 2 regions, A and B, then the welfare weight for region A (W A ) is given by the ratio of the marginal utilities, with respect to income, for the regional representatives: W A = MU A /MU B = (Y A /Y B ) -e = (Y B /Y A ) e (11) If EDEI is specified in equation (8), the representative iso-elastic social utility function, then EDEI A and EDEI B replace Y A and Y B, respectively, in equation (11). Assuming region A is the poorer region then equation (11) would provide a measure of the regional welfare weight to be applied in the case of North Cyprus (A) with South Cyprus (B) as the numeraire. The relevant income measure must be based on data availability and in practice this is likely to be an index of real per capita GDP expressed in PPS, rather than an EDEI measure which requires comprehensive data on intra-regional income dispersion. Apart from the obvious influence of relative regional incomes on the size of the welfare weight, equation (11) reveals that the elasticity of marginal social utility of income (e) also has a key influence. Empirical evidence on e is a crucial factor in the determination of appropriate values of the regional welfare weights to be applied in social CBA.

13 12 2) Empirical findings for other countries Studies focusing on the estimation of distributional welfare weights include the work of Weisbrod (1972), Stern (1977), Evans et al (2005), Kula (2002 and 2007) and Sezer (2006 and 2007). The work of Evans, Kula and Sezer focuses exclusively on regional welfare weights and their possible incorporation into social CBA, and thus merit some brief discussion. All three based their measures of welfare weights on equation (11) but only Sezer (2007), in the case of Turkey, estimated weights based on the EDEI measure. In each of the other studies, weights were based on real per capita GDP measures. Kula (2002) focused on India where there were some big differences in regional incomes and so this factor alone produced large welfare weight values for the poorest regions. The sizes of these weights were further enhanced by a relatively high estimate for e; a value of approximately 1.6 was obtained from estimated income and price elasticities in a demand for food model. Sezer (2006 and 2007) also found very large differences in per capita income between the poorer and richer regions of Turkey. However, his estimate of e, based on a revealed social values approach using income tax rates, is at 1.2 clearly lower than Kula s and this tends to modify the values of the Turkish regional weights relative to those estimated for India. Evans et al (2005) estimated regional welfare weights for the countries comprising the United Kingdom and the relatively modest differences in living standards between the countries means that the estimated weights for the poorest countries, Wales and Northern Ireland, are only of moderate size. However, the relatively high e value of approximately 1.6, estimated from both consumer demand data and income tax rates, does serve to raise the values of these weights somewhat, as can be appreciated from inspection of the formula for the welfare weight calculation given by equation (11). Empirical estimates of social discount rates for Cyprus. Estimates of the component parameters of the STPR (see equation (3)) are required for both regions of the island. The utility discount rate (p)

14 13 Based on the crude death-rates in recent years, presented in Table 2, the life chance element is 0.7% for both North and South Cyprus. If a small additional element covering pure time preference is also taken into account, then an overall estimate of 1% is appropriate for both regions and therefore the whole of the island. According to Pearce and Ulph (1999), opinions expressed by economists concerning the appropriate value for this pure time preference rate range from 0%-0.5%.Taking a central value and adding this to the death-rate yields an overall utility discount rate of approximately 1%. Table 2 PERCENTAGE CRUDE DEATH RATES IN NORTH AND SOUTH CYPRUS: N. CYPRUS 0.83% 0.82% 0.80% 0.70% 0.71% S. CYPRUS 0.73% 0.72% 0.71% 0.71% 0.70% Data source: N. Cyprus- Main Economic and Social Indicators, , Office of National Planning, Nicosia S. Cyprus- Eurostat, 2008 ESTAT-NSI-SUPPORT@ec.europa.eu The growth of real per capita income (g) Table 3 shows very different average annual growth rates for the two regions over the past 10 years; over 6% in the case of North Cyprus and less than 2.5% for South Cyprus. However, this is a comparatively short period of historical data offering a less than reliable guide to future prospects. In particular, it is unlikely that North Cyprus can maintain this very high rate of growth over many future years. Consequently, incorporating a 6% estimate for g in the discount rate for North Cyprus does not seem particularly sensible.

15 14 Table 3 AVERAGE ANNUAL GROWTH RATE OF REAL GDP PER INHABITANT: AVERAGE N. CYPRUS S. CYPRUS EU-15 EU-25 EU-27 GROWTH 6.30% 2.32 % 1.90 % 2.08 % 2.15 % Data source: N. Cyprus- Main Economic and Social Indicators, , Office of National Planning, Nicosia Other Regions- Eurostat, 2008 An alternative approach is to consider the required rates of economic growth for the 2 regions in order to achieve the EU economic convergence objective. Although the extent of convergence and its future time scale are not clearly defined for this EC objective we will assume that the target is to either match or at least get much closer to average living standards in the EU-15 over a future time period that broadly reflects the average investment horizon for projects currently being financed out of the EU Structural Funds budget for This horizon, measured from the middle of this budget period, is approximately 25 years, so working from the latest available 2007 figures for the indices of per capita real GDP in PPS, growth rates need to be projected for 28 years up to We calculate target growth rates that are designed to achieve 90% convergence for North Cyprus and 100% for South Cyprus, relative to the projected GDP index for the EU-15. The lower convergence target for North Cyprus reflects the fact that average living standards are currently much lower than in the South. On average, the established members of the EU have achieved an average annual growth in real per capita GDP of approximately 2% over the period ; see Table 4. Assuming this average rate of growth is maintained over the period then, based on the GDP data in Table 5, an index value of is projected for the EU-15 in Details of the relevant calculation are given in a footnote to Table 5. The 2007 GDP indices are 52.8 for N. Cyprus and 93.4 for S. Cyprus (EU-27 =100).

16 15 Table 4 REAL GDP PER HEAD IN US$ (constant PPS, reference year 2000): EU Growth (2.3%) (2.3%) (2.1%) (2.1%) Data Source: OECD Database 2009 Note: The growth figures, shown in brackets, represent the average annual percentage growth of real GDP per head from 1970 to the date indicated in the Table. For the longest periods, and , the growth figures are very close to 2% per annum. Table 5 GDP PER CAPITA IN PURCHASING POWER STANDARDS (PPS) EU- 27 = 100: N. CYPRUS S. CYPRUS EU-15 EU-25 EU (90%) (100%) Data source: N. Cyprus- National Statistical Office (January 2009), Nicosia Other Regions- Eurostat, 2008 Notes: a) Average annual real per capita GDP growth in the EU-15 region over the last 35 years is approximately 2% (see Table 4).The projected GDP index for the EU-15 in 2035 is based on this growth rate being maintained over the period So, = x b) The 2035 projection for North Cyprus is based on an assumed 90% convergence target while a 100% target is assumed for South Cyprus. The targets are defined in terms of per capita real GDP expressed in PPS relative to the EU-15. Table 6 shows the growth rates required for each region to achieve the assumed convergence targets. For N. Cyprus the average annual growth rate is 4.4%, while the corresponding figure for the much richer region of S. Cyprus is 2.6%. Furthermore, given the 2007 population figures for Cyprus which show that 25% live in the North (see

17 16 Table 7), a target per capita GDP growth figure of 3.1% is calculated for the whole island. See Tables 5 and 6 and the accompanying notes for full details of these convergence target growth rates. Quite clearly, the required long-term growth rate is about 2 percentage points higher for N. Cyprus compared with S. Cyprus and this justifies a higher social discount rate for the former region. Table 6 CONDITIONAL TARGET GROWTH RATES FOR ECONOMIC CONVERGENCE (with respect to projected EU-15 PPS per capita GDP for 2035) N. CYPRUS S. CYPRUS ALL CYPRUS Growth Convergence target 4.37% (90%) 2.65% (100%) 3.08% (97.5%) Notes: a) The target average growth rates are for the period and the data on which they are based are presented in Table 5. b) The data period is consistent with the average life of the investment projects currently being funded by the European Commission out of the EU Structural Funds budget. Table 7 TOTAL POPULATION (000 S) FOR NORTH CYPRUS, SOUTH CYPRUS AND ALL OF CYPRUS: N. CYPRUS (23%) (23%) (23%) (22%) (25%) S. CYPRUS (77%) ALL CYPRUS (100%) (77%) (100%) (77%) (100%) (78%) (100%) (75%) (100%) Data source: N. Cyprus- Main Economic and Social Indicators, , Office of National Planning, Nicosia S. Cyprus- Republic of Cyprus Statistical Service, 2008

18 17 The elasticity of marginal social utility of income (e) Unfortunately, due to data limitations, the estimates of e for both North and South Cyprus are based only on tax rate data using equation (6). The consumer demand approach based on equation (4) requires reliable estimates of both income and compensated price elasticities of demand for a preference independent good such as food. For both N. Cyprus and S. Cyprus, it was only possible to obtain a relatively short series of annual demand data for food (or any other broad consumer product group): for N. Cyprus and for S. Cyprus. These periods are too short for any sensible co-integration analysis, especially as quarterly data were not available for either region. However, before turning to a tax-based approach, it is useful to note some demand-based estimates of e for other European countries so as to give at least some guidance concerning an appropriate empirical estimate for this component of the STPR. Based on co-integration analysis, Evans (2004) obtained an estimate of 1.3 for France and Percoco (2008) obtained a similar estimate for Italy. For the UK, Evans et al (2005) estimated an e value of 1.6 (this estimate is the same as that provided for India by Kula (2004)). In each of these empirical studies, food is the preference independent product group. The tax-based approach to the estimation of e focuses on the structure of income tax rates in North and South Cyprus. Tables 8 and 9 give full details of these rates in 2007 including the approximate percentage of tax-paying individuals falling into the relevant income bands. Casual inspection of these Tables reveals a milder degree of progression in the case of S. Cyprus, although the average wage-earner in each region pays the same rate of tax (20%) on all taxable income in excess of the basic personal tax allowance. If the average tax rate is calculated with respect to this excess income, on the grounds that diminishing marginal social utility of income only applies to income in excess of the minimum level required to meet basic living standards, then the average tax rate is equal to the marginal tax rate and thus a unitary value of e applies to the average income earner in both regions of Cyprus.

19 18 Table 8 PERSONAL INCOME TAX RATES FOR N. CYPRUS, 2007 TAXABLE INCOME Annual pre-tax YTL PERCENTAGE OF TAX-PAYING INDIVIDUALS AVERAGE TAX RATE- at mid-point of income band N/A 0% % 20% 20% % 21.4% 30% Over % 30.1% 40% Data source: National Statistical Office and Ministry of Finance, Nicosia Notes: a) YTL = New Turkish Lira b) Average annual pre-tax wage earnings = YTL c) Marginal tax rate (t) at the Average annual pre-tax wage = 20% MARGINALTAX RATE (%) d) Average tax rate (T/Y) is measured as the ratio of total tax liability (T) to pre-tax income less single person tax allowance (Y). Table 9 PERSONAL INCOME TAX RATES FOR S. CYPRUS, 2007 TAXABLE INCOME Annual pre-tax C PERCENTAGE OF TAX-PAYING INDIVIDUALS AVERAGE TAX RATE- at mid-point Of income band N/A 0% % 20% 20% % 21.7% 25% Over % 26.8% 30% Data source: Republic of Cyprus Statistical Service, 2008 Notes: a) C = Cyprus Pounds b) Average annual pre-tax wage earnings = C c) Marginal tax rate (t) at the Average annual pre-tax wage = 20% TAX RATE (%) d) Average tax rate (T/Y) is measured as the ratio of total tax liability (T) to pre-tax income less single person tax allowance (Y).

20 19 Tables 10 and 11 provide details of the marginal and average rates of income tax at the mid-points of the relevant taxable income bands for both regions. The calculations of e based on equation (6) are shown in the last row of each Table. The weighted average value of e for N. Cyprus is approximately 1.3 and the corresponding value for S. Cyprus is a bit lower at around 1.1 (the weights are based on the percentage of tax-payers falling into each of the taxable income bands). For full details of all the tax-based calculations of e for both regions of Cyprus, see Tables 8,9,10 and 11. These tax-based estimates of e are in keeping with those for most other European countries although the full range of values stretches from 1.0 to 1.5; see Evans and Sezer (2005), Evans (2005) and Percoco (2008). Some of the variation is due to the inclusion or exclusion of employees social security contributions in the tax rates, some is due to the income levels where marginal and average tax rates are calculated and some can be attributed to whether or not the average tax-rate is calculated with reference to all pre-tax wage income as opposed to income in excess of tax allowances. Table 10 TAX-BASED ESTIMATES OF THE ELASTICITY OF MARGINAL SOCIAL VALUATION OF INCOME (e) AT THE MID-POINTS OF TAXABLE INCOME BANDS IN 2007: N. CYPRUS YT = YT = YT = Marginal tax rate t(y) Average tax rate T/Y Log(1-t(Y)) Log(1-T/Y) e (% of Tax-payers) 1.00 (30%) 1.48 (50%) 1.43 (20%) Notes: a) At the average annual wage: e = 1.00 b) Weighted average value of e = 1.33

21 20 Table 11 TAX-BASED ESTIMATES OF THE ELASTICITY OF MARGINAL SOCIAL VALUATION OF INCOME (e) AT THE MID-POINTS OF TAXABLE INCOME BANDS IN 2007: S. CYPRUS C = C = C = Marginal tax rate t(y) Average tax rate T/Y Log(1-t(Y)) Log(1-T/Y) e (% of Tax-payers) 1.00 (50%) 1.18 (25%) 1.14 (25%) Notes: a) At the average annual wage: e = 1.00 b) Weighted average value of e = 1.08 To some extent, variation in e values obtained for a country is method-dependent and we have been constrained through lack of suitable data to rely on only one method for Cyprus. Application of this method has produced reasonably similar estimates of e for the two regions ranging from unity at the average wage rate to a weighted average of 1.3 for N. Cyprus as opposed to 1.1 for S. Cyprus. It is not unreasonable to use the same estimate of e for both regions of the island, somewhere between unity and 1.3. This is especially the case given that the EC is providing the major funding for social projects and thus it is its own social valuation function that counts. In fact, the EC may wish to apply the same or similar e value in all STPR estimates for EU members subject to variation only if local conditions dictate; see European Commission (2008). In fact, in keeping with the UK Treasury (2003), the EC may wish to consider a wide body of evidence on e based on several different methods (see theory section), in which case it may consider the surveys of evidence provided by Pearce and Ulph (1999) and Cowell and Gardiner (1999). The former suggested a range of values from , while the latter suggest So, it is prudent to consider the implications of different possible e values in the assessment of the STPR (and the regional welfare weights, see below) for each main region of Cyprus while placing particular emphasis on the value range , provided by the 2007 income tax data.

22 21 Estimates of the STPR Based on the evidence for each of the component parameters of the STPR (see above) it seems reasonable to apply common estimates of p and e in the calculation of each region s STPR. The preferred estimate of p is 1%. While allowance for some variation in the possible value of e is advisable, such variation will be applied in common to both North and South Cyprus; the values of 1 and 1.3 have already been highlighted. In relation to g the convergence-based figures presented in Table 6 are preferred. The conditional growth rates for the entire island are based on population-weighted growth rates for each region using the latest population figures in Table 7. The relevant calculation is x = So, g = 3.1% for the whole island assuming that the percentage population figures remain much the same over the period In the presentation of alternative possible values of the STPR, all component parameter estimates are expressed correct to one place of decimals (anything more is spurious accuracy). A) Lower fiscal estimate of e (1.0) N. Cyprus: STPR A = 1.0% + 1.0(4.4%) = 5.4% S. Cyprus: STPR B = 1.0% + 1.0(2.7%) = 3.7% All Cyprus: STPR C = 1.0% + 1.0(3.1%) = 4.1% B) Upper fiscal estimate of e (1.3) N. Cyprus: STPR A = 1.0% + 1.3(4.4%) = 6.7% S. Cyprus: STPR B = 1.0% + 1.3(2.7%) = 4.5% All Cyprus: STPR C = 1.0% + 1.3(3.1%) = 5.0% Empirical estimates of regional welfare weights for Cyprus Based on the theory embodied in equations (7) and (8), the regional welfare weight for N. Cyprus (W A ) is given by equation (11) and consists of the ratio of representative average regional income levels (Y B /Y A ) raised to the power of the absolute value of the elasticity of marginal social utility of income (e). It has already been established, in relation to estimates of the social discount rate, that a common estimate of e for N. and S. Cyprus is appropriate although this common estimate is subject to some uncertainty because different estimation approaches tend to produce differing results. For Cyprus, data limitations mean that only a revealed social values approach based on income tax

23 22 data was used to obtain empirical estimates of e and this particular method suggested the appropriateness of a value in the range Although this is the preferred range, it is prudent to consider a wider range of possible values for e which empirical work for other countries, based on a variety of methods, suggests. See, for example, Pearce and Ulph (1999), Cowell and Gardiner (1999) and Evans (2005). For the regional welfare weights for Cyprus we will apply different plausible estimates of e in the range but will place particular emphasis on our preferred tax-based estimates of 1 and 1.3. Both HM Treasury (2003) and the European Commission (2008) stress the policy relevance of either a unitary value or a figure which is close to this. Using South Cyprus as the numeraire means that the regional welfare weight for this comparatively rich region is set to unity (W B = 1) with the corresponding weights for both N. Cyprus (W A ) and the entire island (W C ) exceeding unity; the latter only modestly so given that 75% of the islanders live in the South according to recent population data (see Table 7). Income measures for constructing regional welfare weights Data limitations mean that we will need to focus on real per capita GDP in PPS rather than the preferred EDEI measure which takes account of any inter-regional differences in the distribution of equivalised household income (see equations (9) and (10) for details concerning the calculation of EDEI). The relevant per capita GDP indices for recent years are shown in Table 5. The figures indicate that while average living standards in the Greek part of Cyprus are less than 20% lower than those for the EU-15, N. Cyprus is very much poorer with an average standard of living that is less than half of that enjoyed in the EU-15. However, recent high growth in N. Cyprus (see Table 3) means that between 2004 and 2007 this region has improved its relative position with respect to both South Cyprus and the EU-15. For example, relative to the EU-15, average living standards have, according to the GDP indices in Table 5, increased from 41% in 2004 to 47% in Despite this improvement, further sustained periods of relatively high growth are required for economic convergence. Based on the formula for regional welfare weights, see equation (11), we can calculate the income ratio Y B /Y A where Y A represents the PPS volume index of per capita GDP for North Cyprus and Y B the same measure for South Cyprus. Based on the 2007 data in Table 5, the income ratio Y B /Y A = 93.4/52.8 = The practice adopted here for estimating regional welfare weights for Cyprus is broadly the same as that used in other studies focusing on the estimation of

24 23 regional welfare weights for application in social CBA; see, for example, Kula (2002), Evans et al (2005) and Sezer (2006). The regional welfare weights for both N. Cyprus and All Cyprus, based on alternative plausible values of e, are shown in Table 12. The weights for the entire island are population-based averages using the most recently available population figures (see Table 7). All relevant details are provided in the Table footnotes including the calculation of the welfare weight for the entire island. The preferred estimates are for the e values 1.0 and 1.3, respectively. So, the preferred estimate of the regional welfare weight for N. Cyprus lies in the range and the corresponding estimate for All Cyprus lies in the range Taking range mid-points produces a best estimate of 1.93 for N. Cyprus and 1.14 for the entire island. Of course, considerable care needs to be taken in applying these regional weights in CBA. For projects impacting either completely or substantially on N. Cyprus then it is reasonable to apply a regional welfare weight of 1.9 providing project net benefits are spread evenly across the regional population, or we have no particular reason to assume otherwise. If a particular section of the regional population is expected to be the main beneficiary, then the representative group income should be used to determine the relevant equity weight. The same considerations apply to projects impacting on both regions and, of course, to lower income groups in South Cyprus if these can be clearly identified as the main beneficiaries from the planned project. Obviously, the relevant welfare weight for whole island projects will change in the future if the geographical distribution of the island s population changes significantly. Table 12 REGIONAL WELFARE WEIGHTS FOR N. CYPRUS AND ALL CYPRUS, 2007 (S. CYPRUS = 1.00) W (e = 0.7) W (e = 1.0) W (e = 1.3) W (e = 1.6) N. Cyprus All Cyprus Notes: a) For N. Cyprus W A = (Y B / Y A ) e b) For All Cyprus W C = (Y B / Y C ) e and Y C = 0.25Y A Y B B Where 0.25 is the proportion of the island s total population living in N. Cyprus and 0.75 is the proportion living in S. Cyprus (see Table 7)

25 24 c) Y B = PPS per capita real GDP index for S. Cyprus in 2007 = 93.4 (EU-27 =100) d) Y A = PPS per capita real GDP index for N. Cyprus in 2007 = 52.8 (EU-27 =100) (See Table 5 for the GDP indices) e) The welfare weight estimates are based on equation (11) Equity-adjusted discount factors and dynamic regional welfare weights Subject to the aforementioned qualifications relating to the application of regional welfare weights in CBA for Cyprus, the preferred weights for both N. Cyprus and All Cyprus can be incorporated explicitly into project appraisal by combining them with the appropriate discount rates. Since N. Cyprus requires higher growth than S. Cyprus in the interests of economic convergence, the application of a higher discount rate will serve to make appropriate dynamic adjustments to the opening year value of W A. This means that the expected narrowing of the regional income differential over time is taken properly into account in the appraisal of the project. The same considerations apply to projects impacting on the entire population of Cyprus. So, taking account of both efficiency and regional equity criteria in CBA requires the application of the following equity adjusted discount factors to projected net benefits impacting generally on N. Cyprus and the whole island, respectively: (i) North Cyprus: W A (1+STPR A ) -t For e = 1.0: 1.77(1.054) -t For e = 1.3: 2.10(1.067) -t (ii) All Cyprus: W C (1+STPR C ) -t For e = 1.0: 1.12(1.041) -t For e = 1.3: 1.16(1.050) -t Notes: a) For N. Cyprus the STPR is consistent with a 90% convergence target by 2035; the average standard of living, on the PPS real per capita GDP basis, reaches 90% of that enjoyed in the EU-15. b) For All Cyprus the STPR is consistent with a weighted convergence target by 2035; the average standard of living reaches 97.5% of that enjoyed in the EU-15 (see Table 6).

26 25 Table 13 shows the equity-adjusted discount factors for North Cyprus and All Cyprus for the preferred values of e (with South Cyprus as numeraire), where it is reasonably assumed that the same value of e applies both inter-temporally in the discount rates and spatially in the regional welfare weights. Figures 1 and 2 highlight the differences between the adjusted present value welfare weights and clearly show the considerable boost to the discount factor in the case of North Cyprus. Table 13 EQUITY-ADJUSTED DISCOUNT FACTORS FOR PREFERRED VALUES OF e (e = 1.0 and 1.3) YRS SC(e=1) NC(e=1) C(e=1) SC(e=1.3) NC(e=1.3) C(e=1.3)