International Relative Price Levels: A Look Under the Hood

Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 1055 August 2012 International Relative Price Levels: A Look Under the Hood Jaime Marquez, Charles Thomas, and Corinne Land NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate discussion and critical comment. References to International Finance Discussion Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Recent IFDPs are available on the Web at www.federalreserve.gov/pubs/ifdp/. This paper can be downloaded without charge from the Social Science Research Network electronic library at www.ssrn.com.

International Relative Price Levels: A Look Under the Hood Jaime Marquez, Charles Thomas, and Corinne Land1 Abstract This paper examines the structure of international relative price levels using purchasing power parities (PPP) at the product-level from the 2005 World Bank’s International Comparison Program (ICP). Our examination is motivated by questions arising from two applications using economy-wide PPPs: the measurement of real effective exchange rates (REERs) and the correlation between prices and development. Specifically, how would our view on competitiveness be affected if one were to use PPP measures that exclude non-tradable categories? Is it the case that an increase in per-capita income raises the prices of non-tradable categories? These questions are not new. What is new here is the use of relative price levels (as opposed to indexes) at the product level for 144 countries that differ greatly in their level of development. Key Words: International Comparison Program, Purchasing Power Parity, Competitiveness, Penn Effect, Real Effective Exchange Rates, Tradability. JEL Codes: F41, F43. 1Theviewsinthispaperaresolelytheresponsibilityoftheauthorsandshouldnotbeinterpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of any other personassociatedwiththeFederalReserveSystem. WearegratefultoNadaHamadehforproviding the ICP data and to both Fred Vogel and D.S. Prasada Rao for numerous comments. We are also gratefultoRudolfsBems,NeilEricsson,andtoparticipantsinpreviouspresentationsofthispaper at George Washington University, the meetings of the Fall 2009 Midwest International Economics Group (Penn State), the Fall 2009 and Spring 2012 Workshops of the Federal Reserve Board, the 58th World Statistical Congress of the International Statistical Institute (Ireland, August 2011), andthe2012IMF’sResearchSeminarseries. Thematerialpresentedheredrawsfrom,andextends, the analysis in Thomas et al. (2011). The regression results use OxMetrics 6.20; see Doornik and Hendry (2007).

1 Introduction This paper examines the structure of international relative price levels using purchasing power parities (PPP) at the product-level from the 2005 World Bank’s International ComparisonProgram(ICP). Ourexaminationismotivatedbyquestions arising from two applications using the familiar economy-wide PPPs: the measurement of real effective exchange rates (REERs) and the correlation between prices and development.2 Economy-wide PPPs provide information on international relative price levels and hence capture a dimension of competitiveness not incorporated in indexes that measurepricechangesalone.3 Butarelevantquestion,sofarneglected,ishowwould our view on competitiveness be affected if one were to use PPP measures that exclude non-tradable categories? In addition, since it is acknowledged that prices for some categories are particularly difficult to compare across countries, to what extent are PPP-based GDP price comparisons being influenced by the readings on these “comparison-resistant” categories? Our calculations indicate that excluding comparsion-resistant categories halves the measured difference between U.S. prices and the prices of its major trading partners; excluding non-tradable categories eliminates the difference entirely. The obvious question raised by this finding is which measure is better for making inferences about international competitiveness: the measure including all the expenditure categories or the narrower measures including only tradable or comparable products? Though we do not have a definitive 2For reviews on the measurement of real effective exchange rates, see Froot and Rogoff (1995), Taylor(2003),Chinn(2005),KlauandFung(2006);otherrelevantpapersincludeLipsey,Molinari, and Kravis (1990), Hooper and Richardson (1991), and Turner and Van’t dac (1993). For the relation between prices and development, see Kravis, Heston, and Summers (1978); Summers and Heston (1991); Asea and Mendoza (1994); De Gregorio, Giovannini and Wolf (1994); Canzoneri, Cumbi and Diba (1996); Bergin, Glick, and Taylor (2006); Heston, Summers, and Aten (2006); Lothian and Taylor (2008); and Ravalion (2010). 3See Turner and Van’t dack (1993) and Thomas et al. (2008, 2011).

2 answer to this question, we follow Keynes (1925) and Corden (1994) and show that prices for non-tradable and comparison-resistant categories play an integral role in measuring international competitiveness. The correlation between aggregate prices and development, known as the Penn Effect, has been examined extensively. The conventional explanation for this correlation is that as development expands, demand across all expenditure categories increases, which raises the prices of non-tradables but not the prices of tradables because these are determined in world markets. This explanation raises an interesting question: is it the case that an increase in per-capita income raises the relative prices of non-tradable categories? This question has not been addressed before and ananswertoitisofinterestbecausefindingthatthesecorrelationsareabsentwould undermine the conventional explanation for the Penn Effect. To be sure, interest in disaggregation is not new.4 What is new here is the use the relative price levels (as opposed to indexes) at the product level for 144 countries that differ greatly in their level of development. Thenextsectiondescribesthedata; section3laysoutthebasicconstructsofour PPP-based REER and demonstrates its sensitivity to the exclusion of non-tradable and non-comparable categories. Section 4 reports the results from regressions relating the within-product relative prices to relative incomes. Section 5 offers a few concluding thoughts. 4BothAseaandMendoza(1994)andDeGregorioetal. (1994)usepriceindexesforproduction 20 sectors from 14 industrial countries; Canzoneri et al. (1996) uses aggregate prices for five production sectors of 13 OECD countries.

3 2 Data Description 2.1 ICP Data The ICP provided the 2005 benchmark purchasing power parities for 146 countries and 126 basic headings;5 a “basic heading” is the lowest level of disaggregation for which PPPs are computed.6 The ICP also provided country data on population, market exchange rates, the 2005 values for GDP, PPPs for GDP, and expenditures on each basic headings; these expenditures add up to GDP. Reliance on the 2005 ICP benchmarks has several advantages. First, they are the first to include actual price observations for China, and the first since 1985 to include actual price observations for India.7 Second, the ICP differentiates between government expenditures and private expenditures, facilitating international price comparisons. Finally, data collection uses the concept of "Structured Product Descriptions," which is a list of standardized attributes that identifies a product as narrowlyaspossible, enhancingproductcomparability.8 Thesedetaileddescriptions allowtheICPtoidentifyseveralbasicheadingsascomparison-resistant: government production of health services, collective services, social protection, education, and various medical services. The ICP does not provide, however, a taxonomy of basic headings as being tradable or not; indeed, developing a widely accepted taxonomy of tradability has remained elusive.9 Thus, given the difficulties of concisely defining tradability, we 5The data had incomplete records for Zambia and Zimbabwe, which are excluded from our analysis. 6For an early treatment, see Kravis and Lipsey (1990); the latest treatment is found in World Bank (2008, p. 14) and chapters 6 and 7 for details. 7See Chen and Ravallion (2008) and appendix G of World Bank (2008). 8See World Bank (2008, p. 142). 9De Gregorio et al. (1994) define a product as tradable if at least 10 percent of the value of its production "worldwide" is exported. DeGregorio et al. examine 20 production sectors for a world consisting of 14 industrial countries. The practical appeal of their definition diminishes as soon as one expands the list ofcountriesincluded in the world and uses disaggregated expenditure categories, which is what we do here.

4 use a subjective but, we believe, reasonable classification of basic headings as tradable. However, one of the advantages of using the disaggregated price data is that one can examine the implications of alternative definitions by re-grouping the basic headings accordingly. So, our definition is ad-hoc but it is not rigid. 2.2 Cross-country Distributions of Relative Prices Wemeasurethe2005bilateralpriceleveloftheUnitedStateswithrespecttocountry  in basic heading  as    = $ , =1126;  =1144 (1)     where  is the 2005 market exchange rate for country  with respect to the U.S.  $ dollar and  is the PPP exchange rate of the  basic heading in the     country, defined as  where  is the price level (local currency per unit) of the     basic heading in the  country. A value of 2 for  means that the price of  the  basic heading in the United States is twice that of the same basic heading in country , when both are expressed in a common currency. Givenequation(1), weassemblethecross-countrydistributionsofrelativeprices for each basic heading to examine two questions: Are the prices of a given basic heading equalized across countries?10 Is the dispersion of relative prices across countries related to whether the product is tradable? Figure 1 shows the cross-country distributions of relative prices ( ) for each  basicheading; thefigureshowsthebasicheadingsthattheICPidentifiesascomparison resistant and the basic headings that we identify as tradable and non-tradable. For each distribution, we show the median and four percentiles; these distributions are arranged in descending order of their medians. The data show that most of the 10For an earlier treatment of this question, see Isard (1977).

5 medians are well above one, especially for comparison-resistant products. Further, themediansofthedistributionsfortradableproductsaregenerallylowerthanthose fornon-tradableproducts. Finally,thedispersionofrelativepricesfornon-tradables is considerably larger than that for tradables. These properties resonate with our priors that international trade tends to equate prices across countries and that this tendency is greatest for the most readily tradable products. 3 U.S. Relative Price Levels in 2005 We now assess the importance of the product mix for measuring U.S. international relative price levels. To this end, we begin by assembling the cross-country distributions of relative prices for the largest trading partners of the United States.11 Figure 2 shows that the median for most of these distributions is quite close to one and well below the median for the distributions using 144 countries. To emphasize the importance of the country mix, figure 3 compares the distributions of relative prices without differentiating across basic headings. The figure shows that the cross-country distribution of relative prices for U.S. trading partners is considerably narrower and more symmetrical than the one for the 144 countries. To provide some perspective on what we are after, figure 4 depicts U.S. relative price levels based on the ICP’s published GDP parities for the 34 countries included in figure 2. By this measure, U.S. GDP prices were twice as high as the GDP prices in India and 30 percent below those in Switzerland. The question of interest is to what extent are these measures of relative prices influenced by the prices of basic 11We use the 34 countries included in the broad measure of the Federal Reserve’s real effective value of the dollar (Leahy 1998): Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China, Colombia, Finland, France, Germany, Hong Kong, India, Indonesia, Ireland, Israel, Italy, Japan, Korea, Malaysia, Mexico, Netherlands, Philippines, Portugal, Russia, Singapore, Spain, Sweden, Switzerland, Taiwan, Thailand, United Kingdom, and Venezuela; these countries account for roughly 92 percent of 2005 total U.S. trade. The data come from the U.S. Commerce Department.

6 headings that are either non-tradable or comparison-resistant? Addressing this question involves two steps. The first one is to measure the aggregate relative price level between the United States and the  trading partner using alternative basic headings. To this end, we use a weighted geometric average:  =   =134 (2)     ∈ Q ¡ ¢ where  is a list of basic headings,  is defined in equation (1),  is the share   of the  country’s expenditure on the  basic heading, and  = 1. A    ∈ valueof2for meansthatU.S.pricesaretwiceashighasthosePinthe country  in list . We consider three lists:  : All headings 1  : Authors’ defined tradable headings 2  : All headings excluding ICP’s “comparison resistant” headings 3 The second step is to map the  into alternative measures of the U.S. real  effective exchange rate. To this end, we use a weighted geometric mean: 34  = ( )  =    (3)   1 2 3 =1 Q where isthelevelof theU.S.real effectiveexchangerateforlist,  isdefined   in equation (2), and  is the U.S. bilateral trade weight associated with the   country.12 A value of 2 for  means that the aggregate of U.S. prices in list  is  12We use the weighting scheme adopted by the Federal Reserve (Leahy, 1998). In this scheme, theun-normalizedbroadweightforagivencountryis =05  +025  +025  where is  ·  ·  ·   theshareofnon-oilimportsfromthecountry; istheexportsharetothecountry;and   is the extent to which exports to the  country compete with exports from other countries; the normalizedbroadweightofthecountryis =  Thedatacomefrom theU.S.Commerce  Σ Department.

7 twice as high as the average of aggregate prices of U.S. trading partners in the same list. Figure 5 reports our calculations. Asa check on our procedures, wecompare the "all-headings" measure  to the published ICP’s GDP relative prices, denoted 1 as  and shown earlier in figure 4. Excluding Thailand and Malaysia, the  two measures are very close and two factors help explain this gap. First,  1 is measuring prices of domestic expenditures whereas  is measuring prices of  expendituresondomesticproducts—thatis,excludingimportsandincludingexports. Second, equation (2) might differ from the one used by the ICP. Taking  as our benchmark of economy-wide relative prices, we find that 1 the relative-price measure excluding non-tradable headings ( ) shifts down the 2 structure of U.S. relative price levels with the shift being particularly pronounced vis-à-vis emerging economies. For example U.S. aggregate prices are measured to be 105 percent above those in India; whereas, if we exclude non-tradable headings, the gap shrinks to 60 percent. In contrast, vis-à-vis Switzerland, the measured differential shrinks by only one percent with the exclusion of non-tradables. The relative-price measure excluding comparison-resistant headings ( ) also shifts 3 down the structure of relative prices, but to a lesser extent than when prices in non-tradable headings are excluded. The rightmost column of figure 5 shows the sensitivity of  to changes in the  mix of basic headings. Specifically, if one includes the prices of all headings ( ), 1 then U.S. prices appear to be 25 percent above the average of its trading partners. If we exclude prices of headings that are difficult to compare across countries, then themeasuredwedgeshrinkstoabout10percent( ). Finally, ifwelimitourselves 2 to prices for tradable basic headings ( ), then there appears to be little difference 3 between U.S. prices and the average of prices of its major trading partners.

8 This finding suggests that excluding either comparison-resistant or non-tradable basic headings from the product mix lowers the measure of U.S. relative prices. We do not take this finding as evidence for designating either  or  as the 2 3 better measure for making inferences about international competitiveness. Rather, we consider the comparison-resistant and non-tradable basic headings essential to analyzing international price positions. Our view is not new. Indeed, Keynes noted in 1925 (p. 301): “it is the price of sheltered [non-tradable] goods that determines the competitiveness of a country because it is those prices that determine the cost of producing tradable goods. The price of unsheltered goods will be equalized by trade."13 Further, Keynes’ view is formalized by Corden (1994, p. 267) who argues that a country’s international competitiveness is determined by the profitability in industries producing tradables. Specifically, Corden measures international competitiveness in the  industry as the ratio of the  country’s price markup to that of the United States:      =   (4)      µ ¶ µ ¶ where  is the dollar price of the  tradable industry in the  country, and   is the associated marginal cost, also in dollars. Thus, if   1, then the    country is said to be more competitive than the United States because it has a higher price markup. Further, if one assumes that international trade equalizes prices of tradable products, then        =  =  (5)        µ ¶ µ ¶ 13Of course, productivity differentials also figure importantly into the mapping from the prices of non-tradables to the cost of producing tradables. Unfortunately, broad, cross-country data that compare the levels of productivity are not available.

9 Again, if   1, then the  country is more competitive than the United States  because it has lower marginal costs. Marginal costs are directly related to factor prices, such as wages that are, in turn, directly related to the importance of nontradables (e.g. housing, medical services) in domestic expenditures. Given that comparison-resistant and non-tradable basic headings account for more than half of U.S. total domestic expenditures (figure 6), abstracting from them yields an incomplete characterization of international competitiveness. 4 Development and Relative Price Levels In this section we study the correlation between the level of economic development andthelevelofrelativepricesacrosscountries,knownasthePennEffect. Intuitively, higher levels of income raise the demands for tradable and non-tradable goods and services. The higher demand for tradables is met through international trade with no change in tradable’s prices. But the higher demand for non-tradables is met by the fixed, local supply, raising the price of non-tradables and, thus, the overall price level. So the natural question to ask is whether the data support the view that an increase in income raises the relative prices of non-tradable categories. To this end, we begin by replicating the Penn Effect and postulate that ln =+ ln+ ˜(02) (6)  · where  =(  )  1 144 0 ···  is the U.S. price relative to the price of the  country using ICP’s  published GDP parities

10  =( 1 144)  ···  0  =(  1 )   ·   $  is the GDP of the  country   is the population of the  country  For the conventional explanation of the Penn Effect to be consistent with the aggregate data, one needs to find that  0: An increase in the per-capita income of the  country relative to U.S. per-capita income raises the price in the  country relative to the corresponding U.S. price and, hence, lowers  . The regression  yields ln = 01715 02354 ln  −  (00502) (00219) wherethestandarderrorsofthecoefficientsarecorrectedforpotentialheteroskedasticity of the residuals.14 The result confirms that   0 when using the ICP’s published parities for GDP. To examine whether this correlation holds at the level of basic headings, we use ln = + ln+  =1126  ˜(02) (7)       · where =(  ) and isdefinedinequation(1). Fortheconventional  1 ··· 144 0  explanation of the Penn Effect to be consistent with the data at the disaggregate level, one needs to find that  0: An increase in the per-capita income of the   country relative to U.S. per-capita income tends to raise the price of the  good in the  country relative to the corresponding U.S. price, which then lowers  .  14TheregressionstatisticsareSER:0.289; 2 :0.55. TheJarque-Beratestfornormalityis4.3466 and one cannot reject the hypothesis that the residuals are normally distributed at the 5 percent significance level.

11 Thus finding that  = 0 for non-tradables would undermine the usefulness of the  conventional explanation for the Penn Effect. Figure 7 shows the estimates of  and their 95 percent confidence bands.15 For  the vast majority of basic headings, the estimated  is negative and significantly  different from zero. That is, for most of the basic headings, higher prices in the  countryareassociatedwithhigherincomesinthecountry. Wealsonotethatthe estimatesof tendtobelarger(inabsolutevalue)fortheheadingsthatwedenoted  non-tradables than for the headings we denoted tradables. This finding strengthens the empirical support of the conventional explanation of the Penn Effect. This pattern for the  s is not a necessary consequence of the pattern seen  in figure 1, as the estimated intercept could absorb the variation in the medians. Indeed, the estimated standard errors of the regressions bear no relationship to the ordering of the basic headings (figure 8). Finally, note that for three of these products (motorcars, motorcycles, and passenger transport by air), the estimated  is significantly positive, meaning that higher prices are associated with lower incomes, a deviation from the Penn Effect. This seemingly contradictory finding might be the result of some countries treating these products as luxuries and thus levying taxes on them. 5 Conclusions The view under the hood yields two insights that might be useful for practical analyses and further research. First, we get a good sense of the extent to which the real effective exchange rate for the United States is affected by the inclusion of non-tradable prices. For 2005, with the full product list, the U.S. REER shows U.S. prices to be more than 15These bands use the heteroskedasticity-corrected standard errors.

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14 [14] Klau, M. and S. Fung, 2006, "The New BIS Effective Exchange Rate Indices," BIS Quarterly Review, March, 51-65. [15] Kravis,I.,A.Heston,andR.Summers,1978,InternationalComparisonsofReal Product and Purchasing Power, Baltimore: Johns Hopkins University Press. [16] Kravis, I. and R. Lipsey, 1990, "The International Comparison Program: Current Status and Problems," NBER Working Paper, No. 3304. [17] Leahy, M., 1998, "New Summary Measures of the Foreign Exchange Value of the Dollar," Federal Reserve Bulletin, October, 811-18. [18] Lipsey,R.,L.Molinari,andI.Kravis,1990,"MeasuresofPricesandPriceCompetitiveness in International Trade in Manufactured Goods," NBER Working Paper, No. 3442. [19] Lothian, J. and M. Taylor, 2008, "Real Exchange Rates Over the Past Two Centuries: HowImportantistheHarrod-Balassa-SamuelsonEffect?"Economic Journal, 118, 1742-1763. [20] Ravallion, M., 2010, "Price Levels and Economic Growth: Making Sense of the PPP Changes Between ICP Rounds," World Bank Policy Research Working Paper, No. 5229. [21] Summers, R. and A. Heston, 1991, "The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950-1988," Quarterly Journal of Economics, 106, 327-368. [22] Taylor, M., 2003, "Purchasing Power Parity," Review of International Economics, 11, 436-452.

15 [23] Thomas, C., J. Marquez, and S. Fahle, 2008, "Measuring U.S. International Relative Prices," Federal Reserve Board International Finance Discussion Paper, No. 917. [24] Thomas, C., J. Marquez, J. Coonan, and S. Fahle, 2011, “International Relative Price Levels: Stylized Facts,” in F. Vogel and D.S. Prada Rao (editors), Measuring the Size of The World Economy: A Framework, Methodology and Results from the International Comparison Program, Washington DC: World Bank, forthcoming. [25] Turner, P. and J. Van’t dack, 1993, "Measuring International Price and Cost Competitiveness," BIS Economic Papers, No. 39. [26] World Bank, 2008, Global Purchasing Power Parities and Real Expenditures: 2005 International Comparison Program, Washington DC: World Bank.

110000..000000 Figure 1: Distribution of Relative Prices (Pus/Pi) ‐‐ log scale 126basic headings, all countries 0.05 0.2 0.5 0.8 0.95 Comparable, tradable Comparable, non‐tradable Non‐comparable, non‐tradable 1100..000000 11..000000 0.100 Boxplot Charts - T&NT Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls htlh tvog‐ spme fo pmoC cude tvog‐ spme fo pmoC vtclc tvog‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog‐ selas morf stpieceR htlh tvog‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog‐ noitcudorp no sexat teN cude tvog‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog‐ noitcudorp no sexat teN vtclc tvog‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo riapeR kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog‐ prus gnitarepo ssorG vtclc tvog‐ prus gnitarepo ssorG htlh tvog‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw lareniM piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh rojaM dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP 16 Figure 1: Distribution of Relative Prices (Pus/Pi) ‐‐ log scale 126basic headings, all countries 0.05 0.2 0.5 0.8 0.95 Comparable, tradable Comparable, non‐tradable Non‐comparable, non‐tradable

FFFFFiiiiiggggguuuuurrrrreeeee 22222::::: DDDDiiiissssttttrrrriiiibbbbuuuuttttiiiioooonnnn ooooffff RRRReeeellllaaaattttiiiivvvveeee PPPPrrrriiiicccceeeessss ‐‐‐‐‐‐‐‐ lllloooogggg ssssccccaaaalllleeee 111110000000000.....000000000000000 111122226666 bbbbaaaassssiiiicccc hhhheeeeaaaaddddiiiinnnnggggssss,,,, 33334444 FFFFRRRRBBBB ccccoooouuuunnnnttttrrrriiiieeeessss 0000....00005555 0000....2222 0000....5555 0000....8888 0000....99995555 CCCCoooommmmppppaaaarrrraaaabbbblllleeee,,,,ttttrrrraaaaddddaaaabbbblllleeee CCCooommmpppaaarrraaabbbllleee,,, nnnooonnn‐‐‐tttrrraaadddaaabbbllleee NNNooonnn‐‐‐cccooommmpppaaarrraaabbbllleee,,, nnnooonnn‐‐‐tttrrraaadddaaabbbllleee 11110000....000000000000 111...000000000 00..110000 htlh tvog‐ spme fo pmoC cude tvog‐ spme fo pmoC vtclc tvog‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog‐ selas morf stpieceR htlh tvog‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog‐ noitcudorp no sexat teN cude tvog‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog‐ noitcudorp no sexat teN vtclc tvog‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo ri kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog‐ prus gnitarepo ssorG vtclc tvog‐ prus gnitarepo ssorG htlh tvog‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh ro dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP Figure 2: Distribution of Relative Prices ‐‐ log scale 100.000 126 basic headings, 34 FRB countries 0.05 0.2 0.5 0.8 0.95 Comparable,tradable Comparable, non‐tradable Non‐comparable, non‐tradable 10.000 1.000 0.100 htlh tvog‐ spme fo pmoC cude tvog‐ spme fo pmoC vtclc tvog‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog‐ selas morf stpieceR htlh tvog‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog‐ noitcudorp no sexat teN cude tvog‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog‐ noitcudorp no sexat teN vtclc tvog‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo riapeR kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog‐ prus gnitarepo ssorG vtclc tvog‐ prus gnitarepo ssorG htlh tvog‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw lareniM piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh rojaM dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP Figure 2: Distribution of Relative Prices ‐‐ log scale 100.000 126 basic headings, 34 FRB countries 0.05 0.2 0.5 0.8 0.95 Comparable,tradable Comparable, non‐tradable Non‐comparable, non‐tradable 10.000 1.000 0.100 Boxplot Charts - T&NT WARP Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls htlh tvog‐ spme fo pmoC cude tvog‐ spme fo pmoC vtclc tvog‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog‐ selas morf stpieceR htlh tvog‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog‐ noitcudorp no sexat teN cude tvog‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog‐ noitcudorp no sexat teN vtclc tvog‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo riapeR kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog‐ prus gnitarepo ssorG vtclc tvog‐ prus gnitarepo ssorG htlh tvog‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw lareniM piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh rojaM dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP 17 Figure 2: Distribution of Relative Prices ‐‐ log scale 126 basic headings, 34 FRB countries 0.05 0.2 0.5 0.8 0.95 Comparable,tradable Comparable, non‐tradable Non‐comparable, non‐tradable

3000 2500 2000 1500 ycneuqerF Figure 3: Histogram of Relative Prices ‐ Ln(Pus/Pi) 3000 All Countries All Products 2500 FRB Countries All Products 2000 1500 1000 500 0 Histograms - More Bins Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls ycneuqerF 5.2‐ 52.2‐ 2‐ 57.1‐ 5.1‐ 52.1‐ 1‐ 57.0‐ 5.0‐ 52.0‐ 0 52.0 5.0 57.0 1 52.1 5.1 57.1 2 52.2 5.2 57.2 3 52.3 5.3 57.3 4 52.4 5.4 57.4 5 52.5 5.5 57.5 6 eroM 18 Figure 3: Histogram of Relative Prices ‐ Ln(Pus/Pi) All Countries All Products FRB Countries All Products Bin

FFFFFiiiiiggggguuuuurrrrreeeee 44444::::: PPPPPuuuuubbbbbllllliiiiissssshhhhheeeeeddddd DDDDDooooommmmmeeeeessssstttttiiiiiccccc EEEEExxxxxpppppeeeeennnnndddddiiiiitttttuuuuurrrrreeeeesssss LLLLLnnnnn RRRRReeeeelllllaaaaatttttiiiiivvvvveeeee PPPPPrrrrriiiiiccccceeeeesssss (((((PPPPPuuuuusssss/////PPPPPiiiii))))) 111111......222222000000000000 PPPPuuuubbbblllliiiisssshhhheeeedddd DDDDoooommmm.... EEEExxxx.... 11111.....000000000000000 00000.....888880000000000 0000....666600000000 0000....444400000000 000...222000000 000...000000000 ‐‐00..220000 ‐‐00..440000 ‐00.660000 aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF aisyalaM aibmoloC BR ,aleuzen lizarB elihC anihC ,naw eropagniS ocixeM anihC ,gnoK .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK de dnalniF nedewS dnalerI dnalreztiwS Figure 4: Published Domestic Expenditures Ln Relative Prices (Pus/Pi) 1.200 Published Dom. Ex. 1.000 0.800 0.600 0.400 0.200 0.000 ‐0.200 ‐0.400 ‐0.600 aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF naissuR aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK gnoH .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK detinU dnalniF nedewS dnalerI dnalreztiwS Figure 4: Published Domestic Expenditures Ln Relative Prices (Pus/Pi) 1.200 Published Dom. Ex. 1.000 0.800 0.600 0.400 0.200 0.000 ‐0.200 ‐0.400 ‐0.600 Selected WARPs Chart Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF naissuR aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK gnoH .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK detinU dnalniF nedewS dnalerI dnalreztiwS 19 Figure 4: Published Domestic Expenditures Ln Relative Prices (Pus/Pi) Published Dom. Ex.

FFFFFiiiiiggggguuuuurrrrreeeee 55555::::: SSSSSeeeeellllleeeeecccccttttteeeeeddddd DDDDDooooommmmmeeeeessssstttttiiiiiccccc EEEEExxxxxpppppeeeeennnnndddddiiiiitttttuuuuurrrrreeeee GGGGGrrrrrooooouuuuupppppiiiiinnnnngggggsssss LLLLLnnnnn RRRRReeeeelllllaaaaatttttiiiiivvvvveeeee PPPPPrrrrriiiiiccccceeeeesssss (((((PPPPPuuuuusssss/////PPPPPiiiii))))) 111111......222222000000000000 PPPPuuuubbbblllliiiisssshhhheeeedddd DDDDoooommmm.... EEEExxxx.... 11111.....000000000000000 AAAAllllllll 6666‐‐‐‐ddddiiiiggggiiiitttt DDDDoooommmm.... EEEExxxx.... TTTTrrrraaaaddddeeeeaaaabbbblllleeee DDDDoooommmm.... EEEExxxx.... 00000.....888880000000000 CCCooommmpppaaarrraaabbbllleee DDDooommm... EEExxx... 0000....666600000000 0000....444400000000 000...222000000 000...000000000 ‐‐00..220000 ‐‐00..440000 ‐00.660000 aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF na aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK g .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK deti dnalniF nedewS dnalerI dnalreztiwS sthgiewedarT Figure 5: Selected Domestic Expenditure Groupings Ln Relative Prices (Pus/Pi) 1.200 Published Dom. Ex. 1.000 All 6‐digit Dom. Ex. Tradeable Dom. Ex. 0.800 Comparable Dom. Ex. 0.600 0.400 0.200 0.000 ‐0.200 ‐0.400 ‐0.600 aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF naissuR aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK gnoH .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK detinU dnalniF nedewS dnalerI dnalreztiwS sthgiewedarT .S.U htiw .gvA Figure 5: Selected Domestic Expenditure Groupings Ln Relative Prices (Pus/Pi) 1.200 Published Dom. Ex. 1.000 All 6‐digit Dom. Ex. Tradeable Dom. Ex. 0.800 Comparable Dom. Ex. 0.600 0.400 0.200 0.000 ‐0.200 ‐0.400 ‐0.600 Selected WARPs Chart Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF naissuR aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK gnoH .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK detinU dnalniF nedewS dnalerI dnalreztiwS sthgiewedarT .S.U htiw .gvA 20 Figure 5: Selected Domestic Expenditure Groupings Ln Relative Prices (Pus/Pi) Published Dom. Ex. All 6‐digit Dom. Ex. Tradeable Dom. Ex. Comparable Dom. Ex.

0.700 0.650 0.600 0.550 0.500 0.450 0.400 0.350 0.300 Selected Expenditures Chart Z:\LandMarquezThomas\Copy of Final detailed results-Researchers.xls aidnI senippilihP dnaliahT aisenodnI anihC anitnegrA noitaredeF naissuR aisyalaM aibmoloC BR ,aleuzeneV lizarB elihC anihC ,nawiaT eropagniS ocixeM anihC ,gnoK gnoH .peR ,aeroK learsI lagutroP niapS adanaC ailartsuA airtsuA ylatI ynamreG muigleB sdnalrehteN ecnarF napaJ modgniK detinU dnalniF nedewS dnalerI dnalreztiwS setatS detinU Figure 6: 21 Selected Expenditure Shares Non‐comparable Non‐tradable

0.5 0.4 0.3 0.2 0.1 0 ‐0.1 ‐0.2 ‐0.3 ‐0.4 ‐0.5 ‐0.6 ‐0.7 ‐0.8 ‐0.9 ‐1 All headings corrected SE ‐Plot Z:\LandMarquezThomas\Relative_Prices_Development.xlsx htlh tvog ‐ spme fo pmoC cude tvog ‐ spme fo pmoC vtclc tvog ‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog ‐ selas morf stpieceR htlh tvog ‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog ‐ noitcudorp no sexat teN cude tvog ‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog ‐ noitcudorp no sexat teN vtclc tvog ‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo riapeR kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog ‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog ‐ prus gnitarepo ssorG vtclc tvog ‐ prus gnitarepo ssorG htlh tvog ‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog ‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog ‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw lareniM piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh rojaM dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP 22 Figure 7: Corrrelation Between Relative Prices and Development: 95% Confidence Band 126 Basic Headings +2 HACSE LRelativePCGDP_PPP ‐2 HACSE

1.2 1 0.8 0.6 0.4 0.2 0 All headings corrected SE ‐Plot Z:\LandMarquezThomas\Relative_Prices_Development.xlsx htlh tvog ‐ spme fo pmoC cude tvog ‐ spme fo pmoC vtclc tvog ‐ spme fo pmoC scvs latneD scvs latipsoH noitacudE scvs citsemoD scvs demaraP scvs lacideM raewtoof fo erih & riapeR piuqe gnissecorp ofni & otohp ,v‐a fo riapeR htlh tvog ‐ selas morf stpieceR htlh tvog ‐ noitcudorp no sexat teN step rof scvs hto & yranireteV gnisuoh rof slatner detupmi & lautcA vtclc tvog ‐ noitcudorp no sexat teN cude tvog ‐ selas morf stpieceR scvs trpsnrt desahcrup htO occaboT stnemhsilbatse gnimoorg srep & snolas riaH secnailppa dlhsh fo riapeR noitcetorp laicoS sgnidliub laitnediseR sgnidliub laitnediser‐noN daor yb trpsnrt ssaP ntsrP vtclc tvog ‐ noitcudorp no sexat teN vtclc tvog ‐ selas morf stpieceR .c.e.n scvs htO scvs dlhsH scvs larutluC daerB taog & nottum ,bmaL gnillewd eht fo riaper & tniaM doofaes & hsif nezorf ro hserF skrow gnireenigne liviC piuqe trpsnrt srep fo riaper & tniaM yawliar yb trpsnrt ssaP piuqe trpsnrt srep fo tcepser ni scvs htO sleuf htO saG tiurf dellihc ro hserF laev & feeB gnihtolc fo riaper & gninaelC scvs latsoP selbategev dellihc ro hserF sgnirevoc roolf & sgnihsinruf ,erutinruf fo riapeR kroP trpsnrt ssap denibmoC scvs gnitrops & ceR htlh tvog ‐ pmusnoc mtnI gnillewd eht ot ler scvs csiM cude tvog ‐ prus gnitarepo ssorG vtclc tvog ‐ prus gnitarepo ssorG htlh tvog ‐ prus gnitarepo ssorG syadiloh egakcaP dorp lacituecamrahP seotatop dellihc ro hserF eciR ecnahc fo semaG cude tvog ‐ pmusnoc mtnI ecnarusnI sgnirevoc roolf hto & stepraC c.e.n scvs laicnanif htO MISIF yrenoitats & skoob ,srepapsweN seirossecca csim & sloot llamS sgnihsinruf & erutinruF yticirtcelE seirossecca & slairetam gnihtolC step & snedraG vtclc tvog ‐ pmusnoc mtnI sehctaw & skcolc ,yrelleweJ aidem gnidroceR stceffe srep htO eniragram & rettuB scvs gniretaC slisnetu dlhsh & erawelbat ,erawssalG selcyciB dorp htO reeB stnemraG gnillewd eht ot ler scvs csim & ylppus retaW erac srep rof dorp & selcitra ,secnailppA dorp yrekab htO piuqe trpsnrT piuqe & secnailppa lacitueparehT .c.e.n dorp dooF selitxet dlhsH sdoog dlhsh elbarud‐noN scvs xafelet & enohpeleT secnailppa dlhsh cirtcele llamS klim hserF raewtooF dorp lacidem htO stiurf dessecorp ro devreserp ,nezorF yrtluoP dorp desab‐gge & sggE cer roodni & roodtuo rof selbarud rojaM yenoh & sedalamram ,smaJ yawretaw dnalni & aes yb trpsnrt ssaP eseehC staf & slio elbide htO aococ & aet ,eeffoC seciuj elbategev & tiurf ,sknird tfos ,sretaw lareniM piuqe xafelet & enohpeleT ton ro cirtcele rehtehw secnailppa dlhsh rojaM dorp klim & klim devreserP eniW dorp atsaP ruolf & slaerec htO piuqe gnissecorp ofni & otohp ,lausiv‐oiduA piuqe & sloot rojaM selbategev devreserp ro nezorF raguS stiripS piuqe & smeti cer htO doofaes & hsif devreserP piuqe & dorp lateM scvs noitadommoccA snoitaraperp & staem htO srac rotoM maerc eci & etalocohc ,yrenoitcefnoC selcyc rotoM piuqe trpsnrt srep rof stnacirbul & sleuF ria yb trpsnrt ssaP 23 Figure 8: Standard Error of Regression: Equation (7) 126 Basic Headings