Income Differences Across Countries

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1 Income Differences Across Countries Pete Klenow Stanford University Society for Economic Dynamics July 6th, 2006 Vancouver, Canada 1

2 2000 PPP Income per capita 90 th /10 th th /25 th 8.8 S.D. of logs 1.16 Source: Penn World Table 6.1 (86 countries) 2

3 Relative Income Per Capita United States Norway Canada Hong Kong Switzerland Australia Japan Sweden Germany France Great Britain Italy Israel South Korea Argentina Malaysia Mexico Russia Brazil Thailand Egypt China Indonesia India Pakistan Malawi Nigeria Ethiopia Tanzania Source: Penn World Table

4 Production function α Y = K ( AhL) 1 α Y L h = PPP GDP pop = population = hours worked K = PPP physical capital = human capital per worker A = a residual 4

5 A useful decomposition Y L K = pop pop Y α 1 α Ah 5

6 Point 1: Quality and Variety Quality: Perhaps 30% higher in rich vs. poor. ICP: services are comparison resistant. half is missed in PPP calculations. Source: Hummels and Klenow (2005) 6

7 Price of Medical Care 4 2 Relative to the U.S. = 1 1 1/2 1/4 1/8 1/16 TZA CHE MKD SWE BMU NOR JAM ATG FINGER AUT DNK USA YEM FRA ESP JPN ISRNLD BEL LBN TTO NZL IRL BHR PRT AUS ITA NGA GAB BHSGBR QAT SYR ISL CAN GRC OMN HRV BRA SVN BRB BWA URY ARG HKG TUR EGY BLZ KOR VCT JOR POL CHL KNA SGP FJI GRD BEN VENMEX COG CIV ECU LCA DMA MLI SEN PER MAR EST SVK MDG CMR PA N HUN SWZ LVA RUS TUN KEN BOL CZE KAZ LTU THA PHL IDNBGR SLE UZBZWEUKR ALB MDA BLR ROM IRN MUS ZMB MWI VNM BGD GEO KGZPAK NPL ARM AZE GIN LKA TJK TKM LUX 1/32 1/64 1/64 1/32 1/16 1/8 1/4 1/2 1 2 PPP GDP per worker (U.S. = 1) Source: Penn World Table (114 countries in 1996) 7

8 4 Price of Education Relative to the U.S. = /2 1/4 1/8 1/16 1/32 TZA NGA MWI ZMBCOG BEN SLE SEN MLI KEN MDG YEM VNM NPL CMR MDA CIVGIN ZWE FJI TTO HRV THA KNA LCA JAM DMA BLZ TURPOL HUN PER SVK ATG MEX CZE ARG VCT GRD IRNBRACHL PAK EST URY LVA ECU LTURUS PA N VEN BOL IDN LKA PHL ALB UKR KAZ ROM BLR UZB BGR AZE BGD KGZ ARM GEO MKD LBN CHE GER SWE JPN USA NOR FIN FRA AUT NLD DNK HKG BEL GAB GBR QAT BMU BWA ISL BHR NZL ISR CAN ITA ESP IRL AUS SGP SYR MUS TUN MARJOR GRC OMN SVN KOR EGY SWZ PRT BHS 1/64 1/64 1/32 1/16 1/8 1/4 1/2 1 2 PPP GDP per worker (U.S. = 1) BRB LUX Source: Penn World Table (114 countries in 1996) 8

9 Point 1: Quality and Variety Variety: Perhaps 15% higher in rich vs. poor. Suppose 2/3 (consumer portion) missed. Taken together, factor of 30 rather than 24! Source: Hummels and Klenow (2002) 9

10 Point 2: L/pop Prescott, Rogerson: Explains income gap b/w U.S., Western Europe Alwyn Young: Explains 20% of growth in Asian Tigers, China Parente, Rogerson & Wright: Poor do more home work, less market work 10

11 Labor Force / Population 70% JPN 60% 50% 40% 30% ZAR TZA CHN SGP ISLCHE THA DNK SWE CAN HKG USA COG CMR JAM AUS BEN BRB FIN GBR GER NER RWA KEN ROM NOR MOZ MLI UGA CAF GHASEN ZWE GNB GMB LSO PNG NZL CYP AUT NLD COL POL URY MUSPRT FRA MWI PERPRYTUR TWN NPL HTI LKA ARG KOR BEL TGO HUN GRC IND BOL PHL IDN ESP ITA CRI CHL TTO IRL GUY PAN ISR SLE BRA VEN MYS FJI BWAMEX ZMB ZAF TUN HND DOMDZA ECU SLV EGY IRN PAK GTM BGD SYR JOR 20% log income per worker Source: ILO via Penn World Table (97 countries in 1996) 11

12 Source: WDI via Caselli (2005) 12

13 Source: ILO via Caselli (2005), 41 countries in

14 Development Accounting Y L K = pop pop Y 24 1 α 1 α ha 14

15 L/pop: Open Questions ILO data suspect? 10% of Asian growth, vs. Young s 20% Hours worked per agricultural worker? Alternatively, count home production. 15

16 Point 3: K/Y Richer countries have higher PPP I/Y (corr 0.6). Estimate K/Y using perpetual inventory and an initial stock guess. richer countries have higher K/Y (corr 0.7). 16

17 K/Y 4 3 JPN CHE 2 1 ZAR TZA LSO GNB ZMB NPL COG HND MWI CAF BGD CMR PAK IND MLI TGOGMB KEN NER BENGHA SEN RWA SLE MOZ HTI UGA FIN NOR SGP FRA KOR AUT ESP GER ROM THA GRC BEL SWE ITA ISL CAN DNK POL NLD HUN ISR NZL AUS PRT JAM BRA CYP GBR HKG PER USA MEX ECU GUY DZA PAN MYS IRN VEN ZWE CRI ARG TUR IRL PHL JOR CHN FJI BWA IDN CHL TWN TUN DOM URY COL BRB LKA PNG PRY ZAF TTO MUS BOL SYR GTM SLV EGY log income per worker Source: Penn World Table (97 countries in 1996) 17

18 Development Accounting Y L K = pop pop Y α 1 α ha 18

19 Forces driving K/Y variation 19

20 Forces driving K/Y variation Saving rates? 20

21 60 Investment Rates at Domestic Prices COG TKM 1996 % Investment Rate at Domestic Prices TZA TJK MLI MWI NGA MDG ZMB KEN BEN THA KNA JOR SVK KOR SGP CZE JAM SYR ATG HKG IDN GRD ALB BLZ JPN SWZ VNM EST AZE VCT DMA HUN MDA KGZ UKR BLR LTU TUR BWA ECU LCA PAN CHL TUN LKA PHL PRT AUT NPL MEX SVN ISR NOR UZB HRV LBN IRN BHR NZL BGD ZWE GAB MUS PER QAT GER ARM MKD MAR POL BRA GRC ESP AUS NLD CHE PA K LVA ARG SEN GIN BRBCAN KAZ ISL IRL ITA USA YEM GBR FIN SWE OMN BOL VEN DNKBEL CMR CIV EGY TTO BHS BMU GEO URY FJI BGR SLE LUX 0 1/64 1/32 1/16 1/8 1/4 1/ PPP GDP per worker (U.S. = 1) Source: Penn World Table 21

22 Forces driving K/Y variation Saving rates? NO 22

23 Forces driving K/Y variation Saving rates? NO Investment prices? 23

24 1996 Price of Equipment 8 MKD SYR 4 Relative to the U.S. = /2 TZA NGA MWI MDG MLI BEN ZMB KEN TJK COG YEM GAB CIV EGY UZB FIN CHE SWE JPN UKR HRV MDA RUS EST NZL AUS DNK LBN JOR BMU SEN ATG NOR PRT GRC QATGER FRAIRL GIN ALB LVA LTU SVN BGR SVK HUN GBRISL AUT NLDITA BOL PER ECU THA TUR CZE ESP OMN AZE KAZ BLR POL MEX ROM ISR CAN USA BEL FJI VENURY IRN BWA BRA PAN CHL ARG VNM CMR KNA LCA BHR JAM GEO DMA BHS GRD TUN BRB SGP SLE ARM KGZ MAR MUS TTO KOR HKG PHL IDN VCT SWZ BLZ LKA NPL PAK BGD ZWE LUX 1/4 1/64 1/32 1/16 1/8 1/4 1/ PPP GDP per worker (U.S. = 1) TKM Source: Penn World Table 24

25 Forces driving K/Y variation Saving rates? NO Investment prices? NO 25

26 Forces driving K/Y variation Saving rates? NO Investment prices? NO Consumption prices? 26

27 1996 Price of Consumption 4 Relative to the U.S. = /2 1/4 1/8 TZA MKD CHE SWE JPN BMU NOR FINFRA GER AUT DNK NGA ISLNLD SYR ISR IRL SGP BEL NZL ESP GBR AUS ITA GRC USA CAN ATG PRT KOR HKG YEM SVN BHS URY BRA ARG BHR JAM HRV LCA DMA LBN PER CHL KNA ECU VCT GRD FJI THABLZ VEN PAN JOR MEX TTO TURPOL QAT COG ZMB EST HUN BOL RUS GAB CZE OMN MDG BEN LVA IRN SEN LTU SVK CIV PHL ALB IDN BWA BRB MWI MLI CMR PAK MAR LKA GEO KAZ ROMEGY KEN AZE BGD BGR TUN MUS ARMUZB UKR KGZ BLRSWZ VNM ZWE SLE MDA GIN NPL TJK TKM LUX 1/16 1/64 1/32 1/16 1/8 1/4 1/ PPP GDP per worker (U.S. = 1) Source: Penn World Table 27

28 Forces driving K/Y variation Saving rates? NO Investment prices? NO Consumption prices? YES 28

29 K/Y: Open Questions Why are richer countries better at making K? Just a reflection of h differences? Eaton & Kortum: Quality differences mask import barriers? 29

30 Point 4: MPK Lucas: why doesn t capital flow from rich to poor? Lately it has: S/Y is more correlated with Y/L (0.5) than is I/Y (0.05 at domestic prices). Why doesn t capital flow to equalize MPK s? Caselli & Feyrer: It does! 30

31 Caselli & Feyrer MPK s Naive MPK αy K Corrected MPK αpy Y land rents PK K 31

32 Naive MPK 50% SLV PRY 40% CIV EGY BWA MUS 30% 20% 10% BDI COG ZMB BOL PHL LKA JAM MAR URY ZAF COL ECU TUN CHL TTO VEN JOR MEX PER DZA MYS CRI PAN PRT GRC KOR NZL ESPGBR JPNFIN SWE SGP IRL ISR NLD AUS CAN DNK AUT FRA CHE NOR ITA BEL USA 0% 0 10,000 20,000 30,000 40,000 50,000 60,000 PPP GDP per worker Source: Caselli & Feyrer (2006), 52 countries in

33 50% MPK Corrected for Prices, Land Rents 40% 30% 20% 10% 0% SLV BWA SGP URY MUS ISR KOR IRL USA PHL PERPRY MEXCHL NLD MAR JOR ESP ZAF PRT GBR JPN DNK ITA FIN TUN SWE FRA NOR JAM COL PAN MYS CHE CAN AUT AUS BEL LKA EGY VEN GRC NZL ECU CRI TTO ZMB COG CIV BOL DZA BDI 0 10,000 20,000 30,000 40,000 50,000 60,000 PPP GDP per worker Source: Caselli & Feyrer (2006), 52 countries in

34 MPK: Open Questions Why does K s share rise with development? Caselli & Coleman, Hansen & Prescott No single MPK? Banerjee & Duflo. 34

35 Point 5: Schooling and h Higher attainment in rich countries (corr 0.9). Can estimate h using Mincerian formulation (log of h is linear in schooling). 1 more year of schooling 10% higher h 35

36 Years of Schooling ZAR TZA ZMB COG HND IND KEN LSO GHA PAK UGA TGO CMR MWI CAF GMB BEN BGD HTI RWA SLE SEN NPL NOR USA NZL SWE CAN KOR AUS CHE GER POL FIN ROM ISR DNK CYP IRL GBR BEL NLDJPN HKG HUN PAN ARGGRCBRB TWN ISL PHL FJI AUT PER CHL URY TTO FRA MEX ESP ITA LKA JOR VEN MYS SGP GUY CHN ECU PRY CRIBWA THA ZAF MUS BOL SYR PRT ZWE EGY JAM COL DOM IDN SLV DZA TUR IRN TUNBRA GTM PNG NER MOZ GNB MLI log income per worker Source: Penn World Table and Barro-Lee (97 countries in 1996) 36

37 Development Accounting Y L K = pop pop Y α 1 α h 2 A 37

38 Development Accounting Y L K = pop pop Y α 1 α h A

39 Point 6: MPH Single Mincerian return in all countries? Psacharopoulos & collaborators: higher Mincerian return in poor countries Banerjee & Duflo: when well-measured, similar across countries 39

40 30 Mincerian returns vs. schooling JAM BWA TWN MAR NPL GTM TUN LKA BRA FRA ETH CIV ZAF COL KOR PAN PHL SGP PRY ECU CHL KEN ARG DOM URY IDN VNM HKG KWT GHA SDN PER RUS ISR GBR EST HUN MYS Years of attainment Source: Banerjee and Duflo (2005); 38 countries, various years 40

41 30 Mincerian returns vs. schooling (better data) SDN NPL PAK GTM COL PAN KEN NIC BRA PRY CHN SGP JPN KOR PHL ECU CHL THA IND ZMB BOL ZAF DOM VEN MYS URYFRA ARG GHA PRTCRI SLVEGY PER FIN IDN LKA ESP AUT GRC GERCHE AUS UGA CMR HKG NLD GBR POL ZWE CYP HUN DNK USA CAN NOR SWE ITA Years of attainment Source: Banerjee and Duflo (2005); 59 countries, various years 41

42 Limits to the Mincerian Approach Manuelli & Seshadri / Erosa, Koreshkova, Restuccia: ln h = f( s, y, a ), y = inputs, a = ability i i i i dln h f f y f a = + + ds s y s a s i i i i i i i i i But x-country = x-individual? 42

43 x-country vs. x-individual Country TFP differences x-country y s i i x-individual y s i i Even more so with public schools? ai ai Yet perhaps x-country x-individual. s s i i 43

44 h: Open Questions Production function for h? Accumulation at home, on the job? Externalities? Sources of h variation across countries? 44

45 Point 7: Immigrants and h Immigrants provide useful info on h. Different source countries, one market. Hendricks: U.S. Census data for

46 160% Immigrants vs. Natives in the U.S. Earnings Relative to Natives (same age, education, sex) 140% 120% 100% 80% 60% 40% 20% 0% ZAF YUG TUR PRT SYR KEN LKA CZE HUN ARG GRC INDROMIDN TWN EGY URY POL BRA MYS BRB JAM PAN IRN JOR SOV VEN TTO GUY CHL IRQ DMA PAK THA ECUCOL CRI BLZ FJI CHN BGD DOM PHL BOL PER GTM KORMEX ETH GHA HTI HNDSLV NGA NIC 45º JPN DNK GBR NZL AUT IRL ISR ESP HKG PRI SWE NORAUS CHE FRA BEL CAN GER ITA NLD 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Real GDP per worker relative to the U.S. in 1990 Source: Hendricks (2002); 74 countries in

47 Source: Hendricks (2002) 47

48 Development Accounting Y L K = pop pop Y α 1 α h 2 4 A 48

49 Development Accounting Y L K = pop pop Y α 1 α h A

50 Point 8: Technology and A Same technology in all countries? TFP gaps exist even within countries. Firms may have to invest in adoption. Why can t FDI eliminate any differences? See Chad Jones recent paper. 50

51 Source: Parente and Prescott (2005) 51

52 Technology and A: Open Questions Data on barriers and investments? Channels for international diffusion? Right model? Parente & Prescott Howitt Klenow & Rodriguez-Clare 52

53 Points 9 & 10: Misallocation and A Perhaps less efficient allocation of K and L within poor countries. Maybe no higher average MPK, but more dispersion of MPK s within poor countries. Parente & Prescott Schmitz Restuccia & Rogerson 53

54 Point 9: Agriculture and A Within agriculture, K and land less efficiently allocated in poor countries? Between agriculture and rest of economy, L less efficiently allocated in poor countries? Restuccia, Yang, & Zhu Gollin, Parente & Rogerson Caselli Handbook 54

55 Source: Caselli (2005) 55

56 Source: Caselli (2005) 56

57 Productivity in Agriculture Ag. Non-ag. S.D. of log Y/L th /10 th Source: Caselli (2005), 80 countries in

58 Counterfactual Calculation S.D. 90th/10th Actual log Y/L With U.S. emp. shares Source: Caselli (2005), 80 countries in

59 Ag. vs. Non-ag.: Open Questions Model of transition with Y/L gaps? Lucas, Hansen & Prescott Gaps reflect h differences? Caselli & Coleman, Jeong & Kim Gaps reflect home production? Parente, Rogerson & Wright 59

60 Point 10: Manufacturing and A Big TFP gaps across plants within industries. TFP gaps may imply MPK and MPL gaps. If so, large potential gains from reallocation. 60

61 TFP Dispersion within 4-digit industries 90 th /10 th 75 th /25 th U.S China India Source: Syverson (2004) for the U.S., Hsieh and Klenow (2006) for China and India. 61

62 Potential A Gains from Reallocation Melitz model (monopolistic competition between firms with different productivity). Reallocate K and L to equalize MPK and MPL across plants. Result: China and India could double A. Source: Hsieh and Klenow (2006) 62

63 Mfg. Misallocation: Open Questions Right model to gauge gaps and gains? Gaps tied to observable distortions? More measurement error in poor countries? 63

64 Recap of Development Accounting Y L K 1 α = pop pop Y α h A

65 Plenty of Open Questions Quality and Variety Magnitude and sources of h differences Externalities Extent and sources of misallocation 65

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