Income distribution

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Group work with Deepika Gupta & Deepa Somdas

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Income distribution

  1. 1. INCOME DISTRIBUTIONSUBMITTED BY:DEEPA.SDEEPIKA GUPTAGARGI GHOSH
  2. 2. STRUCTURE OF PRESENTATION MEASUREMENT OF INEQUALITY Lorenz curve & Gini’s coefficient IMPACT OF DEVELOPMENT ON INCOME DISTRIBUTION A note on U hypothesis Economic growth and income inequality Economic development, Urban Inequality, poverty and development underemployment& Income inequality IMPACT OF INCOME DISTRIBUTION ON DEVELOPMENT Inequality, Political instability and Distributive politics and economic growth Investment CASE STUDIES – Taiwan, Brazil
  3. 3. LORENZ CURVE AND GINI COEFFICIENT Concentration area (area of inequality •The % of households is plotted on the x-axis, the percentage of income on the y-axis. •Complete equality occurs if a % of household received a % of income. •Perfect inequality represents the case where one household has 100% of the country’s income. •Gini coefficient- •Ratio of concentration area to the total area under the line of equality. •Ranges from 0 to 1. • larger the Gini’s coeff., greater the inequality
  4. 4. ECONOMIC GROWTH AND INCOME INEQUALITY. The central theme- Character and causes of long term changes in personal distribution of income. • Incomes are grouped should be family expenditure units-adjusted on the basis of family members • Distribution should be covered all units of a country-LIG,HIG,MIG • Units should segregate ,Income earners are still in the learning or retired stages. • Income defined as national income in this country. • Units should be grouped by secular levels of income, free of transient disturbances.
  5. 5. TRENDS IN INEQUALITY : OBSERVATION 1 • Data before direct taxes show greater inequality. 1 • Addition of Govt. reliefs and direct taxes 2 • Reduction in inequality. • (Data after taxation should only be considered 3 for calculating inequality)
  6. 6. TRENDS IN INEQUALITY : OBSERVATION 2 Stability or reduction in the inequality of the % shares was accompanied by significant rises in real income per capita CONSTANT RATE OF HIGHER RATE OF INCREASE INCREASE FOR LIG •Rise in per capita •Rise in per capita income income •No change in •Decrease in inequality. inequality.
  7. 7. TRENDS IN INEQUALITY : OBSERVATION 3 With technological advancements income is less prone to transient disturbances. DISTRIBUTION BY DISTRIBUTION BY LONG- ANNUAL INCOME TERM AVERAGE SHOWS MORE INCOME SHOWS LESS INEQUALITY. INEQUALITY.
  8. 8. EXPLANATION OF TRENDS • Lower average per capita income in rural population(than urban) 1 • Lower inequality. • Urbanization leads to rural urban shift 2 • Increasing share of unequal URBAN POPULATION ECONOMIC PEAK component in economy. 3 1. Adaptation of the children of rural- urban migrants to city’s economic IMMIGRANTS life 2. Political power of urban lower LOW INCOME GROUP DOWNWARD TREND income groups increase
  9. 9. OTHER TRENDS IN INCOME INEQUALITY INITIAL PHASE NEW WIDENING OF ECONOMIC INDUSTRIAL INEQUALITY U GROWTH SETUP C U R STABILIZED V LATER PHASE INDUSTRIAL E GROWTH DECREASING OF ECONOMIC +PROGRESSIVE INEQUALITY GROWTH TAXES
  10. 10. Inequality,Poverty,and DevelopmentThe purpose is to explore the relationship between the distribution ofincome and the process of development on the basis of cross country dataon income inequality.SAMPLE60 countries 40- developing 14-developed 6-socialistKuznetss Hypothesis: The U shaped curve.
  11. 11. Inferences • Non linear relationship between income inequality & development. 1 • Turning point is different for different income groups of an economy 2 • Nature of U-curve is different for the entire sample and for only developing countries. 3 • Dominancy of middle income group dictates the nature of U-curve which makes its long term relevancy 3 questionable..
  12. 12. GROWTH AND INCOME DISTRIBUTION RAISED INEQUALITY IN REDUCED INEQUALITY LOW INCOME IN HIGH INCOME COUNTRIES GROWTH COUNTRIES KUZNETS CURVE HAS BEEN SUPPORTED BY PAUKERT(1973), CLINE(1975), AHLUWALIA(1976), AND KYN(1987) EMERGES KUZNETS The study of high and low GREATER CURVE income countries to EQUALITY IN determine the effect of EARLY STAGES OF growth on inequality showed LDC DEVELOPMENT that inequality increases with growth as frequently in low income countries as in high income countries
  13. 13. U HYPOTHESIS RELATING INCOME INEQUALITY AND ECONOMIC DEVELOPMENT: DIFFERENT INCOME DISTRIBUTIONS SECTOR 1 SECTOR 2 ECONOMY KUZNTETS U CURVE Suppose W1 , W2 - population shares of two sectors Y1 , Y2 - log mean σ12 , σ22- log variances of income in the two sectors. W1 + W 2 = 1 Overall log variance : Overall log mean income : σ2= W1σ12 + W2 σ22 + W1(Y1-Y)2 + W2(Y2-Y)2 Y= W1Y1 + W2Y2 Log variance is a measure of income inequality.
  14. 14. Assuming that population share in sector 1 is increasing then from above Overall log mean income : equations : Since A<0, the parabolic curve σ2 = AW1 2+ BW1+ C will open downward. With increase in W1, inequality first Where A= -(Y1-Y2)2 increases, reaches a maximum B=(σ12-σ22) + (Y1-Y2)2 and then decreases. Thus U C=σ22 hypothesis is derived. Since W1 ranges from 0 to 1, σ2 is maximum when W=(σ12-σ22) /2 (Y1-Y2)2 +1/2Thus when log variances are more equal and logmean incomes are more different, σ2 is maximumwhen w is ½. INEQUALITY CURVE IN US
  15. 15. ECONOMIC DEVELOPMENT, URBAN UNDEREMPOYMENT AND INCOME INEQUALITY ECONOMIC DEVELOPMENT SHIFT OF LABOR FROM AGRICULTURE TO NON AGRICULTURE INCOME INEQUALITY INCREASES RKF MODEL- RURAL URBAN INCOME ROBINSON, DIFFERENCE KNIGHT,AND CONSTANT ASSUMPTIONS FIELDS GAVE • CHANGE IN BASED ON LESS EXPLANATION SHARE OF DEVELOPED FOR INCOME AGRICULTURAL COUNTRIES INEQUALITY IN POPULATION 1976 • THUS DEFINING INEQUALITY BY U CURVE
  16. 16. ECONOMIC DEVELOPMENT, URBAN UNDEREMPOYMENT AND INCOME INEQUALITY SCENARIO OF LDC IN 1960 HIGHER WAGES •RURAL SECTOR •UNDER DEVELOPMENT •URBAN SECTOR •UNEMPLOYMENT HARRIS –TODARO LOWER WAGES MODEL (1970) The Harris-Todaro model (HT) demonstrates that, in certain parametric ranges, an increase in urban employment may actually result in higher levels of urban unemployment and even reduced national product . In LDC upon migration some rural migrants immediately obtain jobs in formal sector while others get employed in small businesses and self employment i.e. informal sector.
  17. 17. ECONOMIC DEVELOPMENT, URBAN UNDEREMPOYMENT AND INCOME INEQUALITY The workers in formal sector earns more than informal sector, while there is mobility over time from informal to formal sector.  This share of urban labour force in LDC cities engaged in informal sector ranges from 19% to 69% with a mean of 41%. Log variance which is a measure URBAN of inequality will form an inverted U FORMAL SECTOR curve. WORKERS RURAL URBAN (AGRICULTU INFORMAL  When urbanization is low , and the RAL) WORKERS SECTOR WORKERS pressure of land keeps rural incomes are low , inequality will be more and after urbanization it will CLASSES OF WAGE decrease. EARNERS INEQUALTY DEFINED BY THESE GROUPS
  18. 18. EMPIRICAL ANALYSIS OF MODEL Two predictions of informal sector made from the results of labor market behavior: The informal sector share of the The INFORMAL sector share of total labour force (1-Na –Nm)/(1-Na) labour force or underemployment rate decreases with level of urbanization 1-Na –Nm follow an inverted U curve with urbanization. Let URB : 1-Na The data for URB and UNDER has been UNDER : 1-Na –Nm . collected by PREALC covering 17 Latin American countries for the years 1950, SHARE : (1-Na –Nm)/(1-Na) 1960,1970 and 1980. All these countries were lower middle income or upper middle income. Variable Mean Std Minim Maxim dev. um um  Peak U in the underemployment rate URB 50.9 16.6 18.9 84.4 occurs when 61% of labour force has left UNDER 11.3 3.4 4.5 20.4 the primary sector. SHARE 23.8 8.4 10.9 44.0
  19. 19. CONCLUSIONS According to FIELDS inequality during the growth process initially decreases and then increases depicting a U curve in contrast to inverted U curve described by inequality indices. Fields (1987) offers the following explanation:  at the initial stages of the growth process, inequality decreases because the less “elitarian” position of the rich acts to reduce inequality; in the last phases, inequality increases because of the increased “isolation” of the poor. Fields (1993) defines Elitism of the Rich (ER) and Isolation of the Poor (IP) as functions of gap and numerical inequality. But Robert Moore argued against Fields proposal. University of Chicago, gave human capital based explanation where inequality among identically endowed individuals is generated over time by differences in market luck which parents pass to their children by investing in the children’s human capital. Thus market luck is the driving force behind inverted U.
  20. 20. THE INFORMAL SECTOR, INTRAURBAN INEQUALITY AND THE INVERTED U INEQUALITY ALSO FOLLOWS INVERTED U labor market equilibrium INFORMAL SECTOR SHARE OF condition : URBAN LABOUR FORCE FALLS AND INFORMAL SECTOR SHARE OF TOTAL LABOUR FORCE FOLLOWS AN INVERTED U expected utility from working in the agricultural sector = RAUCH URBANIZATION INCREASES MODEL expected utility from working in the urban sector. As urbanization increases, land-labor ratio in agriculture rises, increasing the marginal product of labor in agriculture and the agriculture wage. This will be consistent with labor market equilibrium only if the average log wage in urban sector increases. This is only possible if SHARE falls.
  21. 21. THE INFORMAL SECTOR, INTRAURBAN INEQUALITY AND THE INVERTED U Inequality within agriculture is zero but inequality within urban sector is possible because of the earnings of formal and informal sector. The change in overall inequality will follow two trends: In the early phase, SHARE will be more and the overall inequality will increase. Once SHARE shrinks below one-half , the further decline in SHARE as urbanization increases reduces inequality with in urban sector , tending to decrease overall inequality. Thus the log variance measure of inequality can not decline in Rauch model until after informal share of total labor force declines.
  22. 22. Distributive politics and Economic growth: Regression analysis DISTRIBUTIONAL INITIAL PER INDICATORS OF CAPITA INCOME INCOME AIM HERE IS TO VERIFY IF INITIAL INEQUALITY IS A STATISTICALLY SIGNIFICANT INDICATOR OF LONG TERM GROWTH OF A COUNTRYDISTRIBUTIONAL PRIMARYINDICATORS OF SCHOOL LAND ENROLLMENT INDICTORS OF WEALTH DISTRIBUTION REGRESSION EQUATIONS EMPLOYMENTI=  + βE +є…….simple regression equationI=  + βE + γY +є…multiple regression equation EDUCATION
  23. 23. Distributive politics and Economic growth: Regression analysis Table : Regression data HIGHEST QUALITY SAMPLE HIGHEST QUALITY LARGEST POSSIBLE 1960 - 85 SAMPLE SAMPLE 1970 -85 1970 - 85 OLS TLS OLS OLS CONSTANT 3.60 8.66 4.56 2.80 (2.66) (3.33) GDP -0.44 -0.52 -0.29 -0.27 (-3.28) (-3.72) PRIM 3.26 2.85 3.28 3.79 (3.38) (2.43) GINI -5.70 -15.98 -9.71 -7.95 (-5.70) (-3.21) GINI LAND - - - - R2 0.28 0.27 .28 0.23HERE, DEPENDENT VARIALBLE IS PER CAPITA GROWTH RATE, WHILE INDEPENDENT VARIABLES ARE GDP, PRIM, GINI & GINI LAND RESULTS SHOW THAT  GROWTH IS NEGETIVELY CORRELATED WITH INCOME INEQUALITY AND LAND DISTRIBUTION  POSITIVELY CORRELATED WITH PRIMARY SCHOOL ENROLLMENT
  24. 24. Income Distribution, Political Instability and Investment SOCIAL DISCONTENT DOES INCOME INEQULITY INCREASE POLITICAL INSTABILITY? INCOME POLICY INEQUALITY UNCERTAINITY DOES POLITICAL INSTABILITY REDUCE INVESTMENT? LOW POLITICAL INVESTMENT IN STABILITY CHANNEL OF EFFECT? MEASURE OF POLITICAL INSTABILITY LOW PRODUCTIVITY REGRESSION MODEL HIGH UNCERTAINITY HIGH TAXATION ANALYSIS POLITICAL INSTABILITY
  25. 25. Income Distribution, Political Instability and Investment MEASURE OF POLITICAL STABILITY INV (1) SPI (1) INV(2) SPI (2) SPI = 1.39ASSASS + 1.21DEATH CONST 27.36 37.43 27.85 32.44 +7.58SCOUP + 7.23UCOUP – 5.45DEM GDP .07 0.06 SPI -0.05 -0.57 PPPI -0.14 -0.15 REGRESSION MODEL PPPIDE .04 0.05 INV = α0 + α1 SPI + α2 GDP + α3 PRIM -0.23 -0.32 PPPIDE + α4 PPPI +ε1 MIDCLA -1.01 -0.68 SPI = β0 + β1 PRIM + β2 INV + β3 SS MIDCLASS +ε2 INV 0.72 0.66 LAAM 9.89 GDP – GROSS DOMESTIC PRODUCT DEATH-NO OF PEOPLE KILLED IN MASS VIOLENCE ASIA 2.59 SCOUP-NO OF SUCCESFUL COUP UCOPU- NO OF UNSUCCESSFUL COUP AFRICA -3.17 DEM-DUMMY VARIABLE SPI-SOCIO –POLITICAL INSTABILITY INDEX PPPIDE-DEVIATION OF PPP VALUE FOR INVESTMENT DEFLATOR Table : Regression data PPPI – PPP VALUE FOR INVESTMENT DEFLATOR
  26. 26. CASE STUDY : TAIWAN • SUPERIOR PHYSICAL & DEVELOPING INDUSTRY INSTITUTIONAL THROUGH AGRICULTURE •LABOUR ALLOCATION TRANSITION INTO INFRASTURCTURE – DEVELOPING TO INDUSTRY AN INDUSTRIALPRIMARILY • JAPANESE OWNERSHIP AGRICULTURE THROUGH • SAVINGS BASE FORM ECONOMYAGRAGARIAN OF MANUFACTURING INDUSTRY CAPITAL TO INDUSTRYECONOMY UNITS120100 96 91 80 68 79 60 40 20 32 21 9 0 4 1920 AD 1940AD 1960AD 1980AD • LAND REFORMS RETROCESSION •PROCESSING INDUSTRIES FROM JAPAN - • HIGH INTEREST RATES FOR AGRICULTURE 1945 SAVINGS •IMPORT RESTRICTIONS INDUSTRY • RURAL AGRO
  27. 27. CASE STUDY : TAIWAN –overall FID INCOME DISTRIBUTION 1953 INCOME DISTRIBUTION 1959 120 120CUMULATIVE INCOME 100 100 MEAN INCOME PER 80 HOUSE HOLD -22681 80 60 GINI COEFF - .558 60 40 40 20 20 0 0 0 20 40 60 80 100 0 20 40 60 80 100 CUMULATIVE HOUSEHOLDS MEAN INCOME PER INCOME DISTRIBUTION 1964 HOUSE HOLD -31814 120 GINI COEFF - .44CUMULATIVE INCOME 100 80 60 40 MEAN INCOME PER HOUSE HOLD -32450 20 GINI COEFF - .328 0 0 20 40 60 80 100 Currency in N.T. Dollars CUMULATIVE HOUSEHOLDS
  28. 28. CASE STUDY : TAIWAN –Land Reforms PRE- REFORM REFORMS POST REFORM UNEQUAL REDISTRIBUTION OF LAND NATIONAL WEALTH DISTRIBUTION REDUCING SALE OF LAND RENTS PUBLIC LAND FIERCE COMPETITION LOWER RENT OF SCARCE LAND TO LAND – LOW TILLER LEASE PERIOD LAND OWNERSHIP TO HIGH RENT FARMERS VALUE ITEM REDUCTION SALE OF LAND TO TILLER TOTAL IN FARM PUBLIC LAND PROGRAMME REDISTRIBUTI RENTS ON AREA AFFECTED 256.9 71.7 193.6 215.2 FARM HOUSEHOLD AFFECTED 302.3 139.7 194.9 334.3 PERCENTAGE OF CULTIVATED 29.2 8.1 16.4 24.6 LAND AFFECTED PERCENTAGE OF FARM HH 43.3 20 27.9 47.9 AFFECTED
  29. 29. CASE STUDY : TAIWAN –other developments REORGANISATION OF INSTITUTIONAL INFRASTRUCTURE AGRICULTURAL DEVELOPMENT DURING 1950s DISTRIBUTION OF ASSETS AND INDUSTRIAL GROWTH
  30. 30. CASE STUDY : Brazil INCOME DISTRIBUTION INCOME DISTRIBUTION 100 100 90 90CUMULATIVE INCOME CUMULATIV EINCOME 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 0 0 20 40 60 80 100 0 20 40 60 80 100 CUMULATIVE HOUSEHOLDS CUMULATIVE HOUSEHOLDS MEAN PER CAPITA INCOME – 513 US$/YR MEAN PER CAPITA INCOME – 679 US$/YR GINI COEFF - .59 GINI COEFF - .63 DATA ADJUSTMENTS : • NORMALISED ON NO.OF FAMILY MEMBERS • INCORPORATING NON-MONETORY INCOME
  31. 31. CASE STUDY : Brazil • GREATER SCOPE TO STABILIZATION MARKET FORCES • INCREASE IN GDP AFFECT ONLY • FREER REIN TO PRIVATE HIGHER INCOME GROUP SECTOR • LEADS TO INEQUALITY0.7 800 0.59 0.63 0.6 7000.6 0.51 679 6000.5 •POVERTY A RESULT OF LOW RURAL 5000.4 530 513 PRODUCTIVITY 4000.3 450 • LACK OF GOVT 300 POLICIES0.2 2000.1 100 0 0 MILITARY1960AD 1963 AD GOVERNMENT 1967 AD 1970 AD • GOVT FISCAL POLICIES • POLICIES DECLINE • UNEQUAL ALLOCATION OF • TAX RELAXATIONS NOMINAL WAGES INFRASTRUCTURE • REDUCED REVENUE GINNIS COEFF •DECLINE OF REAL • INEFFECTIVE POLICIES e.g. MINIMUM WAGES BY 20% education, labour allocation MEAN INCOME DUE TO INFLATION etc
  32. 32. THANK YOU

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