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Why are we here?. The planet Earth in the darkness of the night * * Image source: NASA (http://antwrp.gsfc.nasa.gov/apod/ap001127.html)

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Presentation on theme: "Why are we here?. The planet Earth in the darkness of the night * * Image source: NASA (http://antwrp.gsfc.nasa.gov/apod/ap001127.html)"— Presentation transcript:

1 Why are we here?

2 The planet Earth in the darkness of the night * * Image source: NASA (http://antwrp.gsfc.nasa.gov/apod/ap001127.html)

3 Measuring the state of economic development Economic Development = Quality of Life

4 Life has multiple dimensions Development Diamond –Life expectancy at birth –Gross primary (secondary) education enrollment –Access to safe water –GNP per capita

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7 Economic development = quality of life

8 Measuring economic development Country’s income –Production generates income –GDP versus GNP Average standard of living –GNP (GDP) per capita –Purchasing Price Parity (PPP)

9 Comparing Incomes Across Countries PPP GDP per capita as a measure of the standard of living. Standard of living: Income/Prices Read GDP as a measure of income Adjustment for the cost of living: difference in prices Purchasing Price Parity – adjustment for the cost of living. Prices differ across countries creating differences in purchasing power of money. For instance, 1000 USD buys more (today, probably less) in Moscow than in Atlanta. Constructing a cost of living index Fixing a market basket Tracking that market basket through different locations

10 Economic growth = GDP per capita (or per worker) growth Historical Context* –1580 – 1820: The Netherlands 0.2% –1820 – 1890: UK 1.2% –1890 – 1989: USA 2.2% –1990 – 2000: USA 1.93% (GDP per capita) –1994 – 2000: USA 2.7% (GDP per capita) * Growth in GDP per worker hour

11 High-income economies are those in which 2001 GNI per capita was $9,206 or more Middle-income economies are those in which 2001 GNI per capita was between $745 and $9,205 The World Economy

12 Less than 1710 1710-3560 3560-6250 6250-15110 Over 15110 No data available GNI per capita in 2001, PPP method (current international $) World Bank Development Indicators for 2003

13 Real GDP growth rate in 2000 World Bank Development Indicators 2003 Less than –0.6 -0.6 <. < 0.8 0.8 < / <2.1 2.1 <. < 4.2 Over 4.2 No data available

14 Economic Theory of Growth Resource endowment –Land –Natural Resources (typically part of Land) –Physical Capital –Human Capital –Entrepreneurship Institutional Support –Political system and its stability –Legal system –Property rights –Tax system Country specific factors –Business culture

15 LAND Malthusian View of Economic Growth –Land is fixed –Population growth is positive –Ratio of Land to Workers continuously declines Q = f ( Labor, Land) –Land is fixed –Diminishing marginal return to labor As labor increases, additional unit of labor contributes less to the output than the previous unit of labor If  <1 labor exhibits diminishing marginal property The ratio of output to labor (GDP per worker) decreases as labor increases Technological progress is ignored, but the technological progress can enhance the productivity of labor. Recall that technology in this context refers to production methods.

16 Natural Resources Typically defined together with Land In many ways similar properties to those of Land

17 Physical Capital Can make labor more productive Assume Labor = 101; Land = 101  And the production function is: If Capital is zero  Q = 16 if Capital is 2  Q = 19.7 If Capital is 10  Q = 32 If Capital is 101  Q = 64 This example implies that economic growth can be achieved by simply accumulating physical capital

18 From Savings to Investment: The Harrod–Domar Model of Economic Growth What is being saved today can be used productively tomorrow Output produced can either be consumer or saved: Y = C + S Savings translate into investment S = I  Y = C + I

19 Capital Evolution Equation modeling changes in the capital stock overtime Addition to capital stock at time period t –Investment: I t Subtraction from capital stock at time period t –Depreciation:  K t –Where  represents the rate of depreciation of the capital stock and K the level of capital stock K t+1 = K t –  K t + I t Savings Rate: s = S/Y = I/Y Capital to output ratio: K/Y =  Y t+1  = Y t  –   Y t + s Y t

20 Harrod-Domar Equation Importance of savings to economic growth Importance of capital productivity to economic growth

21 Importance of Capital Formation The Marshal Plan for reconstruction of Europe and Japan The Soviet experience The US in the 1990’s –Not domestic but foreign savings! –Investment growth lead the economic boom of the 1990’s (BEA website for stats)

22 Incorporating population growth Population evolution: P t+1 = P t (1 + n ), where n represents population growth Lower case letters refer to per capita values: k t = K t /P t ; y t = Y t /P t Per capita GDP growth (g’): A more intuitive expression is: g’ ~ s/  –  – n Long-term growth is driven by capital productivity (  ) and the savings rate (s).

23 Assume: Capital stock = 10,000 Output = 2,000  = 5 % What should the savings rate be to ensure the long-term growth of 5%? What should the savings rate be if the productivity of capital improves, and the 10000 capital stock results in the production of 4000 units of output? What if population growth of 5% were introduced in part 1?

24 Weaknesses of the model Savings rate is exogenous –Subsistence consumption makes savings a function of income Capital to output ratio is exogenous –In the H-D model it is assumed to be driven mainly by technological progress –However,  can be impacted by relative endowments of resources. If labor is scarce then wage rate increases relative to the cost of capital, and as a result  increases Population growth is exogenous –Population growth is likely to depend on the level of economic development Opportunity cost of time Retirement provisions

25 The Solow Model Allows to make  endogenous by introducing the production function with input substitutability and diminishing marginal productivity Capital Evolution Equation: K t+1 = K t –  K t + s Y t Note, no more  Adjusting by population growth: k t+1 (1+n) = (1 –  ) k t + s y t Note: y t = f ( k t ) (1-  )k+sy (1+n)k

26 Steady State Capital per capita remains constant over time Achieved when: k / f(k) = s / (n +  ) –Savings increase k/y ratio thereby increasing y –Depreciation reduces k/y ration thereby decreasing y –Population growth: Lowers the ratio of k/y, thereby reducing y Increases total income growth ( Y ) and creates long-term growth in Y equal to population growth (steady state Solow model and the post war Europe

27 Assume: Y = L^(1/3) K^(2/3) s = 10%  n = 0 What is the steady state level of capital per capita? What is the level of output per capita? What if n is set to 5%?

28 Convergence I Growth Neutrality (H-D) –Constant returns to capital Unconditional convergence (S-G): convergence to the same k* –Baumol’s 1986 study 16 wealthy countries Ln(1979)-ln(1870) =  ln(1870)   The study showed complete convergence: almost all of the initial gap in GDP per capita is closed Problems: –Too few countries –All countries selected are wealthy in 1979, hence have converged or stayed wealthy –De Long’s 1988 adjustment Seven more countries included The included nations appear similar to the original 16 countries based on 1870’s characteristics  is indistinguishable from zero –Barro 1991 large set of countries over a short time period no correlation between average per capita growth and the starting GDP level.

29 Convergence II Conditional Convergence (S-G) –Country specific parameters Savings rate; population growth; state of technology Different steady-states: no unconditional convergence –Technology is the only source of long-term growth Assuming that technological spread is the same across the world: differences in parameters of the model lead to convergence in growth rates –Mankiw, Romer and Weil (1992) Ln y = A +  ln s +  ln n +  ln (  S and n explain almost 60% of the variation in GDPs across countries

30 Human capital endogeneity of growth Y t = K t   t  Two forms of investment –Into physical capital:  K = sY k t+1 = k t (1-  )+sy t   k = s (h/k)^(1-  ) –  –Into human capital:  H = qY h t+1 = h t + qy t   h = q (h/k)^(-  ) –  y =  k + (1-  )  h Endogenous growth Convergence in growth rates and not in per capita values Formation of human capital –Education –Industry composition –Direct foreign investment Lack of low-skilled labor in the production function Input prices –Brain drain

31 Technological Progress: long-term growth in the Solow Model Productivity of labor “effective” labor: L = E P –P – population –E – productivity coefficient –Productivity growth: E t+1 = (1 +  ) E t –Y t = L t 1-  K t     y t = E t 1-   k t  –Productivity growth  long term growth in output per capita

32 Technological Progress: endogenous explanation Romer, 1990 Human capital –Productive resource: uH –Investment into research: (1-u)H Investment into research at the expense of current output Across time growth variation

33 Technological Progress: externality approach Output of each firm is impacted by investment done by other firms –“network” externality Y t =E t K t  L t 1-  –Although K exhibits diminishing returns, it is possible to have an increasing return given E’s dependency on K-average –External effects and central planning –Complementarities Multiple equilibrium paths: depending on the expectations of the firms

34 Technological Progress: Growth in Total Factor Productivity  Y/Y t = (MPK  K t )/Y t + (MPL  L t )/Y t + TFPG

35 Income Distribution, Poverty and Growth Distribution of Income –Current –Life-time Older versus younger generations –Functional (source) characteristics of the distribution Income and the Utility Function Distribution of Consumption Spending Distribution of Wealth

36 Measuring income inequality Basis for inequality measures –Anonymity –Scale –Relative income –Changes in the distribution, i.e. the Dalton principle I(x1, x2, x3, x4)<I(x1, x2-e, x3+e, x4) Regressive versus progressive

37 Visualizing Inequality: The Lorenz Curve 100% Population share Income share 25%50%75%

38 GINI Coefficient Differences approach: |I i – I k | Gini Coefficient and the Lorenz Curve

39 Income Distribution and Development State of development of the banking sector and the availability of loanable funds Income distribution and the state of economic development –The Inverted U-hypothesis Poverty –Unemployment due to “subsistence” wages –Urban Poverty

40 Correcting for Income Inequality through Taxation Progressive Taxation –Income Taxation USA case Russian Case Wage Regulations


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