U6602: Economic development for international affairs



Malgosia Madajewicz

U6602 Economic Development for International Affairs

Spring 2001

Part II: Aggregate perspectives: growth and structural change

A. Growth

1. Introduction: some empirical patterns

Country Time period Average annual growth rate of real per-capita income

Netherlands 1580-1820 0.2%

U.K. 1820-1890 1.2%

U.S.A. 1890-1989 2.2%

Note: at a 2% rate of growth, per-capita income doubles in 35 years

• per capita GDP in OECD countries 1870-1978 increased sevenfold (on ave for all OECD); such an increase cannot but transform societies completely

• takeoff into sustained growth (W. W. Rostow) has occurred only in the last century, and only in a handful of countries; in most developing countries, process of growth began only post-WWII and even since then has been quite erratic

• between 1960-1985 annual growth rate of real per-capita income averaged 1.9%, but there were tremendous disparities in the growth experiences of individual nations:

- E.Asian and S.E. Asian economies, excluding China, averaged 5.5% per year between 1965-1990

- China averaged 8.2% between 1980-1993

- average per-capita income in Latin America fell by 11% during the 1980s

- similar declines in Africa

(show table 3.2 from Ray)

• the implications of these stark differences in growth performance are tremendous, and raise the basic question: what explains these differences?

• Robert Lucas: “Rates of growth of real per-capita income are … diverse even over sustained periods … Indian incomes will double every 50 years, Korean every 10. An Indian will, on average, be twice as well off as his grandfather; a Korean 32 times … I do not see how one can look at figures like these without seeing them as representing possibilities. Is there some action a govt of India could take that would lead the Indian economy to grow like Indonesia’s or Egypt’s? If so, what exactly? If not, what is it about the “nature of India” that makes it so?

• economic models of growth attempt to provide a framework for thinking about this question; the models are highly aggregative (in some ways, simplistic?), reflecting the methodological bias of economics towards beginning with abstract simplified models and introducing complications as necessary

2. Review of basic concepts

a. macroeconomic accounting identities

• at simplest level economic growth is the result of abstention from current consumption. To understand this, need to understand macroeconomic balance.

(figure 3.1 from Ray as a macroeconomic balance story – inflows = outflows)

• macroeconomic balance implies the following accounting identities (assuming a closed economy and ignoring government spending):

the first equation must be true as a matter of accounting – national income is divided between C and S

Y(t) = C(t) + S(t)

Value of produced output must match goods produced for C and I

Y(t) = C(t) + I(t)

But what is income – consumption?

S(t) = I(t)

where:

- Y(t) = total output (income) of the economy at time t

- C(t) = total consumption (expenditure on consumption goods) at time t

- S(t) = total savings at time t

- I(t) = total investment (expenditure on capital goods) at time t

• this is a static equilibrium at each point in time. We’re interested in the dynamic story – how an economy changes (grows) from period to period.

• to describe the dynamic evolution of the economy, we also need to track K(t), the capital stock of the economy at time t, which evolves according to:

K(t + 1) = (1-() K(t) + I(t)

• the evolution of the economy can then be schematically represented as:

[pic]

• the rate of growth of aggregate output, i.e., [pic], therefore depends on:

- how the capital stock K(t) is translated into output, Y(t) (production function)

- how income Y(t) is allocated between C(t) and S(t) (household or individual utility maximization)

- how S(t) is translated into I(t) (firm profit maximization)

• for most purposes we will be interested in the rate of growth of per-capita output or income, and to think about that we also need to consider the rate at which the population is growing. Let N(t) be the size of the population in the country at time t. Let [pic] denote the population growth rate. Then, the rate of growth of per-capita output or income, i.e., [pic], will be given by:

[pic]

Note: [pic] for small changes.

b. Production functions

• to capture how capital and labor are combined to produce output, we need the concept of a production function (how much output will increase if number of spindles or of workers goes up given amount). Production functions are mathematical relationships characterized by the assumptions we make about what the relevant inputs are, the degree of substitutability across inputs and returns to scale. Can be defined for given output or at more aggregate level, firm or country. Two simple production functions that have been widely used in the growth literature are the fixed-coefficients (also called the Leontief) production function, and the neoclassical production function

• the fixed-coefficients production function is represented in the following way:

[pic]

where L is the amount of labor available in the economy. At the efficient amount of K and L, Y=aK=bL, so K/L=b/a (i.e. capital labor ratio is constant), a is the inverse of the capital-output ratio (i.e., the number of units of capital required to make 1 unit of output), and b is the inverse of the labor-output ratio. Note that if we assume a fixed-coefficients production function we are assuming:

- no substitutability across inputs (factors of production) – e.g. person mowing a lawn, however is it still the appropriate representation over the long term (e.g. size of lawn mower)?

- capital-output ratio fixed

- constant returns to scale

• under the neoclassical production function output is given by [pic], where the function F(.) is characterized by:

- diminishing marginal returns to both capital and labor, which implies, in particular, that the capital-output ratio increases as the capital-labor ratio increases

- the possibility of factor substitution

- e.g. Cobb-Douglas: [pic]

- returns to scale depend on the assumptions we make regarding ( and (; for instance:

< 1 decreasing returns to scale

( + ( = 1 constant returns to scale

> 1 increasing returns to scale

3. Harrod-Domar growth model

• developed independently in 1940s by Roy Harrod (England) and Evsey Domar (MIT).

• main assumption – output of any economic unit depends on amount of capital invested in that unit. Essentially assumption that in a poor, labor-surplus economy, the binding constraint is likely to be the stock of physical capital.

(growth as abstention from current consumption, figure 3.1 from Ray again as a growth story – how growth happens, savings as leakage out of system which allows investment and therefore growth, system in balance when S=I; ec expands when I > than needed to replace depreciated capital, allowing next period’s cycle to recur on larger scale)

• basic equations/assumptions:

S(t) = sY(t)

[pic]

I(t) = K(t + 1) – (1-()K(t) = S(t)

where s is economy-wide savings rate (total savings divided by total income), i is the economy-wide capital-output ratio, j is the economy-wide labor-output ratio,

- we’ve assumed all three are fixed and exogenously determined

- we've assumed that the binding constraint is the stock of physical capital, i.e. the economy has a surplus of labor

• the rates of growth of aggregate output, [pic], and per-capita output, [pic], can then be determined:

K(t + 1) = (1-()K(t) + I(t) (

iY(t + 1) = (1-()iY(t) + sY(t) (

[pic] (

[pic] (

[pic]

• to increase growth, raise s and accumulate capital, lower i, lower n

• comments/criticisms:

- combines fundamental features underlying growth: ability to save and invest, ability to convert capital into output, rate at which capital depreciates, population growth

- capital created by investment in plant and equipment is the main determinant of growth and savings determine this investment

- basis for Soviet planning, Indian five-year plans and other planned industrialization strategies; estimate i, then choose g and model will tell you s and therefore I, or choose s and model will tell you g; for whole country or by sector, especially useful if can affect s or i

- the Leontief production function assumes a fixed i, however this is likely to vary over time and to be susceptible to policy intervention. In general, capital-output ratio rises as ec grows, savings increase and surplus labor diminishes. However, it also depends on efficiency with which inputs used.

- assumption that s, i, and n are exogenous in the sense that there are no endogenous feedback mechanisms from the variables being determined within the model, i.e., K, Y, S, and I, to these "parameters"; hence, presumption that these parameters, can be directly manipulated by governments within a planned/command economy

- think through example in which savings rate endogenous – increases and then decreases as ec grows (and ec growth rate with it)

4. Neoclassical/Solow growth model

• developed by Robert Solow and others. Endogenizes i by introducing law of diminishing returns.

• basic assumptions/equations:

[pic]

S(t) = sY(t)

[pic]

[pic]

• assumptions about F(K, L):

- diminishing marginal returns to each input

- input substitution possible, hence capital-output ratio endogenous

- constant returns to scale

• constant returns to scale allows us to rescale (ratio of marginal productivities depends only ratio of inputs, not on scale):

[pic]

For example:

[pic]

• fundamental equation of the Solow model:

[pic]

• figure below depicts the long-run equilibrium of the Solow model

• the steady-state or long-run equilibrium is defined by:

[pic]

where * denotes the steady state quantity of the variable

• comments/criticisms:

- key to difference with Harrod-Domar is diminishing marginal returns

- in the long-run, y is constant, i.e., [pic] in the steady state, unless there is technological progress, i.e., increases in (; in other words, technological progress is the only source of sustained growth in y (can be put into model as efficiency units of labor, then SS growth of per capita income at rate of tech progress)

- but note that even in the steady state, Y continues to grow at a rate of n

- long-run level effects: [pic]; [pic]

- long-run growth effects: [pic]

- therefore in the long-run, three sources of variation in y, all of which are taken to be exogenously determined:

➢ population growth rates

➢ savings rates

➢ rates of technological progress

- thus if these three features are similar across economies, in the long-run we expect to see convergence, i.e., countries that start off with lower levels of k (and hence y) will exhibit higher growth rates in the transition to the long-run equilibrium. This is the hypothesis of unconditional convergence. Predicts convergence irrespective of historical starting point (i.e. two countries with similar parameters will end up in same place regardless of where started).

- hypothesis of conditional convergence admits that countries may differ in these parameters and emphasizes instead convergence to a country-specific steady state y

- a lot of empirical research using cross-country data has been done on this; evidence still inconclusive; some evidence for conditional convergence, i.e. convergence to same per capita growth rate (if tech progress same across countries), but still much more variation than in per capita income than theory predicts (can exaggerate theoretical predictions only at cost of ascribing a constancy of ec returns to physical capital which physical capital does not possess, it needs labor to be productive)

- also empirical research raises questions: why do saving rates and pop growth rates remain so different across countries, if tech progress drives all growth, what drives tech progress, diffusion etc

5. Endogenous growth models

• in Solow model, growth of y cannot be sustained in the long-run because of diminishing returns to K, except through technological progress, which is left unmodelled (modeled in black box way)

• endogenous growth models build upon Solow model by addressing these shortcomings:

- some models introduce human capital, H, as an additional form of capital that can be deliberately accumulated and assume that F(.) displays constant returns to scale when both factors, K, and H are included:

e.g. [pic]

[pic]

Note: the omission of labor, L, here is intentional; what makes this model qualitatively different from the Solow model is the fact that the production function displays constant returns to scale in all the factors that can be deliberately accumulated; to the extent that the labor force grows exogenously, introducing L into the production function would make this model essentially equivalent to the Solow model.

Note: conditioning on human capital shows conditional convergence and divergence due to human capital

- other models have explicitly introduced investments in R&D that contribute to technological progress –who chooses the level of R&D? if individual then issue of appropriability of returns, need some degree of monopoly

- still other models have focused on increasing returns to scale, externalities and spillovers in the process of growth and capital accumulation such as those that might arise from learning-by-doing, or from knowledge spillovers across firms, or complementarities such as will choose to save and invest more if expect overall ec investment to be higher in a way which affects my productivity

• Comments:

- all of these models have the implication that growth in y can be sustained in the long-run

- these models predict divergence in y across countries over time

- these models have focused the policy discussion on the importance of accumulating human capital and of increasing the knowledge base of an economy

6. Sources of growth analysis/growth accounting

• economists have attempted to determine the respective contributions of physical and human capital and tech progress to growth

• tech progress, or productivity growth, calculated as residual after all measurable inputs accounted for

• results very sensitive to procedure. Have to be very careful to properly measure measurable inputs, since TFP is residual. E.g. WB study finding that 1/3 of growth of rapidly growing E. and S.E. Asian economies due to TFP. Result wiped out by Alwyn Young’s careful study (TFP growth varying from .2% in Singapore to 1.7% in S. Korea): overest TFP growth if proxy L force with pop growth since L force participation increased hugely, if looking for TFP in manufacturing have to account for rural-urban migration in calculating L force, have to account for changes in K and L, particularly changes in quality, e.g. education of L (more educated L is more L)

• if don’t do exercise carefully, get distorted policy prescriptions

B. Structural change

1. Two-sector/dual-economy models: Lewis/Fei-Ranis

• the process of economic growth typically does not affect all parts of the economy evenly. A salient feature of the process is shift from urban to rural, agricultural to industrial. Agriculture provides labor and food for the industrial sector. (Other links – industry can provide inputs for agric, agric provides D for industrial output, agric exports can earn foreign exchange for the import of inputs into industry.) How does this interaction affect the process of growth?

• Model developed by Arthur Lewis in 1954. Central feature – dual economy. Duality may refer to traditional/modern (often equated to agric/industrial, types of techniques of production, but perhaps most imp types of ec org family with profit distributed as shares as opposed to capitalist based on wages), rural/urban, agric/industrial. These often equated. The equations don’t hold up exactly but useful for organizing thoughts (agric may rely on modern, capital-intensive techniques, informal sector in urban areas often more usefully thought of as traditional, much of informal sector non-agric but does not fit in with industrial classification)

• Basic setup and assumptions:

- the economy consists of 2 sectors, which may be thought of as agriculture(A) and industry(I), traditional and modern, rural and urban, or non-capitalist and capitalist

- A-sector inhabited by peasant farmers with production function [pic]where A is the stock of land, which is non-reproducible/non-accumulable. We make the following assumptions:

➢ diminishing marginal product of labor

➢ initially, [pic], i.e. excess supply of labor

➢ but wA fixed at some subsistence level, w

➢ no investible surplus in A-sector

- I-sector inhabited by capitalists/industrialists with production function [pic] where K is accumulable/reproducible through savings and investment of surplus. Assume:

➢ diminishing marginal product of labor

➢ wage in I-sector, [pic]

➢ industrialists save and invest some of their surplus, so the capital stock grows from period to period

• Static equilibrium

- based upon the initial capital stock in the I sector, labor moves freely between the two sectors so as to equate wages in the two sectors. (see figures below)

• Dynamics

- capitalists in the I-sector obtain profits which they save and invest, thereby increasing the capital stock and hence, the marginal product of labor (at any given quantity of labor). This in turn puts upward pressure on wages in the I-sector, inducing a flow of labor in from the A-sector, mitigating the upward pressure on wages. This is depicted in figures below.

- over time the I sector grows, with more and more labor shifting from A-sector to I-sector. The growth is initially facilitated by the fact that the industrial wage is kept low by excess supply of labor; hence industrialists benefit from growth, but not workers. However, at some point, the excess supply of labor is used up and then wages begin to grow as well

• Critique/comments

- is [pic]? Here useful to distinguish between marginal product of labor vs. marginal product of a laborer.

- As L withdrawn from agric sector there’s more income for remaining workers to share. Why not share it and raise wage? If do then reduce agric surplus and raise required industrial wage. Even if market surplus in response to higher prices, second effect remains.

- presumes existence of entrepreneurial/industrialist class and assumes class will save and accumulate; but what about conspicuous consumption, capital flight?

- ignore possible emergence of urban labor interests, unions, pushing industrial w above the subsistence wage, and consequent behavioral responses of industrialists in choosing more capital-intensive technologies or not investing

- where does the market for industrial goods come from?

C. Aggregate measures of development

1. Gross National Product (GNP)/Gross Domestic Product (GDP)

• Definitions

- GNP: the sum of the value of all finished goods and services produced by individuals and firms of an economy during a given year; equals the total income (including wages and profits) earned by citizens of a country regardless of location/source of income, Note: in calculating GNP we exclude intermediate goods (so as to avoid double counting); e.g. a cattle rancher sells quarter-pound of meat to McDonalds for 50 cents, then McDonalds sells you the burger for $1.50, GNP goes up by $1.50. Include value of domestically consumed agricultural production, but not of “in-house” output such as child-care, cooking, etc. Value public services at cost of provision.

- GDP: similar to GNP except it counts all income produced within the borders of an economy by both foreigners and citizens

- Note: what does the magnitude of the difference between GNP and GDP for an economy tell us about the economy's integration into the global economy?

• GNP/GDP measures, for their drawbacks, which we go through below, offer really the only way of aggregating across the thousands of goods and services that are produced by an economy

a. Conceptual and practical problems

• GNP/GDP measurement requires sophisticated data collection/statistical institutional apparatus/capability, which is not always present in poorer economies; size of the informal or underground economy in many developing economies poses a particular problem

• GNP/GDP measures based on market transactions; again, this may be a particular problem in poorer economies because of:

- prevalence of subsistence agriculture, include consumed goods produced by households but probably large measurement error

- low rates of female labor force participation

- valuation of goods and services whose prices either don’t exist or may not reflect social value, e.g. cases of monopoly, regulated prices, govt expenditures on bureaucracy, military, space research, environmental degradation,

- Note: some non-marketed expenditures are included by imputing market expenditures; e.g. housing expenditures of homeowners are imputed by estimating the rent a homeowner would have to pay, were he renting his home

- GNP/GDP measures don't take into account the depreciation of an economy's natural resource base

- index number problems complicate cross-country and intertemporal GNP/GDP comparisons

b. Cross-country comparisons: purchasing power parity

• relative prices of traded and non-traded goods can vary substantially across countries; also exchange rates can be distorted; this complicates cross-country comparisons

• Example

U. S.($) India(Rs.)

Quantity Price Value Quantity Price Value

Steel 100 200 20 8 6000 48

Personnel 2 5000 10 4 30000 120

Total GNP 30 168

- suppose official exchange rate (say, from the ratio of steel prices) is Rs.30/$ 1; then India's GNP is: 168/30 = $5.6 billion ( the U.S. economy is 30/5.6 = 5.35 times larger than the Indian economy

- suppose instead we used U.S. (relative) prices to value Indian output (both steel and personnel services); then India's GNP is: (200 X 8) + (5000 x 4) = $21.6 billion ( the U.S. economy is 30/21.6 = 1.38 times larger

- in the latter case we are, in effect, applying a purchasing power parity based exchange rate to convert Indian output into U.S. $; a variant of this method is being used increasingly by international organizations; it has long been used in academic studies. Note: using Indian relative prices to value output in both countries would have given us a slightly different answer

c. Intertemporal comparisons: index number problems

• the problem of which set of prices to use to value GNP also arises in making intertemporal comparisons. Again, the problem stems from the fact that relative prices of different goods and services can change over time

• Example

Base year(1972) Current year(1998)

Quantity Price Value Quantity Price Value

T.V. sets 1 500 500 50 200 10000

Wheat 150 50 7500 200 150 30000

Total GNP 8000 40000

- what is the appropriate GNP growth index? Not 40000/8000 = 5

- using base year prices: [pic]; this is the Laspeyres index

- using current year prices: [pic]; this is the Paasche index

- either one is a more correct index of GNP growth than the ratio of GNP in the two years with GNP in each year being valued at that year's prices

- since in most countries industrial sector grows faster than agric sector, prices which give industrial sector larger weight in national product will result in higher growth rate

2. Human Development Index

a. Definition

• the Human Development Index (HDI) is constructed by taking the simple average of indices of life expectancy, educational attainment and adjusted (PPP) real GDP per capita for an economy

b. Conceptual issues

• which measures of economy - wide development should be included? why focus on only these three?

• how should indices of achievement along each of these dimensions be constructed?

how should achievements along these different dimensions be weighed? what are the weights implicit in taking a simple average of the three indices of achievement?

D. History, expectations, coordination failures and linkages

• History and expectations interact and work through two main channels: complementarities and increasing returns

1. Complementarities, coordination failures and linkages

• an economic activity is said to involve an externality when the fact that an economic agent is undertaking that activity has an effect (positive or negative) on other economic agents that is not mediated (internalized) through a market mechanism; divergence between individual cost and social gain; can think of this in terms of missing market

- cab-fares in Atlanta went up during the 1996 Olympics – does that mean that the visitors to the Olympics imposed a negative externality on local residents?

- the increased levels of traffic during the Olympics resulted in higher levels of noise and air pollution – is that an example of a negative externality?

• an economic activity is said to involve positive complementarities – which are a special case of positive externalities – when the fact that an agent is undertaking that activity, not only has a positive effect on other agents, but also increases their incentives to engage in that activity; one individual’s action affects others’ relative preferences for choosing similar actions; e.g. cost of adopting a system depends on how many other people have adopted it

- safe driving is an example of an activity that provides a positive externality but does not involve complementarities - the fact that you are driving safely need not induce others to drive safely

- investment (and capital accumulation) can sometimes be an example of an activity characterized by complementarities; a firm's decision to invest can sometimes raise the rate of return on the capital stock of other firms - a positive externality - but in doing so, also raises the other firms' incentives to invest themselves, which is an instance of complementarities at work

• the figure below provides an example of complementarities, illustrating the economics of QWERTY

• historical lock-in or Pareto-comparable multiple equilibria can occur only when the externality is positive; figure below provides an example of anti-complementarities, for example due to congestion effects; clearly in this case history can have no effect, both roads will be used regardless of which was put in first

• insights:

- the presence of complementarities raises the possibility of multiple equilibria to which an economy might converge

- both the history (of past actions and choices) - this is what is meant by path dependence or historical lock-in - as well as expectations/beliefs (about future choices) determine which particular equilibrium an economy actually converges to

- the possibility of multiple equilibria and historical lock-in arises only when externalities take the form of complementarities

• basic idea: in the presence of complementarities, history (past patterns of activity) as well as expectations/beliefs (about others' future actions) become very important in determining aggregate outcomes

• pervasive complementarities, by raising the possibility of multiple equilibria, suggest the possibility that economies might get trapped in a "low-level" equilibrium or vicious cycle of poverty; the phenomenon of poverty and underdevelopment may therefore be the outcome of a massive coordination failure

• Example: Rosenstein-Rodan's parable of the shoe factory

- shoe factory that produces $1,000,000 worth of shoes (and hence $1,000,000 worth of wages, profits and rent) cannot by itself survive if all the shoes have to be sold locally simply because people will want to buy things other than shoes. Suppose the local population would like to spend 50% of their income on food, 30% on clothing, and 20% on shoes, and imagine that three factories were set up: a food factory to produce $500,000 worth of food, a clothing factory to produce $300,000 worth of clothing, and a shoe factory to produce $200,000 worth of shoes. All three would be jointly viable, whereas each individually would not. But suppose no single entrepreneur is large enough to set up all three. There are then two possible equilibria:

➢ a "good!' equilibrium where each of three entrepreneurs invests because she believes the other two will invest

➢ a "bad!' equilibrium where none invest because each believes the others will not; this latter equilibrium is characterized by a coordination failure

• big-push/balanced growth: Rosenstein-Rodan argued that to overcome such coordination failures, which can arise both because of lack of demand, as in the above example, as well as supply bottlenecks, governments needed to coordinate a "big push" industrialization effort along a broad front (i.e., multiple sectors); this is also often referred to in terms of the need to pursue a balanced growth path. Requires massive gov’t investment in many sectors at once and quantitative allocation of I across sectors – how know the right allocation? Also, this does not exploit fact that desirable outcome is also an equilibrium (as the following does).

• linkages: Hirschman's response was that backward and forward linkages also play a role; basic idea is that the development of one sector (perhaps with government support) will stimulate/induce investment in those sectors, because it creates supply for downstream sectors and demand for upstream sectors, without the need for active government intervention

- an industry A is said to have a forward linkage to another industry B when expansion of A increases the availability of some input needed by B, thereby easing the supply of good/service produced by industry B

- an industry B is said to have a backward linkage to another industry A if expansion of the former raises the demand for the good/service produced by the latter

- the following figure provides illustrative examples of backward and forward linkages

- focus on linkages suggests an alternative policy of unbalanced growth where key or leading sectors, i.e., those with strong linkages (especially backward linkages) to other sectors, are identified and selectively promoted, in the hope that the market pressures created by these linkages will then automatically foster the growth of other sectors

- how identify which sectors to develop? (a) number of linkages, (b) strength of linkages (forward vs backward), (c) “intrinsic profitability” of each sector – govt would do best to invest in least profitable one. Possible examples of leading sectors: heavy industry, exports, tourism, transportation, agriculture

- the magnitude of linkages can be estimated by analyzing input-output matrices; input - output matrices implicitly assume a fixed coefficients technology and can be constructed at as disaggregated a level as data permit; for instance an input-output matrix for an economy with four goods might look like:

To produce 1 unit of

Good 1 Good 2 Good 3 Good 4

units Good 1 a11 a12 a13 a14

needed of Good 2 a21 a22 a23 a24

Good 3 a31 a32 a33 a34

Good 4 a41 a42 a43 a44

• issues to keep in mind:

- role of credit market imperfections

- role of domestic market size, possibility of trade

- coordination problem may require one, short-term intervention, unlike externalities which require sustained regulation

- role of beliefs and expectations

2. History vs. expectations

• analysis so far suggests that while history can lead an economy to a bad equilibrium, self-fulfilling expectations can lead an economy to a better equilibrium; so what is the relative role of history and expectations?

• In econ expectations may not play as strong a role as in fashion. Historical lock-in effects can be hard to overcome because structural changes take time and occur gradually; even if I believe that everyone will eventually be using a new operating system, I have an incentive to delay switching to the new system till the early users have identified the bugs and they've been fixed, until new software is made available for use on that system, etc.; what matters therefore is whether the first movers (early adopters, innovators) gain some advantage from moving first; only in those instances will coordination failures not arise or can be overcome without external intervention

• Expectations can play a very strong role when some advantage in being an early mover, e.g. maybe get better jobs if get there first or don’t face costs of congestion (e.g. initially cheap housing if new tech allows move out of city)

3. Increasing returns

• a production activity is said to display increasing returns to scale if an expansion of output (scale) lowers the unit costs of production

• the presence of IRS can have very similar effects as complementarities, in fact complementarities can be seen as sort of IRS at a more aggregate, social level

• ability to realize gains from production depends on size of available market, at the same time size of market may depend on ability to exploit increasing returns, expand production and pay out income.

• New tech may not be developed if perceived that will not be able to invade mkt. May not develop more appropriate techs than ones which currently command mkt (e.g. imported from developed countries)

• Again mult equil possible – (1) small mkt, little D for final good, intermediate input industries can’t operate at viable level, input prices high, employ mostly L, low productivity, low wages, stay poor, (2) large D, allows IRS to be exploited in intermediate goods, prices of inputs go down, substitute away from L, increase productivity, higher wages, more D

• Imp to remember that small mkt argument relies on assumption of little trade

4. Other roles for history: social norms, persistence of status quo (because of problems with identifying and/or compensating gainers and losers)

E. Inequality, growth and development

1. Inequality and growth: interrelationships

• Inequality of what? Current income, wealth, lifetime income. Mostly only data on the first. Latter two perhaps more important. Big problem with current income, point of time at which measure it.

a. Inequality and savings

• one link between inequality and growth comes from the relationship between the level of income inequality in an economy and the economy's aggregate savings rate. The direction of the link depends on whether marginal savings rates are increasing or decreasing with income. How does this work? Compare two different settings. In one, construction worker making $5,000 a year and investment banker making $55,000 a year. In another, two professors making $30,000 a year each. In which case are savings higher?

• Factors that might lead to differential savings rates at different levels of income:

- subsistence needs

- aspirations for upward mobility

- conspicuous consumption

• in very poor countries redistributive policies may limit growth – but how do we feel about recommending inegalitarian policies

• savings behavior can also affect evolution of inequality – through evolution of standards which people aspire to if the rich set the standard for everybody else. If egalitarian to begin with, stay that way. If big differences, middle class may catch up to the rich by saving a lot, while poor may not be able to save enough to do any catching up. Another example of history mattering.

b. Inequality and redistributive politics

• inequality may retard economic growth by increasing political pressures for redistributive policies. However, it is important to distinguish between:

- redistribution of assets, i.e., taxes on the stock of wealth; redistribution of wealth can have positive growth effects if it facilitates human capital investment, or eases the effects of capital market imperfections (example of East Asian tigers)

- redistribution through taxes on increments to wealth, i.e., capital income, reduces incentives to invest and thus can be a hurdle to growth.

• inequality can lead to political instability and conflict that creates an environment of uncertainty, which discourages investment. When is growing inequality likely to lead to political unrest? Hirschman talks about the tunnel effect which nicely captures the dynamics of political tolerance for inequality

c. Inequality, market size and demand composition

• inequality, by determining the composition of aggregate demand, can affect the market size for certain products; if production involves learning-by-doing or significant fixed costs, small size of market may retard development of these sectors, potentially slowing the process of industrialization. But keep in mind that the limitations of domestic market size can, in principle, be overcome by targeting export markets.

• Income determines not only level of consumption but also its composition, e.g. falling share of food items as incomes rise. D composition can also affect distribution of incomes. If high D for luxury goods in highly unequal environment, and if luxury goods capital-intensive, perpetuate inequality, if L intensive may reduce it.

d. Inequality, capital market imperfections, investment and human capital development

• capital markets are imperfect in the sense that an individual's capacity to borrow is usually linked to their ability to provide collateral. Thus, to the extent that credit is necessary to start a small business, pay for education, buy yield-enhancing inputs, or any form of productivity - enhancing investment, the poor, who cannot provide the necessary collateral to obtain credit, will be unable to make such investments. Other than the obvious human cost that this implies, inequality can reduce the overall level of investment and lead to a mismatch of funds and investment ideas/opportunities.

• in the presence of capital market imperfections, there is a tendency for inequality to be perpetuated (in some cases, exacerbated) from generation to generation. Again history matters.

2. Measuring inequality

a. Conceptual issues

• should we care about inequality in current income, wealth, or lifetime income? Moving from short-term to long-term considerations. Concern about short-term inequality should depend on what we know about mobility. In other words, what should we use to measure the welfare of individuals and households?

• should we care about inequality across households, or inequality across individuals; in the latter case we also have to worry about intrahousehold inequality

• should we care only about inequality in outcomes (vertical inequality), or do we also care about inequality in treatment (horizontal inequality) regardless of outcomes? Also functional or personal income distribution? Former concerns how people earn what they do, i.e. ownership structure (why would functional matter – (1) where income comes from may influence welfare (e.g. charity vs earnings), (2) functional distribution affects rel between inequality and growth)

• should we care about inequality at all, i.e, should our focus instead be on poverty?

b. Lorenz curves

• in practice, usually focus on measures of vertical inequality (i.e., inequality in outcomes), and the outcome measure is usually income/consumption/wealth/landholding

• household-survey data and/or Census data can be used to plot the distribution of income (or whatever the outcome measure is that we choose) in a country

• several ways of depicting the distribution of income:

- histograms (i.e., for each income level (or range) plot the fraction of individuals with income lying in that range)

- cumulative distribution function (i.e., for each income level, plot the fraction of individuals with incomes below that level)

- for discussions of inequality the preferred way is often the Lorenz curve. To generate a Lorenz curve:

➢ order the households by income, from poorest to richest

➢ for each percentile of the population, starting from the poorest, plot the cumulative proportion of the population against the cumulative proportion of overall income earned by households

• Example: Following figure depicts the Lorenz curve for the following economy with four individuals

Cumulative proportion Cumulative proportion

Individual Income of population of income

1 20 25% 10% = [pic]

2 30 50% 25% = [pic]

3 50 75% 50% = [pic]

4 100 100% 100% = [pic]

c. Cross-country and intertemporal comparisons

• Lorenz curves offer a convenient way of summarizing the distribution of income, and the extent of inequality and facilitates cross-country and intertemporal comparisons of inequality

• if the Lorenz curve for country/time period 1 lies everywhere outside the Lorenz curve for country/time period 2, as in the figure below, then country/time period 1 has a more unequal distribution

• however, if the Lorenz curves cross, comparisons become harder to make at an aggregate level

d. Gini coefficient/Gini concentration ratio

• a common way of summarizing the information captured in a Lorenz curve that avoids the problem described above is to compute the corresponding Gini coefficient (Gini concentration ratio), which is defined as the ratio of the area between the Lorenz curve and the 45-degree line, and the area of the triangle below the 45-degree line. Thus a Gini coefficient of 0 (coincides with 45-degree line) implies perfect equality while a Gini of 1 implies perfect inequality.

• here are the Gini coefficients for several countries during the 1980s:

Bangladesh .280

Brazil .610

Hong Kong .400

Japan .282

United States .369

e. Coefficient of variation

• a particularly simple way of measuring inequality is to compute the coefficient of variation of income (or whatever the relevant variable is) within a country. From household survey data or the Census it is usually possible to estimate the standard deviation and mean of income for a population. The coefficient of variation is then simply the ratio of the two, i.e., a measure of the variation in income relative to the mean income.

• When Lorenz curves can be compared Gini coefficient and coefficient of variation give the same ranking, consistent with Lorenz curves. However, when Lorenz curves cross these may give contradictory rankings, flagging crossed Lorenz curves and telling us that comparison is not clear-cut.

3. Empirical patterns and evidence

• inverted-U hypothesis/Kuznets curve: observation that for a limited cross-section of countries, the level of inequality tends to initially rise with increasing per-capita income, and then subsequently decline:

Per-capita income(1965 U.S.$) Average Gini Range of Gini

Less than 100 0.419 0.33-0.51

101 to 200 0,468 0.26-0.50

201 to 300 0,499 0.36-0.62

301 to 500 0.494 0.30-0.64

501 to 1000 0.438 0.38-0.58

1001 to 2000 0.401 0.30-0.50

2001 and higher 0.365 0.34-0.39

• have to be careful in interpreting such data, e.g. is it just a Latin America effect (most middle income countries are latin american and high inequality for whatever reason in latin america). Also problem with gini in that crossing Lorenz curves while gini may be increasing and decreasing. In fact inverted U goes away when control for parallel shifts (fixed effects for countries)

• cross-country evidence on initial inequality and subsequent growth (Alesina and Rodrik):

Dependent variable: per-capita growth, 1960-85

Variable Coefficient (t-statistic)

1960 per-capita income -0.39(4.63)

1960 primary enrollment rate 2.62(2.53)

1960 income Gini coefficient -3.45(l.79)

1960 land Gini coefficient -5.24(4.32)

Democracy x land Gini 0.12(0.12)

• what drives this? Lower inequality encouraging S and I or political redistribution? Not known.

F. Poverty

1. Measuring poverty

a. Conceptual issues

• conceptual issues that one faces in measuring poverty include:

- in terms of which variable should poverty be defined? Common choices include caloric intake, broader measures of consumption, income, landholding, etc. Usually only have data on income

- household or individual? Usually only have data on households. This neglects issues of intra-household distribution. Also larger households often have more children who consume less – need adult equivalence scales. Also, fixed costs in setting up household, which larger households can be spread over larger # of members.

- how should a poverty line be chosen ? Keep in mind that any choice is ultimately somewhat arbitrary. Fuzzy pointers to a deeper, less quantifiable concept.

- are notions of relative poverty as opposed to absolute poverty meaningful (or is the former simply inequality in another guise)? Minimum necessary to function in a society is likely to differ across societies, e.g. need for clothes, types of clothes, transportation, housing. Need to be evaluated relative to prevailing socioec standard, can’t be given absolute meaning. While poverty lines may have to vary across countries for these reasons, this can be taken too far.

- should the focus of policy be on transient or chronic poverty?

- in estimating the poverty status of a household, how should access to public goods, non-marketed items, subsidized health care, etc. be treated?

b. Head-count ratio

• Definition: HCR = fraction of the population that is poor, i.e, have incomes less than z, the poverty line

• the main advantages of the HCR as the measure of poverty in an economy are that it's intuitive, easily explained, and easily calculated; the primary drawback is that it's insensitive to the distribution of income among the poor. For instance, a government policy that results in a transfer of income from the poorest of the poor to the least poor of the poor might lower the HCR, but would seem objectionable from an ethical perspective. Also, policy based on HCR, e.g. minimize HCR, would lead to transfers to the wealthiest of the poor since its easiest to move them above the line. Another drawback is that it gives no indication of how poor the poor are.

c. Poverty gap/Income gap ratio

• the poverty gap in an economy is defined as:

[pic]

where [pic] is the mean income of those below the poverty line

• the income gap ratio (IGR) expresses the poverty gap as fraction of the poverty line, i.e.:

[pic]

• the IGR provides a measure of the depth of poverty and hence of the resources required to eliminate poverty; because it does not focus on the numbers of people classified as poor, it is in some ways less manipulable by policy makers. But it goes too far in ignoring the actual numbers of people who are poor.

• Both HCR and IGR ignore relative deprivation, or inequality, among the poor. E.g. price of rice increased in Java, Indonesia in 1981. Poor who are rice farmers helped by this. However, poorest are landless laborers or marginal farmers who are net consumers of rice and therefore hurt by this. But HCR and IGR went down. (need transfer-sensitive measures which would go up as a result)

d. Foster-Greer-Thorbecke class of measures/Sen's index

• Amartya Sen proposed an axiomatic approach to defining a poverty measure; he suggested that a poverty measure should have the following desirable properties:

- if the number of the poor increases, the measure should go up

- if the poor get poorer, the measure should go up

- if the distribution of income among the poor becomes more unequal, the measure should go up

• the HCR satisfies the first but not the latter two conditions; the IGR satisfies the second, but need not satisfy the other two; Sen proposed an index of poverty which satisfied all three conditions

• Foster, Greer, and Thorbecke, building upon Sen's work proposed a specific functional form for poverty measures, which depending on the choice of a key parameter, (, reduces to one of the other poverty measures. The general formula is:

[pic]

where N is the total number of individuals in the economy, and yi is the income of individual i. Note that each choice of ( yields a different poverty measure. For instance:

[pic]

where Cp is the coefficient of variation of income among the poor.

• As ( increases above 1, FGT index puts greater weight on larger poverty gaps making measure more sensitive to these gaps and therefore to issues of distribution.

• Case of ( = 2 esp interesting. With no inequality poverty can be captured through some combination of HCR and IGR. However, inequality increases poverty and its effect captured by coefficient of variation. This case also makes boundary above which index acquires transfer sensitivity (regressive transfer between two people should matter more if starting incomes of both people reduced equally)

2. Empirical patterns of poverty

• Inequality often implies poverty but no necessary relationship between the two.

• World Bank has experimented with two universal poverty lines, $275 and $370 per person in 1985 PPP prices (poverty lines of some of the poorest countries fall between these, lower figure coincides with poverty line for India). According to the latter, in 1990 over 1 billion individuals below poverty line (600 million according to lower line). Percentage of people in poverty, approximately 30% of total population in developing countries constant over this period, but absolute numbers rising significantly.

• Poverty associated with large households – this may not hold up once control for adult-equivalence, fixed costs. Causality not clear.

• Poverty associated with rural areas, lack of assets (e.g. landlesness)

• Poverty associated with malnutrition, although interestingly, no direct relationship between increases in income and nutrition (caloric intake increases but often substitute towards less nutritious foods)

• Poverty associated with females – related to functional effects of poverty; poorest households may need to concentrate available nutrition on breadwinners (relationship much more complicated than this)

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