AGEC 640 Agricultural Development and Policy Thursday, August 31, 2017 Last class Farm and food problems: the development paradox and structural transformation Today Mouths to feed, farmers to employ: population growth and demographic transition Next week: farm households’ response

Drivers of Change: Population growth and economic transformation Last class: broad diversity of policy problems and policy actions, but also strong regularities (“stylized facts”): the development paradox, from taxing to subsidizing farmers the structural transformation, from farm to nonfarm activity Today: a key driver (from outside, exogenous to agriculture) is demography: the demographic transition from large to small families high to low death rates and birth rates high to low fraction of people who are children …and other corresponding changes

Demographic transition A pattern of steadily increasing population growth, followed by a period of slowing population growth. Generally indicated as an S-shaped curve for population through time.

? 1 2 3 4 Frank Notestein (b. 1945) Three stages of population growth 1. High growth potential 2. Transitional growth 3. Incipient decline we might add… 4. Sustained decline? pop ? 1 2 3 4 time

1. High growth potential Pre-industrial Birth rate high (25-40/1000) Death rate high Life expectancy short Population growth low but positive Widespread misery

2. Transitional growth Early industrial Birth rate remains high (or rises!) Death rate low and falling Life expectancy rises Population growth is “explosive” Mortality declines before fertility due to better health, nutrition, and sanitation

3. Incipient decline Industrial Birth rate drops due to desires to limit family size (female education, empowerment and employment) Death rate low and stable Life expectancy high Population grows until birth rate = death rate Characterized by higher levels of wealth and reduced need for large families for labor or insurance.

A stylized model of a demographic transition The gap between birth and death rates is the population’s “rate of natural increase” (≈ population growth) CDR = crude death rate CBR = crude birth rate

An actual demographic transition Sweden’s population growth rate peaked at about 1.5% per year, in the late 19th century Spikes in CDR reflect a series of bad harvests and a dysentery epidemic in 1773

A different demographic transition The second wave of the 1918 influenza reaches Africa in September 1918 Mauritius’ peak pop. growth rate was over 3%/year, twice that of Sweden, because its death rate fell so fast…

A third kind of transition Mexico’s peak population growth was even faster, because its birth rate fell slowly…

Birth and death rates depend in part on age structure and “population momentum”

Reprinted from www.census.gov/ipc/www/idb. A very young age structure: the population pyramid for Nigeria 1980, 2000, 2020 Reprinted from www.census.gov/ipc/www/idb. AGEC 340 - Fall 99

A later stage of demographic transition: population pyramids for Indonesia 1980, 2000, 2020 Reprinted from www.census.gov/ipc/www/idb. Indonesia has a much more “mature” population pyramid than Nigeria AGEC 340 - Fall 99

The final stage of demographic transition: population pyramids for the United States 1980, 2000, 2020 Reprinted from www.census.gov/ipc/www/idb. The population “ages”, with tiny echoes of the post-WWII baby boom AGEC 340 - Fall 99

The lower-income regions have had a later (and much faster The lower-income regions have had a later (and much faster!) demographic transition

Africa’s pop. growth has been of unprecedented speed and duration, but is now slowing

Africa’s child dependency has been similarly unprecedented, and is now improving 10 20 30 40 50 60 70 80 90 100 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 No. of children (0-14) per 100 adults (15-59) E. Asia S. Asia Sub-Sah. Africa Whole World Source: UN Population Division, World Population Prospects: The 2000 Revision (http://esa.un.org/unpp)

Explaining the demographic transition What can account for the patterns we’ve seen, including especially the late and rapid demographic growth and child dependency in poor regions? Will look first at mortality decline, then fertility decline…

The age structure of mortality decline

The HIV/AIDS tragedy

Explaining the mortality decline (UK data) General improvements in: overall well-being education female literacy diet, water and sanitation Not, medical breakthroughs…!

Explaining the mortality decline (US data)

Explaining the mortality decline? From Frederiksen, H. (1966) Determinants and Consequences of Mortality and Fertility Trends, Public Health Reports 8(8): 715-727.

Explaining the fertility decline: social policies? Source: K. Sundstrom. “Can governments influence population growth?” OECD Observer, December 2001, p. 35.

Explaining the fertility decline: infant mortality The fertility decline lags substantially the drop in IM

Conclusions on population growth and the demographic transition Much popular understanding about population growth turns out to be wrong. In fact, over time and across countries: population growth starts with a fall in child mortality, which raises population growth initially because the fertility decline happens later the temporary burst of population growth involves a rise and then fall in the fraction of people who are children these changes are similar in all countries, but in today’s poor countries they occurred later and faster, with larger magnitude over shorter time period than occurred historically elsewhere How does the demographic transition affect agriculture?

What happens to the number of farmers? 28

What happens to the number of farmers? Initially, farmers are much poorer than non-farmers less capital/worker, lower skills, less specialized this means agriculture is the “residual” employer… (what is the opportunity cost of labor?)  CARL: Country with Abundant Rural Labor  The annual change in the number of farmers depends on: growth in the total population growth in nonfarm employment

Some arithmetic of structural transformation If we divide the total workforce into farmers and nonfarmers: Lf = Lt – Ln (Li=no. of workers in sector i) And solve for the growth rate of the number of farmers as a function of growth in total and nonfarm employment, we see that size of the sectors matters a lot: %Lf = (%Lt – [%Ln•Sn]) / (Sf) (Si=share of workers in i) In CARLs, even if nonfarm employment grows much faster than the total workforce, the number of farmers may still rise quickly: Rate of growth in rural population, by relative size of the sector proportion of workers who are farmers (Sf): 3/4 2/3 half Country is poor but successful: nonfarm employment growth (%Ln) = 6%, twice rate of workforce growth (%Lt) = 3% +2.0% +1.5% 0.0%

The number of farmers rises then falls… until farmers’ incomes catch up to nonfarm earnings The “textbook” picture of structural transformation within agriculture: farm numbers stabilized by off-farm income and rising profits per acre; latest US census shows slight rise in no. of farms Figure 5-3. Number and average size of farms in the United States, 1900-2002.

In very rich countries, the number of farmers does not keep falling to zero! In the Harris-Todaro model of migration, farmers move to cities if nonfarm work offers higher expected incomes: migrate if: Wrural < (Lemployed/Ltotal) x Wurban An equilibrium at which the number of farmers stays constant would offer equal farm and nonfarm earnings: Wageoff-farm = Earningson-farm = Profits/acre x acres/hour Thus, you can have no change in the number of farmers IFF profits/acre or acres/hour rise fast enough to keep up with off-farm wages

In the world as a whole, the number of farmers recently peaked and will soon decline AGEC 340 - Fall 99 33

Regions differ sharply in their population growth rates Source: Calculated from FAOStat data (www.fao.org).

Cities are growing much faster than total population Source: Calculated from FAOStat data (www.fao.org).

…but cities are still too small to absorb all population growth, especially in S. Asia and SSA Source: Reprinted from W.A. Masters, 2005. “Paying for Prosperity: How and Why to Invest in Agricultural R&D in Africa.” Journal of International Affairs 58(2): 35-64.

Conclusions on economic growth and structural transformation As incomes grow… Farming declines as a fraction of the economy in favor of industry and services even within agriculture Farmers’ incomes at first decline relative to others but then farm incomes catch up… until farm incomes equal or pass non-farm incomes The number of farmers first rises and then falls speed and magnitude depend on both population and income growth eventually the number of farmers stabilizes in the future, the number of farmers may even rise!

More conclusions… Demographic transition and structural transformation interact, causing a rise and then a fall in the number of farmers. Today’s developing countries have had very fast decline in death rates, leading to unprecedented rate of population growth. For CARLs, small shares of (urban) population in nonfarm employment, lead to rapid rural population growth and declines in land available per farmer. The rural effect is compounded by a shift in age structure: first, more children/adult (the “demographic burden”), then, more child-bearing women (“population momentum”), then more working-age adults (the “demographic gift”) These are powerful drivers of change in agriculture and in agricultural policy, but occur slowly and are often ignored!