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view/download model file: agriculture_and_competition.nlogo

The model explores the stability, the evolution and the sustainability of a system with technical progress, random shocks, non renewable resources, birth control and a welfare state.

The program creates a world with renewable resources and in which each citizen is generated, moves, eats, reproduces, gets old and dies.

The user, thanks to different sliders and switches, can introduces more variables and he can implement different kind of policies.

The fertility rate and the life expectancy change over time.

1. Adjust the slider parameters (see below), or use the default settings.

2. Press the SETUP button.

3. Press the GO button to begin the simulation.

4. Look at the monitors to check the variables of this model

5. Look at the TOTAL and POPULATION COMPOSITION plots to watch the population fluctuation over time

Parameters:

NUMBER-OF-CITIZENS: The initial size of the population

TECHNICAL-PROGRESS?:Whether or not to introduce progress by means of increasing productivity

SHOW-ENERGY?: Whether or not to show the energy of each citizen as a number

NON-RENEWABLE-RESOURCES?: Whether or not to reduce gradually the growth rate of the resources

BIRTH-CONTROL?: Whether or not to enable only adults citizen with less than 50 children to reproduce themselves

SHOCKS?: Whether or not to introduce random shocks which may modify the composition of the population

REDISTRIBUTION?: Whether or not to introduce a welfare state

EDUCATION?:Whether or not to introduce an education system

MARGINAL-TAX-RATE: the tax burden, i.e. citizens have to pay a tax which is equal to the marginal tax rate multiplied by their energy

POVERTY-LINE: citizens which have less energy than the poverty line are considered poor

POVERTY-REDUCTION: the import of the subsidy received by poor citizens is equal to poverty reduction times the difference between poverty line and the energy of the citizen

EDUCATION-EXPENDITURE-PERCAPITA: public expenditure per capita in order to offer a public education to young citizens

See the different patterns of population and population composition when different switches are activated. Some choice are sustainable in the long run and other ones tends to bring citizens towards extinction or are financial unsustainable.

Note that is very important the time in which some policies such as education system or welfare state are implemented. The results may be very different both in the short run and in the long run.

Note that the tax burder play a key role in stimulating or dampening the population growth.

Try to modify the initial number of citizens. Does the shorth run equilibrium change?

Try to activate only some switches and see the effects.

Try to balance a good welfare state and education sistem with their financial sustainability: if the government debt is more than 500000, there is the default of the State.

Try to see, modifing sliders and activating switches, if there is a long-run equilibrium, a trend or if the model is instable.

Some interesting things to add would be: pollution, diseases and health system, happyness of population and possibility of rebellions, different breeds which compete to survive.

Note the use of let in order to create temporary variables.

Note the use of global variables in order to set variables which affect all the citizens, such as productivity, life expectancy, grass growth rate, knowledge and government budget.

Note the use of mathematical function, such as the square root or the natural logarithm, in order to consider decreasing marginal improvement in progress, life expectancy and growth rate of natural resources.

Look at Wolf Sheep Predation for a model of interacting populations with limited resources and instability problems.

Paolo Bosi (a cura di), "Corso di scienza delle finanze", 2010 - Quinta edizione, Il Mulino. Cap. 7 - La spesa per il Welfare State

Giovanni Pavanelli, "Valore, distribuzione, moneta: un profilo di storia del pensiero economico", 2010 - Seconda edizione, FrancoAngeli. Cap. 5.1 - Malthus e il Saggio sul principio della popolazione

The World Bank, World Development Report 2008, "Agriculture for Development", Overview

globals [productivity-reds productivity-blues life-expectancy-reds life-expectancy-blues grass-growth-rate energy-from-grass-reds energy-from-grass-blues government-budget-reds government-budget-blues knowledge-reds knowledge-blues productivity-of-the-young-reds productivity-of-the-young-blues] turtles-own [energy age children] breed [blue-turtles blue-turtle] breed [red-turtles red-turtle] to setup ca ask patches [set pcolor one-of [green brown]] create-blue-turtles initial-number-of-blue-citizens [setxy random-xcor random-ycor set energy random 10 set color blue set size 2 set age random 180] create-red-turtles initial-number-of-red-citizens [setxy random-xcor random-ycor set energy random 10 set color red set size 2 set age random 180] do-plots end to go ifelse technical-progress-reds? [set-productivity-reds] [set productivity-reds 0] ifelse technical-progress-blues? [set-productivity-blues] [set productivity-blues 0] set energy-from-grass-reds 25 + productivity-reds set energy-from-grass-blues 25 + productivity-blues set life-expectancy-reds 180 + sqrt (ticks + productivity-reds) set life-expectancy-blues 180 + sqrt (ticks + productivity-blues) ifelse non-renewable-resources? [set-grass-growth-rate] [set grass-growth-rate 10] ask turtles[move-turtle display-label] let temp random 2 ifelse temp = 0 [ask red-turtles [eat-grass-reds death-reds] ask blue-turtles [eat-grass-blues death-blues]] [ask blue-turtles [eat-grass-blues death-blues] ask red-turtles [eat-grass-reds death-reds]] ask patches with [pcolor = brown] [grow-grass] if redistribution-reds? or education-reds? [ask red-turtles [pay-taxes-reds]] if redistribution-blues? or education-blues? [ask blue-turtles [pay-taxes-blues]] if redistribution-reds? [ask red-turtles [redistribution-of-resources-reds]] if redistribution-blues? [ask blue-turtles [redistribution-of-resources-blues]] if education-reds? [implement-education-system-reds] if education-blues? [implement-education-system-blues] ifelse birth-control-reds? [reproduction-conditions1-reds] [reproduction-conditions2-reds] ifelse birth-control-blues? [reproduction-conditions1-blues] [reproduction-conditions2-blues] ask patches with [pcolor = brown] [grow-grass] if shocks? [do-shock] if count red-turtles = 0 or count blue-turtles = 0 [stop] if government-budget-reds < -500000 [user-message ( word "Default of the State of the reds") ask red-turtles [die]] if government-budget-blues < -500000 [user-message ( word "Default of the State of the blues") ask blue-turtles [die]] tick do-plots end to implement-education-system-reds let education-expenditure-reds (education-expenditure-percapita-reds * count red-turtles with [age < (30 + round(life-expectancy-reds / 10))]) set government-budget-reds (government-budget-reds - education-expenditure-reds - 2000) set knowledge-reds (knowledge-reds + (1 + random 1) * education-expenditure-reds) set productivity-of-the-young-reds (2 * education-expenditure-percapita-reds) end to implement-education-system-blues let education-expenditure-blues (education-expenditure-percapita-blues * count blue-turtles with [age < (30 + round(life-expectancy-blues / 10))]) set government-budget-blues (government-budget-blues - education-expenditure-blues - 2000) set knowledge-blues (knowledge-blues + (1 + random 1) * education-expenditure-blues) set productivity-of-the-young-blues (2 * education-expenditure-percapita-blues) end to set-productivity-reds set productivity-reds sqrt (0.1 * ticks + 2 * count red-turtles with [age >= (30 + round(life-expectancy-reds / 10)) and age <= (150 + round(life-expectancy-reds / 20))] + (0.5 - productivity-of-the-young-reds) * count red-turtles with [age < (30 + round(life-expectancy-reds / 10))] + 0.2 * count red-turtles with [age > (150 + round(life-expectancy-reds / 20))]+ 0.1 * knowledge-reds + random-normal 0 1) end to set-productivity-blues set productivity-blues sqrt (0.1 * ticks + 2 * count blue-turtles with [age >= (30 + round(life-expectancy-blues / 10)) and age <= (150 + round(life-expectancy-blues / 20))] + (0.5 - productivity-of-the-young-blues) * count blue-turtles with [age < (30 + round(life-expectancy-blues / 10))] + 0.2 * count blue-turtles with [age > (150 + round(life-expectancy-blues / 20))]+ 0.1 * knowledge-blues + random-normal 0 1) end to set-grass-growth-rate set grass-growth-rate 10 - ln (1 + 0.001 * ticks + 0.00001 * count turtles) end to move-turtle let steps random 10 right random 360 fd steps set energy energy - steps set age (age + 1) end to eat-grass-reds if pcolor = green [set pcolor brown set energy (energy + energy-from-grass-reds)] end to eat-grass-blues if pcolor = green [set pcolor brown set energy (energy + energy-from-grass-blues)] end to death-reds if energy < 0 or age > life-expectancy-reds [die] end to death-blues if energy < 0 or age > life-expectancy-blues [die] end to reproduction-conditions1-reds ask red-turtles with [age >= (30 + round(life-expectancy-reds / 10)) and age <= (150 + round(life-expectancy-reds / 20)) and children < 51] [generate-red-turtle] end to reproduction-conditions2-reds ask red-turtles with [age >= (30 + round(life-expectancy-reds / 10)) and age <= (150 + round(life-expectancy-reds / 20))] [generate-red-turtle] end to generate-red-turtle if count red-turtles in-radius 1 > 2 and energy > 50 + round (count red-turtles / 10) [set energy (energy / 2) set children (children + 1) hatch 1[set energy random 50 set age 0]] end to reproduction-conditions1-blues ask blue-turtles with [age >= (30 + round(life-expectancy-blues / 10)) and age <= (150 + round(life-expectancy-blues / 20)) and children < 51] [generate-blue-turtle] end to reproduction-conditions2-blues ask blue-turtles with [age >= (30 + round(life-expectancy-blues / 10)) and age <= (150 + round(life-expectancy-blues / 20))] [generate-blue-turtle] end to generate-blue-turtle if count blue-turtles in-radius 1 > 2 and energy > 50 + round (count blue-turtles / 10) [set energy (energy / 2) set children (children + 1) hatch 1[set energy random 50 set age 0]] end to grow-grass if random-float 100 < grass-growth-rate [set pcolor green] end to display-label ifelse show-energy? [set label round energy][set label "" ] end to pay-taxes-reds set energy (energy - marginal-tax-rate-reds * energy) set government-budget-reds (government-budget-reds + marginal-tax-rate-reds * energy) end to pay-taxes-blues set energy (energy - marginal-tax-rate-blues * energy) set government-budget-blues (government-budget-blues + marginal-tax-rate-blues * energy) end to redistribution-of-resources-reds if energy < poverty-line-reds [let subsidy poverty-reduction-reds * (poverty-line-reds - energy) set energy (energy + subsidy) set government-budget-reds (government-budget-reds - subsidy - 1)] end to redistribution-of-resources-blues if energy < poverty-line-blues [let subsidy poverty-reduction-blues * (poverty-line-blues - energy) set energy (energy + subsidy) set government-budget-blues (government-budget-blues - subsidy - 1)] end to do-shock let probability-of-shock random-float 1 let population-striken random 4 if population-striken = 0[if probability-of-shock < 0.05 and probability-of-shock > 0.001 [ask n-of ((count turtles) * random-float 0.1) turtles [die]] if probability-of-shock < 0.001 [ask n-of ((count turtles) * random-float 0.4) turtles [die]]] if population-striken = 1[if probability-of-shock < 0.05 and probability-of-shock > 0.001 [ask n-of ((count turtles with [age < 50]) * random-float 0.1) turtles with [age < 50] [die]] if probability-of-shock < 0.001 [ask n-of ((count turtles with [age < 50]) * random-float 0.4) turtles with [age < 50] [die]]] if population-striken = 2[if probability-of-shock < 0.05 and probability-of-shock > 0.001 [ask n-of ((count turtles with [age >= 50 and age <= 150]) * random-float 0.1) turtles with [age >= 50 and age <= 150][die]] if probability-of-shock < 0.001 [ask n-of ((count turtles with [age >= 50 and age <= 150]) * random-float 0.4) turtles with [age >= 50 and age <= 150][die]]] if population-striken = 3[if probability-of-shock < 0.05 and probability-of-shock > 0.001 [ask n-of ((count turtles with [age > 150]) * random-float 0.1) turtles with [age > 150] [die]] if probability-of-shock < 0.001 [ask n-of ((count turtles with [age > 150]) * random-float 0.4) turtles with[age > 150] [die]]] end to do-plots set-current-plot "Totals" set-current-plot-pen "red-citizens" plot count red-turtles set-current-plot-pen "blue-citizens" plot count blue-turtles set-current-plot-pen "resources" plot (count patches with [pcolor = green]) set-current-plot-pen "red-poor" plot count red-turtles with [energy < poverty-line-reds] set-current-plot-pen "blue-poor" plot count blue-turtles with [energy < poverty-line-blues] set-current-plot "Population composition reds" set-current-plot-pen "young" plot ((count red-turtles with [age < (30 + round(life-expectancy-reds / 10))]) / count red-turtles) set-current-plot-pen "old" plot ((count red-turtles with [age > (150 + round(life-expectancy-reds / 20))]) / count red-turtles) set-current-plot-pen "adult" plot ((count red-turtles with [age >= (30 + round(life-expectancy-reds / 10)) and age <= (150 + round(life-expectancy-reds / 20))]) / count red-turtles) set-current-plot "Population composition blues" set-current-plot-pen "young" plot ((count blue-turtles with [age < (30 + round(life-expectancy-blues / 10))]) / count blue-turtles) set-current-plot-pen "old" plot ((count blue-turtles with [age > (150 + round(life-expectancy-blues / 20))]) / count blue-turtles) set-current-plot-pen "adult" plot ((count blue-turtles with [age >= (30 + round(life-expectancy-blues / 10)) and age <= (150 + round(life-expectancy-blues / 20))]) / count blue-turtles) end ; Copyright 2011 Dario Sansone. All rights reserved. ; Supervisor: Pietro Terna, Faculty of Economics, University of Turin