globals [ country1 country2 multiplier-linked-jobs remittances-to-country1 remittances-to-country2 ] breed [ skilled a-skilled ] breed [ unskilled an-unskilled ] turtles-own [ skill reservation-wage wage employed remittances-sent parent ] patches-own [ skilled-wage unskilled-wage skilled-demand unskilled-demand ] to setup clear-all setup-countries reset-ticks end to setup-countries ; creates the world set country1 patches with [pxcor < 0] ask country1 [set pcolor green] set country2 patches with [pxcor >= 0] ask country2 [set pcolor yellow] end to go if (ticks = 150) [stop] create-people create-firms employ send-remittances demographic-trend tick end to create-people ; creates/eliminates people set-default-shape turtles "person" ifelse (n.skilled - count skilled) > 0 [create-skilled (n.skilled - count skilled) [setxy random-xcor random-ycor ; creation of skilled set color one-of [42 52] set employed 0]] ; they are either from country1 or from country2, and initially unemployed [ ask n-of (count skilled - n.skilled) skilled [die]] ; elimination of skilled ifelse (n.unskilled - count unskilled) > 0 ; same for unskilled [create-unskilled (n.unskilled - count unskilled) [ setxy random-xcor random-ycor set color one-of [42 52] set employed 0]] [ ask n-of (count unskilled - n.unskilled) unskilled [die]] ask skilled [ set skill 1 set reservation-wage skilled_reservation-wage] ; assign values to people's variables ask unskilled [set skill 0 set reservation-wage unskilled_reservation-wage] end to create-firms ; creates/destroys firms in country1 ifelse (n.firms_country1 - count country1 with [pcolor = grey]) > 0 ; creates firms [ask n-of (n.firms_country1 - count country1 with [pcolor = grey]) country1 with [pcolor != grey] [set pcolor grey]] [ask n-of (count country1 with [pcolor = grey] - n.firms_country1) country1 [set pcolor green]] ; destroys firms ifelse (n.firms_country2 - count country2 with [pcolor = grey]) > 0 ; same for country2 [ask n-of (n.firms_country2 - count country2 with [pcolor = grey]) country2 with [pcolor != grey] [set pcolor grey]] [ask n-of (count country2 with [pcolor = grey] - n.firms_country2) country2 [set pcolor yellow]] ask country1 with [pcolor = grey] [ set skilled-demand skilled_demand_country1 set unskilled-demand unskilled_demand_country1 set skilled-wage skilled_wage_country1 set unskilled-wage unskilled_wage_country1 ] ; assigns values to patches' variables ask country2 with [pcolor = grey] [ set skilled-demand (int (skilled_demand_country1 / 3)) set unskilled-demand (int (unskilled_demand_country1 / 3)) set skilled-wage (skilled_wage_country1 - skilled_wage_gap) set unskilled-wage (unskilled_wage_country1 - unskilled_wage_gap) ] ask patches with [pcolor != grey] [set skilled-demand 0 set unskilled-demand 0 set skilled-wage 0 set unskilled-wage 0] end to employ ask skilled [ ; employment dynamics for skilled if employed = 0 ; if unemployed [ set heading random 360 fd 1 ; look for a job ifelse (reservation-wage <= skilled-wage) and (skilled-demand > count skilled-here with [employed = 1]) ; when on a grey patch (firm), compare reservation wage to wage offered and see if there is a position avaliable in the firm [ set employed 1 set size 2 set wage skilled-wage fd 0 ; if yes, become employed, receive a wage, increase the size and stop moving if (xcor < 0) [ set multiplier-linked-jobs (multiplier-linked-jobs + Moretti's_multiplier) ]] ; Moretti's multiplier dynamics: when a skilled becomes employed, new jobs are created (both skilled and unskilled) according to Moretti's multiplier [ set heading random 360 fd 1 while [pcolor = grey] [fd 1] ] ; if not, keep moving and looking for a job ] if employed = 1 ; if employed [ifelse (reservation-wage <= skilled-wage) and (skilled-demand >= count skilled-here with [employed = 1]) ; see if these conditions are still satisfied [ set wage skilled-wage fd 0 ] ; if yes, remain in the firm [ set employed 0 set size 1 set wage 0 set heading random 360 while [pcolor = grey] [fd 1] ; if not, become unemployed, stop receiving a wage, reduce the size and start moving again if (xcor < 0) [ set multiplier-linked-jobs (multiplier-linked-jobs - Moretti's_multiplier) ]]] ; Moretti's multiplier operating in both directions ] ask unskilled [ ; employment dynamics for unskilled (same as for skilled but with no Moretti's multiplier) if employed = 0 [ set heading random 360 fd 1 ifelse (reservation-wage <= unskilled-wage) and (unskilled-demand > count unskilled-here with [employed = 1]) [ set employed 1 set size 2 set wage unskilled-wage fd 0] [ set heading random 360 fd 1 while [pcolor = grey] [fd 1] ] ] if employed = 1 [ifelse (reservation-wage <= unskilled-wage) and (unskilled-demand >= count unskilled-here with [employed = 1]) [ set wage unskilled-wage fd 0] [ set employed 0 set size 1 set wage 0 set heading random 360 while [pcolor = grey] [fd 1] ]] ] while [ multiplier-linked-jobs >= (unskilled_demand_country1 + skilled_demand_country1)] [ set n.firms_country1 (n.firms_country1 + 1) set multiplier-linked-jobs (multiplier-linked-jobs - (unskilled_demand_country1 + skilled_demand_country1)) ] ; in the next period creates new firms in country1 due to Moretti's multiplier while [ multiplier-linked-jobs <= (- (unskilled_demand_country1 + skilled_demand_country1))] [ set n.firms_country1 (n.firms_country1 - 1) set multiplier-linked-jobs (multiplier-linked-jobs + (unskilled_demand_country1 + skilled_demand_country1)) ] ; or destroys end to send-remittances ; remittances dynamics ask turtles-on country1 [ ; for country1 if (color = 42) and ( employed = 1) ; only employed immigrants can send remittances [ set remittances-sent ( wage / 100 * remittances%)]] ; remittances are calculated as "remittances%" of the salary ask turtles-on country2 [ ; same for country2 if (color = 52) and (employed = 1) [ set remittances-sent ( wage / 100 * remittances%)]] set remittances-to-country1 (remittances-to-country1 + (sum [remittances-sent] of turtles-on country2)) ; calculates the total level of remittances received by each country set remittances-to-country2 (remittances-to-country2 + (sum [remittances-sent] of turtles-on country1)) while [remittances-to-country1 >= remitt_needed_for_new_firm] ; in the next period creates new firms due to the receival of remittances [ set n.firms_country1 (n.firms_country1 + 1) set remittances-to-country1 (remittances-to-country1 - remitt_needed_for_new_firm)] while [remittances-to-country2 >= remitt_needed_for_new_firm] [ set n.firms_country2 (n.firms_country2 + 1) set remittances-to-country2 (remittances-to-country2 - remitt_needed_for_new_firm)] end to demographic-trend ; regulates demographic growth ifelse inverse-demographic-trend? [ask turtles-on country1 [ if (color = 42) and (employed = 1) and (parent = 0) [set parent 1 hatch random (max-n.sons + 1) [while [pcolor = grey] [ setxy random-xcor random-ycor set size 1 set employed 0 set wage 0 set remittances-sent 0 set parent 0]]]] ; only employed immigrants can have sons ask turtles-on country2 [ if (color = 52) and (employed = 1) and (parent = 0) [set parent 1 hatch random (max-n.sons + 1) [while [pcolor = grey] [ setxy random-xcor random-ycor set size 1 set employed 0 set wage 0 set remittances-sent 0 set parent 0]]]]] [ask turtles-on country1 [ if (color = 52) and (employed = 1) and (parent = 0) [set parent 1 hatch random (max-n.sons + 1) [while [pcolor = grey] [ setxy random-xcor random-ycor set size 1 set employed 0 set wage 0 set parent 0]]]] ; only employed locals can have sons ask turtles-on country2 [ if (color = 42) and (employed = 1) and (parent = 0) [set parent 1 hatch random (max-n.sons + 1) [while [pcolor = grey] [ setxy random-xcor random-ycor set size 1 set employed 0 set wage 0 set parent 0]]]]] set n.skilled count skilled ; updates the n. of skilled set n.unskilled count unskilled ; and the n. of unskilled end @#$#@#$#@ GRAPHICS-WINDOW 220 10 659 470 16 16 13.0 1 10 1 1 1 0 1 1 1 -16 16 -16 16 0 0 1 ticks 30.0 BUTTON 29 22 95 55 NIL setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 116 22 185 55 NIL go T 1 T OBSERVER NIL NIL NIL NIL 1 SLIDER 19 427 196 460 skilled_demand_country1 skilled_demand_country1 3 50 24 1 1 NIL HORIZONTAL TEXTBOX 20 505 203 547 Demands are demands per firm.\nBoth country2_demands are three times lower 11 0.0 1 SLIDER 17 468 197 501 unskilled_demand_country1 unskilled_demand_country1 3 100 60 1 1 NIL HORIZONTAL PLOT 682 21 1198 230 employment_levels time levels 0.0 100.0 0.0 1000.0 true true "" "" PENS "skilled employed_country1" 1.0 0 -2674135 true "" "plot count skilled-on country1 with [pcolor = grey]" "skilled employed_country2" 1.0 2 -955883 true "" "plot count skilled-on country2 with [pcolor = grey]" "unskilled employed_country1" 1.0 0 -13345367 true "" "plot count unskilled-on country1 with [pcolor = grey]" "unskilled employed_country2" 1.0 2 -11221820 true "" "plot count unskilled-on country2 with [pcolor = grey]" "unemployed_country1" 1.0 0 -16777216 true "" "plot count turtles-on country1 with [ pcolor != grey]" "unemployed_country2" 1.0 2 -7500403 true "" "plot count turtles-on country2 with [ pcolor != grey]" SLIDER 443 484 628 517 skilled_wage_country1 skilled_wage_country1 0 15 7 1 1 NIL HORIZONTAL SLIDER 443 527 629 560 unskilled_wage_country1 unskilled_wage_country1 0 10 2 1 1 NIL HORIZONTAL TEXTBOX 637 486 813 570 skilled_wage_country2 is \"skilled_wage_gap\" units less\n\nunskilled_wage_country2 is \"unskilled_wage_gap\" units less\n 11 0.0 1 SLIDER 234 486 420 519 skilled_reservation-wage skilled_reservation-wage 0 15 5 1 1 NIL HORIZONTAL SLIDER 234 525 419 558 unskilled_reservation-wage unskilled_reservation-wage 0 10 1 1 1 NIL HORIZONTAL SLIDER 690 382 862 415 remittances% remittances% 0 100 30 1 1 NIL HORIZONTAL TEXTBOX 871 379 1071 448 Remittances sent by each employed immigrant are expressed as a percentage of the salary perceived 11 0.0 1 PLOT 687 242 1196 362 GDPs time GDP 0.0 100.0 0.0 1000.0 true true "" "" PENS "country1_GDP" 1.0 1 -10899396 true "" "plot ((sum [wage] of turtles-on country1) - (sum [remittances-sent] of turtles-on country1))" "country2_GDP" 1.0 1 -1184463 true "" "plot ((sum [wage] of turtles-on country2) - (sum [remittances-sent] of turtles-on country2))" SWITCH 875 482 1083 515 inverse-demographic-trend? inverse-demographic-trend? 1 1 -1000 SLIDER 874 524 1086 557 max-n.sons max-n.sons 0 10 3 1 1 NIL HORIZONTAL TEXTBOX 26 70 195 252 country1 (green patches) is the more innovative country, i.e. \"the Attractor\".\ncountry2 (yellow patches) is the less innovative country.\nFirms are represented by grey patches.\ncountry1 citizens are dark green, country 2 citizens are dark yellow.\nEmployed people are twice the size of unemployed people. 11 0.0 1 SLIDER 688 426 914 459 remitt_needed_for_new_firm remitt_needed_for_new_firm 0 2000 1000 100 1 NIL HORIZONTAL TEXTBOX 925 430 1075 458 Represents the cost of setting up a new firm 11 0.0 1 SLIDER 444 568 628 601 skilled_wage_gap skilled_wage_gap 0 5 3 1 1 NIL HORIZONTAL INPUTBOX 17 256 90 316 n.unskilled 500 1 0 Number INPUTBOX 104 257 186 317 n.skilled 100 1 0 Number INPUTBOX 12 339 113 399 n.firms_country1 30 1 0 Number INPUTBOX 118 339 216 399 n.firms_country2 15 1 0 Number SLIDER 11 563 185 596 Moretti's_multiplier Moretti's_multiplier 0 15 5 1 1 NIL HORIZONTAL TEXTBOX 191 566 350 594 Actual Moretti's multiplier is 5:1 11 0.0 1 SLIDER 638 568 815 601 unskilled_wage_gap unskilled_wage_gap 0 5 1 1 1 NIL HORIZONTAL @#$#@#$#@ ## WHAT IS IT? The model, which is inspired to the work of Professor Enrico Moretti of the University of Berkeley, represents an attempt at analyzing the phenomenon of international qualified labor migration, driven by innovation, and its effects on the economic growth, both directly, on the country of destination of the workforce, and indirectly, on the country of origin. The possibility for non-qualified workers to migrate as well has been introduced to the model, to increase the realism of the simulation. ## HOW IT WORKS Initially, all the agents are unemployed and they are distributed randomly in the two countries. Country1 (green patches) is the country with the higher degree of innovation, country2 (yellow patches) is instead the less innovative one. Agents are divided randomly into country1 citizens (dark green) and country2 citizens (dark yellow). They also posses a different skill level: 0 for unskilled workers, 1 for skilled ones. When the go button is pressed, they start moving randomly around the world, seeking for a job. When they step on grey patches (firms) they compare their reservation-wage to the wage offered by the firm and decide whether or not to accept the job. Each firm has a maximum number of workers that can be hired, determined by the country in which they are settled. Once people become employed (visible in the model by their increase in size), they start sending remittances to their home country, which determines the creation of new firms. In country1, the creation of new firms is driven mostly by the so-called "Moretti's multiplier". Demographic growth can be observed in two flavours: Only employed locals can have sons (switch off) or only employed immigrants can have sons (switch on). ## HOW TO USE IT The setup command only creates the world, the go command creates people,firms and executes all the dynamic procedures (it is a forever button). The user can set the n.skilled and n.unskilled, along with n.firms in each country. He can also regulate the demand of labor (skilled and unskilled) for the firms as well as the wage offered and the wages gaps between the two countries. The reservation wages can be freely modified too. To choose which percentage of the wage each immigrant sends as remittance, the user can modify remittances%. The cost to create a new firm can be set by remitt_needed_for_new_firm. Demographic growth is regulated by the apposite switch, together with the slider max-n.sons, to set the maximum number of sons by each parent. Moretti's multiplier would actually be fixed at 5:1, but there is the possibility to raise or to reduce it through the apposite slider. The plot employment_levels shows the levels of employment by country and skill of the people, including the unemployment levels. The plot GDPs shows instead the GDPs of the two countries, using as a proxy the sum of the wages paid in the country minus the sum of the remittances sent. ## THINGS TO NOTICE Notice how people who get a job stops on the grey patches and become double size, while the others continue to move randomly in search for a job. Notice also how the total number of people increases over time due to the demographic trend, and how the number of firms evolves due to remittances and to Moretti's multiplier (this one only for country1). Finally, on the plots, notice the impact of migrations on the employment levels and on the GDPs of the countries. ## THINGS TO TRY The user might want to try different settings of the model, either by modifying the initial scenario or by manually introducing changes while the model is running, for example to simulate the effect of a crysis. The last one is in fact the biggest advantage of having all the main commands into the go procedure, so that a change in any of the sliders, inputs or switches is immediately visibile in a dynamic context. Just as an example the user could try to decrease the demand of labor by firms as well as the number of firms. Alternatively, he could modify the amount of remittances sent by each worker, or he could try different values for Moretti's multiplier, or again he could change the demographic trend and reduce/increase the maximum number of sons by each worker. ## EXTENDING THE MODEL A very interesting extension of the model could be to develop a dynamic for innovation on its own, by explicitely modeling the innovation gap between the two countries, instead of assuming it exogenous. Schooling system and/or R&D spending by firms could be used to endogenously determine the level of innovation in each country. Another interesting development of the model could be to analyze the impact of migrations on the demand for goods (which I only left in the foreground) and on the saving rates of people regarding intertemporal consumption decisions. ## CREDITS AND REFERENCES Enrico Moretti, 2012, "The new geography of jobs", Houghton Mifflin Harcourt. 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