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State of Rural Minnesota 2013-full report
 

State of Rural Minnesota 2013-full report

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The State of Rural Minnesota 2013 is a presentation produced annually by the Center for Rural Policy & Development in St. Peter, MN, showing how population, income, poverty, education, and many other ...

The State of Rural Minnesota 2013 is a presentation produced annually by the Center for Rural Policy & Development in St. Peter, MN, showing how population, income, poverty, education, and many other indicators vary across the state.

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    State of Rural Minnesota 2013-full report State of Rural Minnesota 2013-full report Presentation Transcript

    • State of Rural Minnesota Report 2013
    • Who we are In 1997, a group of rural Minnesota advocates came together to create a rural policy “think tank” that would provide policy makers, rural advocates and concerned citizens with an objective, unbiased and politically “unspun” examination of contemporary rural issues.  Based in St. Peter, Minn.  Non-partisan, non-profit policy research organization  Dedicated to providing Minnesota’s policy makers with an unbiased evaluation of issues from a rural perspective.  The Center is recognized as a leading resource for rural policy research and development.Center for Rural Policy & Development, 2013
    • A State of Diverse Regions   Ruralplexes: Regions based on common characteristics. Developed for the Center by former State Demographer Tom Gillaspy and State Economist Tom Stinson.   The State of Rural Minnesota uses these regions to show major characteristics and trends of Minnesota’s people and economy.Center for Rural Policy & Development, 2013
    • Growth of Minnesota’s regions, 1900 to 2010 450.0% 400.0% 350.0% 300.0% Metroplex 250.0% Southeast River Valley Southwestern Cornbelt 200.0% Northwest Valley 150.0% Up North Central Lakes 100.0% 50.0% 0.0% 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 -50.0%Center for Rural Policy & Development, 2013
    • Demographics Population change, 1960-2010 (U.S. Census) Population, Population, Region Percent change 1960 2010 Metroplex 1,854,630 3,634,786 96.0% Southeast River 507,663 552,682 8.9% Valley Southwestern 218,331 164,341 -24.7% Cornbelt Northwest Valley 271,849 292,150 7.5% Up North 359,839 363,617 1.0% Central Lakes 201,552 296,349 47.0% Minnesota 3,413,864 5,303,925 55.4%Center for Rural Policy & Development, 2013
    • Population change, 1990-2010 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   From 1990 to 2010, the state’s F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 population grew by nearly 1 :/(#/0 million, to 5.3 million. The most 24&5%*/01 2"43(&0 dramatic growth was seen in the *"+$0" <(($4%="/3 Twin Cities suburbs, stretching up */3#/0 8/0$ =&++ 6/33$% into the Central Lakes area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enter for Rural Policy & Development, 2013
    • Long-term population change, 1960-2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4 F&47"0 6")0&7$0 JA99"4+ 2",,   Looking at how the population has 23"B H$.#$4 changed since 1960 shows the :/(#/0 relentless shift from the rural 24&5%*/01 2"43(&0 counties to the urban and *"+$0" <(($4%="/3 suburban cores of the Twin Cities, */3#/0 8/0$ =&++ St. Cloud and Rochester. Sherburne County has seen the 6/33$% >4"0( 6&44/,&0 !"., -"0"9$. G&A13", ?($@$0, 8&C$ H$0(&0 !"#$"%&$()%*" most growth, increasing by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enter for Rural Policy & Development, 2013
    • Projected population change, 2010-2035 L<((6)0 E)64/7 I/J4)D (A4K))16 ;/86A/FF =($I)7<6 U4F(8/>< G)FJ G400<0?()0 B))J I/J4 L))9A<9A<0? E41I/J4 O(/69/ BF4/8M/(48   T)8>/0 ;/A0)>40 W722/81 B/66 Minnesota’s State Demographic BF/H U49J48 Center projects that population trends will continue much as they N<(J<0 B8)MK<0? B/8F()0 have: the western and southern K/140/ P((48Q/<F K<FJ<0 G<04 counties will continue to lose population while growth will Q)11 ;<FF4 continue to radiate out from the R8/0( ;)88<6)0 I/96 L/0/249 5)7?F/6 !"#$"%&$()%*" =(43406 G)@4 =(4/806 U40()0 O6/0(< Twin Cities and north into the Q8/34864 !"#$%&()!#$*& central lakes region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enter for Rural Policy & Development, 2013
    • Population projections Projected population change, 2010-2035 (Minn. State Demographic Center). Projected pop., Region Population, 2010 Percent change 2035 Metroplex 3,634,786 4,569,350 25.7% Southeast River 552,682 613,890 11.1% Valley Southwestern 164,341 160,740 -2.2% Cornbelt Northwest Valley 292,150 333,790 14.3% Up North 363,617 398,300 9.5% Central Lakes 296,349 369,420 24.7% Minnesota 5,303,925 6,446,270 21.5%Center for Rural Policy & Development, 2013
    • Population projections, 2010-2035 30.0% 25.7% 24.7% 25.0% 21.5% 20.0% 14.3% 15.0% 11.1% 9.5% 10.0% 5.0% -2.2% 0.0% -5.0%Center for Rural Policy & Development, 2013
    • Median Age, 2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   F&47"0 6")0&7$0 JA99"4+ 2",, Median age—the age at which half 23"B H$.#$4 the population is older and half is younger—gives an indication of :/(#/0 24&5%*/01 2"43(&0 the overall age of the population in *"+$0" <(($4%="/3 */3#/0 8/0$ an area. Fast-growing counties with young families, large =&++ 6/33$% institutions of higher education, or >4"0( 6&44/,&0 !"., -"0"9$. G&A13", !"#$%&()"*+"%,-. ?($@$0, 8&C$ H$0(&0 ;,"0(/ large minority populations tend to ?($"40, !"#$%&()* have a lower median age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enter for Rural Policy & Development, 2013
    • Population under age 18, 2010 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4 F&47"0 6")0&7$0 JA99"4+ 2",,   The highest percentage of people 23"B H$.#$4 under age 18 is concentrated in :/(#/0 the Twin Cities ring suburbs, but 24&5%*/01 2"43(&0 also in counties like Mahnomen, *"+$0" <(($4 ="/3 Dodge and Roseau. For the state */3#/0 8/0$ =&++ as a whole, approximately one quarter of the population is 6/33$ >4"0( 6&44/,&0 !"., -"0"9$. G&A13", !"#$"%&() ?($@$0, 8&C$ H$0(&0 &(&*+,(,-+*&.(% under age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enter for Rural Policy & Development, 2013
    • Projected population age 19 and under, 2035 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   F&47"0 6")0&7$0 JA99"4+ 2",, The population age 19 and under 23"B H$.#$4 is projected to stay highest in the Twin Cities. :/(#/0 24&5%*/01 2"43(&0 *"+$0" <(($4%="/3 */3#/0 =&++ 8/0$   Some rural counties are projected >4"0( 6&44/,&0 6/33$% !"., to have higher rates of young -"0"9$. G&A13", !"#$"%&() people as well, most likely due to &(&*+,(,-+*&.(% =4"@$4,$ ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ !"##$%&($)*+,- the presence of a college or a large minority population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enter for Rural Policy & Development, 2013
    • Population 65+, 2010 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   The higher percentage of seniors F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 remaining in rural counties has :/(#/0 many implications for state and 24&5%*/01 2"43(&0 local government, such as a *"+$0" <(($4%="/3 demand for increased levels of */3#/0 8/0$ =&++ 6/33$% service to those living on low and/ or fixed incomes. >4"0( 6&44/,&0 !"., !"#$"%&() -"0"9$. G&A13", &(&*+,(,-+*&.(% H$0(&0 ?($@$0, 8&C$ ;,"0(/ =4"@$4,$ ?($"40, !"##$%&($)*+,- *",)/01(&0 2)/,"1& H/1% ?)$49A40$ ?(&0$ ?5/( :0&#" )*+,-$%.$),+/- -"0+/B&)/ 6$$#$4 )0+1-$%.$)2+3- 2)/CC$5" ,M *4/1)( E"7 !".%NA/%8"43$ J$00$C/0 )2+,-$%.$*1+/- 6.!$&+ E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ *)+1-$(4$5.6" ?/93$B !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 K/337&4$ J&A,(&0 7%$#.89:"; <+=+$>"(#8#$?89"8 @.A8B%C.($D#%CE%"$@9.F9E $G$>"(%"9$H.9$I89B$@.BC:J$(4$7"6"B.AE"(%Center for Rural Policy & Development, 2013
    • Projected population age 65+, 2035 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   While the trend in aging is F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 projected to continue through :/(#/0 2035 much as it has, the growth in 24&5%*/01 2"43(&0 the aging population may be offset *"+$0" <(($4%="/3 in some southern and western */3#/0 8/0$ =&++ 6/33$% counties by the presence of minorities and immigrants and by >4"0( 6&44/,&0 !"., -"0"9$. G&A13", !"#$"%&() &(&*+,(,-+*&.(% ?($@$0, 8&C$ H$0(&0 ;,"0(/ colleges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enter for Rural Policy & Development, 2013
    • Natural rate of increase, 2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Natural increase is simply the F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 number of births minus the :/(#/0 number of deaths. The highest 24&5%*/01 2"43(&0 increases have been in the western *"+$0" <(($4%="/3 suburbs, Dodge County, Olmsted */3#/0 8/0$ =&++ 6/33$% County and in the north central counties. Meanwhile, several rural 6&44/,&0 >4"0( !"., !"#$%"&()*%+",+ -"0"9$. G&A13", -+%./000%+,(1+)#, ?($@$0, 8&C$ H$0(&0 ;,"0(/ counties showed a natural ?($"40, !"#$"%&" decrease. Natural increase, =4"@$4,$ *",)/01(&0 2)/,"1& H/1% ?)$49A40$ ?(&0$ ()*+),(- ?5/( -"0+/B&)/ 6$$#$4 :0&#" however, this does not take into ,(.)*+)/(0 2)/CC$5" consideration immigration, which ,M *4/1)( E"7 -()*+)1(0 !".%NA/%8"43$ E$0@/33$ 6.!$&+ 2"4@$4 J$00$C/0 is driving population growth in 2()%34)%5+6" some rural counties. D$33&5%6$+/./0$ ?/93$B !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 !%*%)&+7$#"8 9(:()!";%$*<"3*)+=)>"%?*@ A337%?)>"%?*@):7<<%$B C)D"3*"$)=+$)E7$%?)F+?G#B)%34)!"6"?+;<"3*Center for Rural Policy & Development, 2013
    • Minorities in Minnesota, 2010 Minnesota 16.9% Central Lakes 6.8% Up North 10.7% Northwest Valley 7.2% Southwestern Cornbelt 11.2% Non-white population as percentage of total Southeast River Valley 8.9% population (U.S. Census Bureau, Metroplex 20.7% 2010). 0.0% 5.0% 10.0% 15.0% 20.0% 25.0%Center for Rural Policy & Development, 2013
    • Decrease in Increase in Change in County white minority total population population population Clearwater -116 502 386 Fillmore -243 332 89 Hennepin -88,200 208,194 119,994 Kandiyohi -1,093 4,571 3,478 Lyon -1,691 2,759 1,068 Fifteen counties that experienced population growth Mahnomen -1,129 1,498 369 between 1990 and 2010 due to growth in their minority Mower -3,753 5,531 1,778 populations (U.S. Census Nobles -4,953 6,233 1,280 Bureau, 2010). Twelve of them are not in a Metropolitan Pennington -175 799 624 Statistical Area. Ramsey -80,755 103,630 22,875 Roseau -59 662 603 Sibley -352 1,212 860 St. Louis -6,678 8,691 2,013 Todd -137 1,669 1,532 Waseca -506 1,563 1,057Center for Rural Policy & Development, 2013
    • Distribution of people of color, 2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Minnesota’s minority population F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 has more than doubled since :/(#/0 1990, increasing from 6.3% of the 24&5%*/01 2"43(&0 total population to approximately *"+$0" <(($4%="/3 17% in 2010. */3#/0 8/0$ =&++ 6/33$% 6&44/,&0 !"#$"%&()   Counties in the north tend to have >4"0( !"., -"0"9$. G&A13", &(&*+,(,-+*&.(% =4"@$4,$ ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ !"##$%&($)*+, large Native American populations; Latinos and Somalis make up the *",)/01(&0 2)/,"1& H/1% ?)$49A40$ ?(&0$ )*+,$%-$+*., largest minority groups in western ?5/( -"0+/B&)/ :0&#" 6$$#$4 /*0,$%-$1*), 2)/CC$5" and southern Minnesota. ,M *4/1)( E"7 !".%NA/%8"43$ J$00$C/0 1*+,$%-$22*., 6.!$&+ E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ 23*0,$(4$5-6" ?/93$B !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 7%$#-89:"; <*=*$>"(#8#$?89"8 @$>"(%"9$A-9$B89C$D-CE:F$(4$7"6"C-GH"(%Center for Rural Policy & Development, 2013
    • Change in the distribution of people of color, 1990-2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Between 1990 and 2010, northern F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 counties’ Native American :/(#/0 populations remained relatively 24&5%*/01 2"43(&0 stable. Some western and *"+$0" <(($4%="/3 southern counties saw dramatic */3#/0 8/0$ =&++ 6/33$% !"#$"%&$()%*" growth with the in-migration of Latinos, Laotians, Somalis, >4"0( 6&44/,&0 !"., -"0"9$. G&A13", !"!#$%&$()")## ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ *!"!#$%&$))")# Sudanese, Hmong and other groups. However, some of the =4"@$4,$ *",)/01(&0 2)/,"1& H/1% ?(&0$ ?)$49A40$ +!!"!#$%&$+))")# ?5/( -"0+/B&)/ 6$$#$4 :0&#" ,!!"!#$%&$())")# highest growth was in the ring 2)/CC$5" suburbs of the Twin Cities. ,M *4/1)( *!!"!#$.8A$.E&B3 E"7 !".%NA/%8"43$ J$00$C/0 6.!$&+ E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ ?/93$B !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 -.%.$/&01234 5"6"$738/0/$9013.0 :$738%31$;&1$<01.=$>&=?2@$.8A$-3B3=&CD38%Center for Rural Policy & Development, 2013
    • Population in poverty, all ages, 2011 02--$+3 E+$)"A "()*+,* -%)*.++/$ !"#$%"&& !"#$%"&& ?-M*+A2$ H)&-#"72 8+&( 8)33234-+3 5++( "() 0++1%21%234 E)/*"() ;-"$1"   The poverty rate for Minnesota in 5&)"#6"-)# F+#7"3 !"%3+7)3 JA99"#/ 5"$$ 2011 was estimated at 11.8% 5&"B H)1()# compared to 15.9% for the United States as a whole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enter for Rural Policy & Development, 2013
    • Children in poverty, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   The percentage of children under F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 the age of 18 in poverty in :/(#/0 Minnesota was estimated at 24&5%*/01 2"43(&0 15.3% in 2011. Those counties *"+$0" <(($4%="/3 with the highest rates of poverty */3#/0 8/0$ =&++ 6/33$% may not correspond with the highest rates of public assistance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enter for Rural Policy & Development, 2013
    • Economics Regional per-capita earned income (Bureau of Economic Analysis, 2011). Per-capita Region earnings Metroplex $57,040 Southeast River Valley $41,442 Southwestern Cornbelt $44,758 Northwest Valley $36,766 Up North $41,661 Earnings by place of work divided by Central Lakes $33,425 workforce. Minnesota $52,184Center for Rural Policy & Development, 2013
    • Median household income, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4 F&47"0 6")0&7$0   In 2011, Minnesota’s estimated JA99"4+ 2",, median household income was 23"B H$.#$4 $58,476. Median household income is a frequently used :/(#/0 24&5%*/01 2"43(&0 measure showing the point at *"+$0" <(($4 ="/3 which half the households in the */3#/0 group have a higher income and 8/0$ =&++ >4"0( 6&44/,&0 6/33$ !"., half have a lower income. Carver -"0"9$. G&A13", !"#$%&()*+"(),# $&-)."/012"%3"+4$.%4"5 County had the highest estimated median household income, at H$0(&0 ?($@$0, 8&C$ ?($"40, ;,"0(/ =4"@$4,$ !"#$%&(()*** $83,415, while Wadena County *",)/01(&0 2)/,"1& H/1 ?(&0$ ?)$49A40$ (()***&+$&(,)--- recorded the lowest, at $35,307. ?5/( -"0+/B&)/ :0&#" 6$$#$4 (.)***&+$&(-)--- 2)/CC$5" ,M *4/1)( E"7 !".%NA/%8"43$ J$00$C/0 /*)***&+$&/,)--- 6.!$&+ E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ /.)***&012&03$4" ?/93$B !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 50+0&6$789": ;<=<&>"1676&!78"07 ?@"8A901&>$@@71A+B&=784"B C&>"1+"8&D$8&E780#&F$#A9B&012&5"4"#$G@"1+Center for Rural Policy & Development, 2013
    • Average earnings, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Average earnings per member of F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 the workforce. :/(#/0 24&5%*/01 2"43(&0   The highest per-worker earnings *"+$0" <(($4%="/3 */3#/0 =&++ 8/0$ are found in the southern part of >4"0( 6&44/,&0 6/33$% !"., the state, particularly in the Twin Cities and in the farm-rich -"0"9$. G&A13", !"#$%&##%$()(&* =4"@$4,$ ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ !"##$%&($)*+,--- counties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enter for Rural Policy & Development, 2013
    • Average earnings in the manufacturing sector, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Typically, manufacturing is one of F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 the better paying industries. It has :/(#/0 a strong presence in rural 24&5%*/01 2"43(&0 Minnesota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enter for Rural Policy & Development, 2013
    • Workforce in the manufacturing sector, 2011 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   F&47"0 6")0&7$0 JA99"4+ 2",, Despite losing nearly 50,000 23"B H$.#$4 manufacturing jobs between 2005 and 2009, Minnesota still has a :/(#/0 24&5%*/01 2"43(&0 number of counties—mostly rural— *"+$0" <(($4%="/3 */3#/0 8/0$ where employment is concentrated in !"#$"%&(")*+),*#-+*#$") manufacturing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enter for Rural Policy & Development, 2013
    • Average earnings in farming, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4 F&47"0 6")0&7$0 JA99"4+ 2",,   Farming has had a strong 23"B H$.#$4 presence in Minnesota historically :/(#/0 and continues to do so today. The 24&5%*/01 2"43(&0 distribution of wealth from *"+$0" <(($4%="/3 */3#/0 8/0$ farming is apparent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enter for Rural Policy & Development, 2013
    • Workforce in farming, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",."   23$"45"($4 F&47"0 6")0&7$0 Only about 2.5% of Minnesota’s JA99"4+ 2",, workforce is employed directly in 23"B H$.#$4 :/(#/0 farming, but that figure varies significantly across the state. 24&5%*/01 Some counties have 20% or more 2"43(&0 *"+$0" <(($4%="/3 */3#/0 =&++ 8/0$ of their workforce working directly >4"0( 6&44/,&0 6/33$% !"., in farming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enter for Rural Policy & Development, 2013
    • Average earnings in the retail sector, 2011 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4 F&47"0 6")0&7$0   Earnings from retail tend to be some of the lowest of any JA99"4+ 2",, industry. The highest retail 23"B H$.#$4 :/(#/0 24&5%*/01 earnings cluster around the Twin 2"43(&0 Cities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enter for Rural Policy & Development, 2013
    • Workforce in the retail sector, 2011 Title  here Kittson Roseau Lake of the Woods Marshall St. Louis Beltrami Polk Pennington Cook Lake Koochiching Red Lake Itasca Clearwater Norman Mahnomen Hubbard Cass   In Minnesota, approximately 10% Clay Becker Aitkin of the workforce works in the retail Crow Wing sector. Retail centers can be seen around the state. Although the Twin Carlton Wadena Otter Tail Wilkin Todd Pine Cities has some of the highest total Morrison Mille Lacs earnings in retail, its low Percentage of workforce Grant Kanabec Douglas employed in retail percentage of workforce in retail Traverse Stevens Pope Stearns Benton Isanti Less than 9.0% compared to the rest of the state shows a more diversified economy. Washington Chisago Big Sherburne Stone Swift Anoka 9.0% to 9.9% Kandiyohi Meeker 10.0% to 10.9% Chippewa s. Wright Ram Lac Qui Parle Hennepin 11.0% to 12.9% McLeod Renville Carver Yellow Medicine 13.0% and above Sibley Lincoln Lyon Scott Dakota Redwood Nicollet Rice Le Sueur Goodhue Wabasha Brown Pipestone Steele Dodge Waseca Murray Watonwan Olmsted Winona Cottonwood Blue Earth Rock Nobles Fillmore Houston Jackson Martin Faribault Freeborn Mower Data source: U.S. Department of Commerce Bureau of Economic Analysis © Center for Rural Policy and DevelopmentCenter for Rural Policy & Development, 2013
    • Average earnings in the government sector, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, % 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Government is a major employer in F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 many rural counties. The highest :/(#/0 average salaries tend to cluster in 24&5%*/01 2"43(&0 the metro area even though *"+$0" <(($4%="/3 government makes up a smaller */3#/0 8/0$ =&++ 6/33$% segment of the workforce in these counties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enter for Rural Policy & Development, 2013
    • Workforce in the government sector, 2011 !"#$%&%(% -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Government is a major employer in F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 many rural counties, where the :/(#/0 need for services is 24&5%*/01 2"43(&0 disproportionate to the population. *"+$0" <(($4 ="/3 In Minnesota in 2010, 12.2% of */3#/0 8/0$ =&++ 6/33$ the workforce worked in the government sector. Mahnomen 6&44/,&0 !"., !"#$"%&(")*+),*#-+*#$") >4"0( -"0"9$. G&A13", "./0*1"2)3%)(*4"#%."%&) ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ County had the highest percentage, !"##$%&($)*+,- at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enter for Rural Policy & Development, 2013
    • Self-employed businesses, 2009 Title  here Kittson Roseau Lake of the Woods Marshall St. Louis Beltrami Polk Pennington Cook Lake Koochiching Red Lake Itasca Clearwater   Business establishments of fewer Norman Mahnomen Hubbard Cass Clay Becker than 10 employees make up nearly Aitkin three-quarters of the state’s Crow Wing Carlton businesses. Self-employed Wadena Otter Tail businesses concentrate in the Twin Wilkin Pine Todd Mille Cities, but also in central and north central Minnesota. These Grant Morrison Lacs Kanabec Douglas Per 1,000 Residents Stevens Pope Stearns Benton Isanti businesses have generated enough Fewer than 63.0 income to pay taxes but do not Traverse Washington Chisago Big Sherburne Stone 63.0 to 68.9 Swift Kandiyohi Meeker Anoka have any paid employees. 69.0 to 75.9 Chippewa s. Wright Ram Lac Qui Parle Hennepin 76.0 to 84.9 McLeod Renville Carver Yellow Medicine 85.0 and above Sibley Lincoln Lyon Scott Dakota Redwood Nicollet Rice Le Sueur Goodhue Wabasha Brown Pipestone Steele Dodge Waseca Murray Watonwan Olmsted Winona Cottonwood Blue Earth Rock Nobles Fillmore Houston Jackson Martin Faribault Freeborn Mower Data source: U.S. Census Bureau Nonemployer Statistics © Center for Rural Policy and DevelopmentCenter for Rural Policy & Development, 2013
    • Change in number of self-employed businesses, 2005-2009 Title  here Kittson Roseau Lake of the Woods Marshall St. Louis Beltrami Polk Pennington Cook Lake Koochiching Red Lake Itasca Clearwater   Despite the difficult economic Norman Mahnomen Hubbard Cass Clay Becker climate between 2005 and 2009, Aitkin about a quarter of Minnesota’s Crow Wing Carlton counties managed to see an Wadena Otter Tail increase in the number of self- Wilkin Pine Todd Mille employed businesses. Grant Morrison Lacs Percent change Kanabec Douglas Less than -11.0% Benton Stevens Pope Stearns Isanti Traverse -10.9% to -7.0% Washington Chisago Big Sherburne Stone Swift Kandiyohi Anoka -6.9% to -3.0% Meeker -2.9% to 0.0% Chippewa s. Wright Ram Lac Qui Parle McLeod Hennepin 0.1% to 9.9% Renville Carver Yellow Medicine 10.0% and above Sibley Lincoln Lyon Scott Dakota Redwood Nicollet Rice Le Sueur Goodhue Wabasha Brown Pipestone Steele Dodge Waseca Murray Watonwan Olmsted Winona Cottonwood Blue Earth Rock Nobles Fillmore Houston Jackson Martin Faribault Freeborn Mower Data source: U.S. Census Bureau Nonemployer Statistics © Center for Rural Policy and DevelopmentCenter for Rural Policy & Development, 2013
    • Average receipts from self- employed businesses, 2009 Title  here Kittson Roseau Lake of the Woods Marshall St. Louis Beltrami Polk Pennington Cook Lake Koochiching Red Lake Itasca Clearwater   Receipts from self-employed Norman Mahnomen Hubbard Cass Clay Becker businesses, the income generated Aitkin by the business, ranged from an Crow Wing Carlton average of $27,105 in Yellow Wadena Otter Tail Medicine County to $70,144 in Wilkin Pine Todd Mille Wilkin County. Grant Morrison Lacs Average per Kanabec Douglas establishment Benton Stevens Pope Stearns Isanti Traverse Less than $31,000 Washington Chisago Big Sherburne Stone Swift Anoka $31,000 to $32,999 Kandiyohi Meeker $33,000 to $34,999 Chippewa s. Wright Ram Lac Qui Parle Hennepin $35,000 to $36,999 McLeod Renville Carver Yellow Medicine $37,000 and above Sibley Lincoln Lyon Scott Dakota Redwood Nicollet Rice Le Sueur Goodhue Wabasha Brown Pipestone Steele Dodge Waseca Murray Watonwan Olmsted Winona Cottonwood Blue Earth Rock Nobles Fillmore Houston Jackson Martin Faribault Freeborn Mower Data source: U.S.Census Bureau Nonemployer Statistics © Center for Rural Policy and DevelopmentCenter for Rural Policy & Development, 2013
    • Women in the workforce, 2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   In 2010, the U.S. Census F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 estimated that 66.5% of women :/(#/0 15 years of age and older 24&5%*/01 2"43(&0 participated in the workforce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enter for Rural Policy & Development, 2013
    • Projected change in workforce- age population, 2010-2035 Age 15-65 Age 15-44Center for Rural Policy & Development, 2013
    • Average annual unemployment, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   During the recent recession, F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 Minnesota’s average annual :/(#/0 unemployment rate rose from 24&5%*/01 2"43(&0 4.6% in 2007 to 8.0% in 2009. *"+$0" <(($4%="/3 The seasonally adjusted */3#/0 8/0$ =&++ 6/33$% unemployment rate for December 2012 was 5.5% for the state, but >4"0( 6&44/,&0 !"., !"#$%&#%(()%* -"0"9$. G&A13", )(#+,*-.+#(/$%/# ?($@$0, 8&C$ H$0(&0 ;,"0(/ rates vary greatly from county to ?($"40, !"##$%&($)*+, county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enter for Rural Policy & Development, 2013
    • Median Home Value, 2010 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Median home value is based on F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 the median sales price of existing :/(#/0 homes. 24&5%*/01 2"43(&0 *"+$0" <(($4%="/3 */3#/0 =&++ 8/0$   The data for 2010 reflects the 6&44/,&0 6/33$% !"., housing market in an economic !"#$%&()*"+%,-" >4"0( crisis. At its peak in 2007, the -"0"9$. G&A13", =4"@$4,$ ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ !"##$%&($)*+,+++ median home value in Minnesota )*+,+++$%-$).+/,/// was $200,000; in 2008, *",)/01(&0 2)/,"1& H/1% ?)$49A40$ ?(&0$ )..+,+++$%-$).01,1// $190,000; $174,600 in 2009; and ?5/( -"0+/B&)/ :0&#" 6$$#$4 ).02,+++$%-$).21,1// 2)/CC$5" $169,900 in 2010. ,M *4/1)( E"7 !".%NA/%8"43$ J$00$C/0 6.!$&+ ).22,+++$(3$4-5" E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ ?/93$B 6-$3% !/0.&30 !B&0 ?.&(( G"#&(" E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 7%$#-89:"; <=(("#-%$>%%"$7"?-@9A&=:$B"(%"9 C$B"(%"9$D-9$E89F$G-F=:H$(3$7"5"F-A?"(%Center for Rural Policy & Development, 2013
    • Social Security payments per capita, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ E$+%!"#$ -&&.)/.)/01 ;(",." 23$"45"($4   Social Security payments consist F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 of payments to retired and :/(#/0 disabled persons, their 24&5%*/01 2"43(&0 dependents and survivors, but *"+$0" <(($4%="/3 does not include medical */3#/0 8/0$ =&++ 6/33$% payments. The average monthly Social Security payment in >4"0( 6&44/,&0 !"., -"0"9$. G&A13", !"#$%&()%*(+")," ?($@$0, 8&C$ H$0(&0 ;,"0(/ Minnesota in 2011 was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enter for Rural Policy & Development, 2013
    • Public assistance payments per capita, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ E$+%!"#$ -&&.)/.)/01 ;(",." 23$"45"($4   The average public assistance F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 payment for Minnesota was $705 :/(#/0 in 2011. 24&5%*/01 2"43(&0 *"+$0" <(($4%="/3 */3#/0 =&++ 8/0$   For the purposes of this report, >4"0( 6&44/,&0 6/33$% !"., public assistance includes family assistance, food stamps (SNAP), -"0"9$. G&A13", !"#$%&()%*(+")," =4"@$4,$ ?($@$0, 8&C$ ?($"40, H$0(&0 ;,"0(/ !"##$%&($)**+ general assistance, supplemental security payments and other *",)/01(&0 2)/,"1& H/1% ?)$49A40$ ?(&0$ )**+$%,$)-./ income maintenance benefits. It ?5/( -"0+/B&)/ :0&#" 6$$#$4 )-*+$%,$)01. 2)/CC$5" does not include medical ,M *4/1)( E"7 !".%NA/%8"43$ )01*$%,$)2./ payments or farm program J$00$C/0 6.!$&+ E$0@/33$ 2"4@$4 D$33&5%6$+/./0$ )2*+$(3$4,5" !/0.&30 !B&0 ?/93$B ?.&(( G"#&(" payments. E$+5&&+ F/.&33$( E/.$ !$%?A$A4 >&&+)A$ *"9",)" H4&50 8/C$,(&0$ ?($$3$ G&+1$ *",$." 6A44"B *"(&05"0 <37,($+ */0&0" 2&((&05&&+ H3A$%L"4() E&.# F&93$, K/337&4$ J&A,(&0 I".#,&0 6"4(/0 K"4/9"A3( K4$$9&40 6&5$4 6%$#,789": ;<=<$6">8%?"(%$,@$A,??"89" B78"7$,@$C9,(,?D9$E(FG#D# H$A"(%"8$@,8$I78F$J,FD9G$(3$6"5"F,>?"(%Center for Rural Policy & Development, 2013
    • Health Percent of Region population enrolled in MinnesotaCare Percent of population enrolled in MinnesotaCare, Metroplex 1.7% based on average monthly enrollment for 2009 Southeast River Valley 2.1% (Minnesota Department of Human Services, 2011) Southwestern Cornbelt 2.5% Northwest Valley 3.1% Up North 3.2% Central Lakes 4.4% Minnesota 2.1%Center for Rural Policy & Development, 2013
    • Population insured through Medicare, 2011 -/((,&0 E&,$"A !"#$%&% ()$%*&&+, 6"4,)"33 ?(M%!&A/, H$3(4"7/ 8&3# 8$00/01(&0 2&&# !"#$ -&&.)/.)/01 E$+%!"#$ ;(",." 23$"45"($4   Recipients of Medicare include F&47"0 6")0&7$0 JA99"4+ 2",, 23"B H$.#$4 individuals who are 65+, but also :/(#/0 certain individuals with disabilities 24&5%*/01 2"43(&0 and people with permanent kidney *"+$0" <(($4%="/3 failure with dialysis needs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enter for Rural Policy & Development, 2013
    • Nursing home beds Nursing homes per 1,000 residents and 1,000 seniors (Minn. Department of Health, 2011) Nursing home Nursing home beds Total nursing Region beds per 1,000 per 1,000 seniors home beds residents (age 65+) Metroplex 16,451 4.5 41.2 Southeast River Valley 4,882 8.8 55.6 Southwestern Cornbelt 2,252 13.7 72.2 Northwest Valley 3,166 10.8 61.3 Up North 2,799 7.7 47.6 Central Lakes 1,862 6.3 33.9 Minnesota 31,412 5.9 46.0Center for Rural Policy & Development, 2013
    • EducationStudent-teacher ratio (Minnesota Department of Education, 2010-2011). Total teachers or Students perRegion Total enrollment Full-Time teacher EquivalentMetroplex 547,272 32,345.7 16.9Southeast River 79,719 5,288.6 15.1ValleySouthwestern 26,097 1,946.8 13.4CornbeltNorthwest Valley 42,618 2,948.0 14.5Up North 49,361 3,235.3 15.3Central Lakes 46,403 3,025.9 15.3Minnesota 791,470 48,790.2 16.2Center for Rural Policy & Development, 2013
    • Total School Enrollment, 2011-2012   Minnesota’s public school districts had 839,426 students enrolled in the 2011-2012 school year, up nearly 4,800 students from one year earlier. !"#$%&"()%*($+"*+,"   14 districts: 10,000+ students *+#,-.- !"#$#%&"""   24 districts: 5,000-9,999 %&""%#$#&"""   120 districts: 1,000-4,999 &""%#$#%"&""" %"&""%#$#("&"""   177 districts: less than 1,000 ("&""%#$#)"&""" !"#"$%&()*+ ,-..*%&#"$!*/"(#0*.#$&1$23)"#-&. 4 5*.#*($1&($6("7$8&7-)9$".3$!*:*7&/0*.#Center for Rural Policy & Development, 2013
    • Total Charter School Enrollment, 2011-2012 !"#$%&"()%*($+"*+," !"#$%&% #(#)* )+#(#, ,-#(#**, **)#(#.**+ !"##$%&%("!)! /%&%#0"12345 678840"&%#/49%2&:48&#";#<$13%&7"8 =#>48&42#;"2#?12%@#A"@73B#%8$#/4C4@"9:48&Center for Rural Policy & Development, 2013
    • Graduation Rates, 2009-2010   To calculate the graduation rate here, the number of graduates was divided by the number of ninth-graders four years earlier, adjusting for students dropping out or leaving the district. !"#$%#&()*+#&, !"#$%&%   Districts with graduating classes ()*+#,#-(+ under 40 were not included. -().+#,#-*+ -*).+#,#/(+ /().+#,#/*+ /*).+#,#.((+ 0%&%#1"23456 789951"&%#05:%3&;59&#"<#=$24%&8"9 >#?59&53#<"3#@23%A#B"A84C#%9$#05D5A":;59&Center for Rural Policy & Development, 2013
    • Dropout Rates, 2009-2010   Factors contributing to high dropout rates include low income levels and the presence of minority students. Many districts are working hard to help these at-risk students to stay in school. !"#$#%&()*+, !"#$%&%   For schools to receive a dropout ()*#+#,* rate, the cohort total must be at ,(,*#+#,(-* least 40 students. ,(.*#+#/(-* /(.*#+#0* 0(,*#+#-1()* 2%&%#3"45678 9:;;73"&%#27<%5&=7;&#">#?$46%&:"; @#A7;&75#>"5#B45%C#D"C:6E#%;$#27F7C"<=7;&Center for Rural Policy & Development, 2013
    • Student-teacher ratio, 2011-2012   The student-teacher ratio is often used as an indicator of class size. !"#$%&"()%*(+%,-.%* !"#$%&% ()#*#+,(- +,(.#*#+(, +(+#*#+/(, +/(+#*#+0(, +0(+#*#-(. 1%&%#2"34567 89::62"&%#16;%4&<6:&#"=#>$35%&9": ?#@6:&64#="4#A34%B#C"B95D#%:$#16E6B";<6:&Center for Rural Policy & Development, 2013
    • Students of color, 2011-2012   The diversity of students continues to rise in the core Twin Cities districts and in suburban districts. While most of rural Minnesota remains white, pockets of diversity !"#$"%&()&(&*+ can be found around the state. "%#(++,"%& Native American students make up !"#$%&% this population in the northern (#)#*( districts, while southern districts *+,(#)#,( are home to largely immigrants of ,+,(#)#-*( Latino, African and Asian origin. -*+,(#)#.*( .*+,(#)#,( /%&%#0"12345 678840"&%#/49%2&:48&#";#<$13%&7"8 =#>48&42#;"2#?12%@#A"@73B#%8$#/4C4@"9:48&Center for Rural Policy & Development, 2013
    • Languages spoken at home, 2011-2012   Understanding the variety of languages spoken at home is important for effective curriculum design. St. Paul and Anoka- Hennepin had the largest number !"#$%&() of languages spoken at home (114 *+,-"+-%../(0%, and 96 respectively), followed by !"#$%&% Rosemount-Apple Valley-Eagan #(#) (85). *#(#) *#(#+, +#(#-* -.#(#- /%&%#0"12345 678840"&%#/49%2&:48&#";#<$13%&7"8 =#>48&42#;"2#?12%@#A"@73B#%8$#/4C4@"9:48&Center for Rural Policy & Development, 2013
    • Free lunch eligibility, 2010-2011   For the state of Minnesota, 37.2% of students were eligible for free or reduced-price lunch in the 2010-2011 school year. Since recipients’ families must meet !"#$"%&(")*+),&-."%&,) "/0(01/")+*#)+#"")*#) certain income guidelines to #".-$".)/-%$2 qualify, free and reduced-price !"#$%&% lunch can be a good proxy for ()*#+#,-(,* poverty rates. ,-(.*#+#./(* ./(0*#+#1* 1(2*#+#/3(0* /3()*#+#233* 4%&%#5"6789: ;<==95"&%#49>%7&?9=&#"@#A$68%&<"= B#C9=&97#@"7#D67%E#F"E<8G#%=$#49H9E">?9=&Center for Rural Policy & Development, 2013
    • Student Mobility Index, 2010-2011   High mobility is considered detrimental to a student’s achievement. Poverty, unemployment, and an unstable home life are all factors in student mobility. !"#$%&"()*+,+"- !"#$%&% (#)#*( *+,(#)#,( ,+,(#)#-( -+,(#)#./( ./+,(#)#0,( 1%&%#2"34567 89::62"&%#16;%4&<6:&#"=#>$35%&9": ?#@6:&64#="4#A34%B#C"B95D#%:$#16E6B";<6:&Center for Rural Policy & Development, 2013
    • Thank You!Atlas of Minnesota Onlinewww.ruralmn.org