Minimum Wage Effect on Small Businesses

a presentation by Lindsey Terry

The Issue

• Mandatory wage increases hurt not only small businesses, but their employees as well. Big corporations do not have to absorb the cost because most minimum-wage jobs are offered by small businesses. Government manipulation of the starting wage has failed as tool of social and/or economic justice. It has not been proven to reduce poverty or narrow the income gap and puts a stranglehold on America's top job creators: small businesses. The overwhelming majority of economists continue to affirm the job-killing nature of mandatory wage increases. Mandatory minimum-wage increases end up reducing employment levels for those people with the lowest skills. (NFIB, National Federation of Independent Business )

The Research Question:

• What are the effects of increasing minimum wages in regard to its effects on small businesses?

The Dependent Variable

• Each state’s # of small businesses

The Independent Variables

• Each state’s minimum wage X1• Each state’s population growth rate

X2• Each state’s per capita income X3• Each state’s percentage change in

real gross state product X4• Each state’s population X5

The Sources and Data

• SBA (United States Small Business Association sba.gov)

• US Department of Labor dol.gov• US Bureau of Economic Analysis

bea.gov• 2005 information

# of Small BusinessesState

# of small businesses (Y)

AL 323891

AK 63497AZ 396318AR 55542CA 3320977CO 493886CN 322805DE 68495DC 59775FL 1633574GA 722089HI 105242ID 131663IL 1001185IN 451437IA 243932KS 229776KY 317115LA 347436ME 141936MD 477233

MA 599389

MI 765487

MN 464946

MS 197586

MO 461259

MT 106789NE 151088NV 177282NH 133052NJ 766232NM 143909NY 1779932NC 671810ND 59158OH 850961OK 303135OR 320019PA 927369RI 95390SC 312108SD 72949TN 471316TX 1787607UT 203468VT 74957VA 567830WA 529863WV 119806WI 406766WY 56740

Each State’s Minimum WageState Minimum Wage (X1)AL 5.15AK 7.15AZ 5.15AR 6.25CA 8CO 7.02CN 7.65DE 7.15DC 7FL 6.79GA 5.15HI 7.25ID 5.85IL 7.5IN 5.85IA 7.25KS 2.65KY 5.85LA 5.15ME 7MD 6.15MA 8MI 7.15MN 5.15

MS 5.15MO 6.65MT 6.25NE 5.85NV 6.33NH 6.5NJ 7.15NM 6.5NY 7.15NC 6.15ND 5.85OH 7OK 5.85OR 7.95PA 7.15RI 7.4SC 5.15SD 5.85TN 5.15TX 5.85UT 5.85VT 7.68VA 5.85WA 8.07WV 6.55WI 6.5WY 5.15

Each State’s Population Growth Rate

State Population Growth Rate (X2)

AL 2.5AK 5.9AZ 15.8AR 4.0CA 6.7CO 8.4CN 3.1DE 7.6DC -3.8FL 11.3GA 10.8HI 5.3ID 10.4IL 2.8IN 3.1IA 1.4KS 2.1KY 3.2LA 1.2ME 3.7MD 5.7MA 0.8MI 1.8MN 4.3

MS 2.7MO 3.6MT 3.7NE 2.8NV 20.8NH 6.0NJ 3.6NM 6.0NY 1.5NC 7.9ND -0.9OH 1.0OK 2.8OR 6.4PA 1.2RI 2.7SC 6.1SD 2.8TN 4.8TX 9.6UT 10.6VT 2.3VA 6.9WA 6.7WV 0.5WI 3.2WY 3.1

Each State’s Per Capita IncomeMS 25,015MO 31,231MT 29,015NE 32,923NV 35,744NH 37,768NJ 43,831NM 27,889NY 39,967NC 31,041ND 31,357OH 31,860OK 29,948OR 32,289PA 34,937RI 35,324SC 28,285SD 32,523TN 30,969TX 32,460UT 27,321VT 32,717VA 37,503WA 35,479WV 26,419WI 33,278WY 37,305

State Per capita Income (X3)AL 29,623AK 35,564AZ 30,019AR 26,681CA 36,936CO 37,510CN 47,388DE 37,088DC 52,811FL 34,001GA 30,914HI 34,489ID 28,478IL 36,264IN 31,173IA 31,670KS 32,866KY 28,272LA 24,664ME 30,808MD 41,972MA 43,501MI 32,804MN 37,290

Each state’s PopulationState PopulationAL 4,539,611

AK 669,411AZ 5,952,083AR 2,772,152CA 35,990,312CO 4,673,724CN 3,486,490DE 840,558DC 582,049FL 17,736,027GA 9,107,719HI 1,267,581ID 1,425,894IL 12,719,550IN 6,257,121IA 2,955,587KS 2,741,665KY 4,171,016LA 4,495,670ME 1,312,222MD 5,573,163MA 6,429,137MI 10,107,940MN 5,113,824

MS 2,900,456MO 5,787,885MT 935,784NE 1,754,042NV 2,408,948NH 1,303,112NJ 8,657,445NM 1,916,331NY 19,262,545NC 8,679,089ND 635,938OH 11,459,776OK 3,535,926OR 3,629,959PA 12,367,276RI 1,066,721SC 4,254,989SD 780,046TN 5,989,309TX 22,843,999UT 2,505,013VT 619,736VA 7,557,588WA 6,270,838WV 1,805,626WI 5,540,473WY 506,541

The First AttemptSUMMARY OUTPUT

Regression Statistics

Multiple R 0.993837316

R Square 0.987712611

Adjusted R Square 0.986347346

Standard Error 67674.71044Observations 51

ANOVA  df SS MS F

Regression 5 1.65667E+13 3.31E+12 723.4583

Residual 45 2.06094E+11 4.58E+09Total 50 1.67728E+13   

  Coefficients Standard Error t Stat P-value

Intercept -235385.0526 74921.61331 -3.14175 0.002968

Minimum Wage (X1) 12817.07183 10577.23116 1.211761 0.231929

Population Growth Rate (X2) -2705.378885 3450.933511 -0.78396 0.437173

Per capita Income (X3) 3.32404943 1.976098868 1.682127 0.099472

% change in real gross state product (X4) 8329.761628 6559.714787 1.269836 0.21067

Population (X5) 0.087169697 0.001526475 57.10522 1.23E-43

The Problem

• Glejser Test ran positive for Heteroscedasticity!!

 Coefficie

ntsStandard

Error t Stat P-value

Intercept22983.1

68925817.3524

413.9507

950.00024

954

Predicted Number of small businesses (Y)

0.050654774

0.007806238

6.489013

4.10732E-08

The Solution• Put the dependent variable in terms of population and eliminate

population and as an independent variable

State Number of small businesses (Y)

Population Growth Rate (X2)

Population

Population /1000

Small Business/thousand pop.

AL 323,891 2.54,539,6

11 4,540 71AK 63,497 5.9 669,411 669 95

AZ 396,318 15.85,952,0

83 5,952 67

AR 55,542 4.02,772,1

52 2,772 20

CA 3,320,977 6.735,990,

312 35,990 92

CO 493,886 8.44,673,7

24 4,674 106

CN 322,805 3.13,486,4

90 3,486 93DE 68,495 7.6 840,558 841 81DC 59,775 -3.8 582,049 582 103

FL 1,633,574 11.317,736,

027 17,736 92

The Second AttemptSUMMARY OUTPUT

Regression StatisticsMultiple R 0.445183778R Square 0.198188596Adjusted R Square 0.128465866Standard Error 14.41838785Observations 51

ANOVA

  df SS MS FSignificance

F

Regression 4 2363.72894 590.932235 2.8425250.03456258

3Residual 46 9562.935774 207.8899081Total 50 11926.66471     

  Coefficients Standard Error t Stat P-value  Intercept 41.44657143 15.83346593 2.617656274 0.011944Minimum Wage (X1) 1.402953191 2.21772868 0.632608129 0.530122

Population Growth Rate (X2) -0.746064698 0.725358374 -1.028546336 0.309071

Per capita Income (X3) 0.000975934 0.000419778 2.324882233 0.024546

% change in real gross state product (X4) 1.327013332 1.394713335 0.951459557 0.346344 

The Results of the Second Attempt

• No Heteroscedasticity (YAY!)• Lower R-Squared (went from .98 to .19) • Per Capita Income (X3) only significant

independent variable• 3rd Attempt - Restricted Regression (that is,

dropping all variables except X3)

The 3rd Attempt(Restricted)

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.41750501

R Square 0.174310434

Adjusted R Square 0.157459626

Standard Error 14.17652746

Observations 51

ANOVA

  df SS MS F Significance F

Regression 1 2078.942 2078.942097 10.34434 0.00230215

Residual 49 9847.723 200.973931

Total 50 11926.66     

  CoefficientsStandard

Error t Stat P-value Lower 95%

Intercept 44.97367198 12.38349 3.631745222 0.000672 20.08812239

Per capita Income (X3) 0.001167602 0.000363 3.21626136 0.002302 0.000438064

The F Test

knR

mRRF

ur

rur

2

22

1

The Results of the F-Test

• R2(ur)=.1982 n=51 k(ur)= 4

• R2 (r)=.1743 n=51 k(r)=1

• m= k(ur)-k(r) = 4-1=3• F = (.1982-.1743)/3 (1-.1982)/(51-4) F=.47

• F=.47• Not Significant• At less than 10%• Adding the 3 exp. var.

does not significantly increase explanatory power

The Conclusions

• Drop Excess Variables for BEST regression

• Y= 44.97+0.0012X• Holding other

variables constant, for every change in per capita income there is a positive .0012 change in the number of small businesses.

• Results not definitive• Question of Reverse

Causality (the states that adopted minimum wages were those states that were less expected to suffer adverse effects)

• Further Research is needed to find the factors that could influence small business success