cloudy with a chance of enrollment: the effects of weather on student enrollment behavior

Enrollment Research Team

AACRAO-SEMNov. 2013Chicago Ralston, Wohlgemuth, Herzmann, Hagruth,

2013

CLOUDY WITH A CHANCE OF ENROLLMENT:

The effects of weather on student enrollment behavior

Kate RalstonDarin Wohlgemuth

Daryl HerzmannCorey Hagruth

Iowa State University

November 12, 2013AACRAO - SEM

Chicago, IL



2013



2013

What is Weather?

The state of the atmosphere at a given moment in time at a given location.



2013

What is Weather?Measures include the amount of

– sunshine – clouds– rainfall– humidity– wind– temperature

fluctuating on a daily basis.



2013

Weather vs. Climate

Not the same as climate

may include a combination of the same measures considers them in 30-year increments

Climate Normals



2013

Why do we care?

Weather affects an array of human behaviors and decisions, often – without us knowing.



2013

Effects of weather on behavior

• Hirshleifer, D. and Shumway, T. (2003): Sunny days higher stock returns

• Rind, B. (1996): Cloudy skies less tips to servers

• Anderson, C. (1989): Hotter weather higher levels of aggression



2013

Weather in Higher Ed?

• Baxter (2009): Rainy days Less med school applicants accepted

• Simonsohn (2007, 2009): Cloudy skies Academic rigor of applicants matters more than extra-curricular achievements to admissions and applicants



2013

Then, the question is…

Does weather during campus visit affect a student’s probability of enrollment?



2013

Other questions to consider?

Does any particular weather element matter more?What about element combinations?Seasons?Gender?Choice of major college?



2013

Getting Data

Enrollment: individual level, students

Meteorology: - daily 8-hour average, town

- climatology, regional

Joint File:Visits, enrollment, high-

school status, daily weather variables, climate averages



2013

Preparing the data

Office of Admissions:

Daily visit data, 5 years High school status – Senior/Junior Application and admission status Enrollment information from census Other relevant information



2013

Preparing the data

Iowa State Meteorology Department:

Daily readings from Ames Hourly readings, averaged across regular business hours Daily climate normal for IA Daily climate normal, regional



2013

Preparing the data

Identifying influential weather variables:

– Temperature: Above/Below average– Wind-chill: Yes/No– Heat Index: Yes/No– Snow: Yes/No– Clouds: Yes/No– Rain: Yes/No

What else matters?



2013

Perception of WeatherCombination of objective climate normals and subjective comfort.



2013

What is Good Weather?

How do you define and measure good

weather?



2013

Creating a Weather Index

Weather Property “GOOD” “BAD”Temperature Above 0 Below 1

Wind Chill No 0 Yes 1

Heat Index No 0 Yes 1

Snow No 0 Yes 1

Rain No 0 Yes 1

Clouds No 0 Yes 1

Can’t have wind chill and heat indexCan’t have snow and rain

Index range: 0 to 4, the higher the worse

Bad weather indicator:

Weather index >2



2013



2013

Recognizing seasons

Cold season: November – MarchWarm season: June-AugustDemi-season: April/May, September/October

Create seasons variables:

Dummy codes: cold, warm, demi = 0/1Effect codes: cold, warm, demi = -1/1Effect switch: cold -1, warm 1, demi 0



2013

Winter vs. SummerWeather Property GOOD BADTemperature Above 0 Below 1



Snow No 0 Yes 1

Rain No 0 Yes 1

Clouds No 0 Yes 1

Weather Property GOOD BADTemperature Above 0 Below 1



Snow No 0 Yes 1

Rain No 0 Yes 1

Clouds No 0 Yes 1



2013

Understanding climate normals

• Understanding the norm helps adjusting expectations

benchmarking weather is important for informing initial campus visit strategies



2013

Iowa weather is…

• Best in early spring and fall • Sunniest: September-October• Best temperature: March/April

• Extreme heat: ~ 2 months a year• Extreme cold: ~ 2 months a year• Rain: ~30% of the year



2013

Benchmarking the weather

Visits

# %

January 1,618 4.64February 3,374 9.67March 4,552 13.04April 4,452 12.75May 852 2.44June 1,219 3.49July 3,766 10.79August 3,244 9.29September 1,416 4.06October 5,573 15.96November 3,644 10.44December 1,198 3.43Total 34,908 100



2013

Benchmarking the elements

Visits Temperature Snow Rain Heat Wind chill Clouds

# % Above Below No Yes No Yes No Yes No Yes No Yes

January 1,618 4.64 974 644 1,244 374 1,513 105 1,618 0 604 1,014 739 879

February 3,374 9.67 1,935 1,439 2,459 915 3,180 194 3,374 0 1,229 2,145 1,353 2,021

March 4,552 13.04 3,363 1,189 3,782 770 3,546 1,006 4,552 0 3,459 1,093 2,224 2,328

April 4,452 12.75 3,142 1,310 4,389 63 2,518 1,934 4,452 0 4,324 128 2,796 1,656

May 852 2.44 591 261 827 25 500 352 836 16 852 0 566 286

June 1,219 3.49 976 243 1,219 0 722 497 870 349 1,219 0 818 401

July 3,766 10.79 3,095 671 3,766 0 2,595 1,171 1,801 1,965 3,766 0 2,725 1,041

August 3,244 9.29 2,613 631 3,244 0 1,910 1,334 2,210 1,034 3,244 0 2,173 1,071

September 1,416 4.06 1,123 293 1,416 0 1,007 409 1,354 62 1,416 0 1,030 386

October 5,573 15.96 3,388 2,185 5,547 26 3,484 2,089 5,573 0 5,530 43 3,407 2,166

November 3,644 10.44 3,305 339 3,573 71 3,228 416 3,644 0 3,350 294 2,987 657

December 1,198 3.43 662 536 963 235 1,132 66 1,198 0 541 657 579 619

Total 34,908 100 25,167 9,741 32,429 2,479 25,335 9,573 31,482 3,426 29,534 5,374 21,397 13,511



2013

Bad weather visits

Bad weather visitWeather

Decent BadJanuary 1,146 472February 2,161 1,213March 3,805 747April 3,567 885May 671 181June 1,041 178July 3,146 620August 2,709 535September 1,302 114October 4,448 1,125November 3,559 85December 806 392Total 28,361 6547



2013

So…?

Goal – satisfactory experience:

Planning more visits during more favorable weather times

Allocating necessary staff time and resources

Creating plan B for adverse conditions



2013

Does weather truly matter?

Going beyond frequencies:

correlation t-test/chi-square multiple regression



2013

CorrelationsDichotomous

variables can be correlated using Pearson’s phi or

mean square contingency coefficient

apply 0.466 0.009 0.028 -0.050 0.053 0.019 -0.020 0.061 -0.077 0.005 0.013

0.466 enroll -0.001 0.031 -0.066 0.054 0.006 -0.029 0.082 -0.121 0.022 -0.002

0.009 -0.001 temp_ind 0.274 -0.205 0.282 0.359 0.139 0.017 -0.113 0.083 0.669

0.028 0.031 0.274 snow_ind -0.091 0.400 0.250 -0.170 0.304 -0.154 -0.177 0.456

-0.050 -0.066 -0.205 -0.091 heat_ind -0.141 -0.175 0.019 -0.276 0.576 -0.227 0.046

0.053 0.054 0.282 0.400 -0.141 windchill_ind 0.205 -0.234 0.482 -0.237 -0.286 0.456

0.019 0.006 0.359 0.250 -0.175 0.205 cloud_ind 0.417 0.112 -0.093 -0.033 0.772

-0.020 -0.029 0.139 -0.170 0.019 -0.234 0.417 rain_ind -0.282 0.113 0.190 0.494

0.061 0.082 0.017 0.304 -0.276 0.482 0.112 -0.282 cold_season -0.465 -0.617 0.089

-0.077 -0.121 -0.113 -0.154 0.576 -0.237 -0.093 0.113 -0.465 warm_season -0.409 0.001

0.005 0.022 0.083 -0.177 -0.227 -0.286 -0.033 0.190 -0.617 -0.409 demi_season -0.093

0.013 -0.002 0.669 0.456 0.046 0.456 0.772 0.494 0.089 0.001 -0.093 weather_index



2013

T-Test vs. χ2

T-Test

χ2



2013

FindingsEnrollment by weather elements

OverallObs Mean St.D. p-level

Temp Above 25167 0.464 0.499 n.s.Below 9741 0.463 0.499

Snow No 32429 0.460 0.498 .000**Yes 2479 0.520 0.500

Rain No 25335 0.473 0.499 .000**Yes 9573 0.441 0.497

Heat No 31482 0.475 0.499 .000**Yes 3426 0.365 0.481

Windchill No 29534 0.453 0.498 .000**Yes 5374 0.527 0.499

Clouds No 21397 0.462 0.499 n.s.Yes 13511 0.468 0.499

Bad Weather No 28361 0.466 0.499

0.085Yes 6547 0.457 0.498



2013

Geography matters

-65 -45 -25 -5 15 35

-25

-20

-15

-10

-5

0

5

10

15

20

25

Visitor Density



2013



2013

FindingsEnrollment by weather elements

By Region Iowa Contiguous States Non-Contiguous StatesObs Mean St.D. p-level Obs Mean St.D. p-level Obs Mean St.D. p-level

Temp Above 10015 0.718 0.450 0.0521 9160 0.442 0.497 n.s. 988 0.454 0.498 n.s.Below 3826 0.704 0.457 3657 0.445 0.497 396 0.485 0.500

Snow No 12813 0.713 0.452 n.s. 11877 0.439 0.496 .0012** 1259 0.445 0.497 .000***Yes 1028 0.728 0.445 940 0.490 0.500 125 0.648 0.480

Rain No 10331 0.714 0.452 n.s. 9164 0.452 0.498 .000*** 996 0.471 0.499 n.s.Yes 3510 0.715 0.451 3653 0.421 0.494 388 0.443 0.497

Heat No 12868 0.716 0.451 0.0174 11403 0.452 0.498 .000*** 1231 0.478 0.500 .000***Yes 973 0.684 0.465 1414 0.376 0.484 153 0.340 0.475

Windchill No 11472 0.713 0.452 n.s. 10834 0.432 0.495 .000*** 1154 0.441 0.497 .000***Yes 2369 0.718 0.450 1983 0.504 0.500 230 0.574 0.496

Clouds No 8558 0.714 0.452 n.s. 7691 0.444 0.497 n.s. 810 0.442 0.497 .030*Yes 5283 0.714 0.452 5126 0.443 0.497 574 0.493 0.500

Bad Weather No 11393 0.716 0.451 n.s. 10261 0.445 0.497 n.s. 1096 0.450 0.498 .026*Yes 2448 0.704 0.456 2556 0.437 0.496 288 0.514 0.501



2013

More?

Enrollment, from the North

By RegionIowa Cont NonC

p-level p-level p-levelTemp n.s. n.s. n.s.Snow n.s. .0023** n.s.Rain n.s. .000*** n.s.Heat n.s. .000*** n.s.Windchill n.s. .000*** n.s.Clouds n.s. n.s. n.s.Bad Weather n.s. n.s. n.s.

No Yes

Sensitive to elements, tend to enroll less during “element” days



2013

Regressions: Weather onlyRegression using weather variables, excluding athletes

enroll

overall Iowa Contiguous States Non-Contiguous States

N F( 14, 30625) R² N F( 14, 13521) R² N F( 14, 9882) R² N F( 14, 1212) R²

30640 52.29 0.0229 13563 5.06 0.0042 9897 9.13 0.0114 1227 3.29 0.0255

Coef. t P>t Coef. t P>t Coef. t P>t Coef. t P>t

isu_di -0.0001915 -14.4 0.000 0.000031 0.79 0.432 0.000304 3.46 0.001 1.13E-05 0.4 0.689temp_ind -0.0261321 -2.63 0.008 -0.00888 -0.65 0.515 -0.01836 -1.05 0.292 -0.03401 -0.68 0.496snow_ind 0.0167511 1.22 0.222 0.02207 1.19 0.235 0.022175 0.93 0.353 0.144117 2.08 0.038heat_ind 0.010846 0.82 0.410 0.051107 2.51 0.012 0.013466 0.6 0.546 -0.02907 -0.48 0.630windchill_ind 0.0198601 1.85 0.064 -0.00811 -0.57 0.567 0.016881 0.89 0.374 0.082091 1.46 0.144cloud_ind -0.0012187 -0.14 0.891 0.015102 1.24 0.214 -0.01531 -0.96 0.335 0.066767 1.53 0.126av_temp -0.0008563 -2.14 0.032 -0.00041 -0.75 0.454 -0.00123 -1.71 0.087 0.001506 0.77 0.442av_hum 0.000103 0.39 0.697 -0.00094 -2.62 0.009 0.000147 0.31 0.757 -0.00163 -1.17 0.240rain_ind -0.0004061 -0.05 0.963 0.028398 2.36 0.018 -0.00745 -0.49 0.624 0.03198 0.73 0.468switch -0.0000732 -0.04 0.971 -0.00524 -1.77 0.076 -0.00154 -0.42 0.671 0.008977 1.26 0.210cold_season 0.0027814 0.27 0.785 0.012435 0.86 0.392 -0.00656 -0.37 0.713 0.047321 0.99 0.323warm_season -0.1071873 -9.16 0.000 -0.06541 -3.93 0.000 -0.07816 -3.68 0.000 -0.11974 -2.07 0.039north -0.0310308 -5.38 0.000 0.012608 1.56 0.120 0.018349 1.75 0.081 0.02434 0.53 0.594bad_weather -0.0151523 -1.25 0.209 -0.01141 -0.69 0.493 -0.01425 -0.68 0.498 -0.038 -0.61 0.541



2013

Regressions: Weather/ HS StatusRegression using weather variables, excluding athletes

enroll

overall Iowa Contiguous States Non-Contiguous States

N F( 15, 30624) R² N F( 15, 13520) R² N F( 15, 9881) R² N F( 15, 1211) R²

30640 73.57 0.0343 13563 5.69 0.0052 9897 10.92 0.0148 1227 3.46 0.0293

Coef. t P>t Coef. t P>t Coef. t P>t Coef. t P>t

isu_di -0.0001929 -14.59 0.000 3.03E-05 0.77 0.443 0.00028 3.19 0.001 1.79E-06 0.06 0.950temp_ind -0.0252887 -2.56 0.010 -0.00871 -0.64 0.523 -0.0169 -0.97 0.332 -0.03301 -0.66 0.508snow_ind 0.0268426 1.97 0.049 0.024391 1.31 0.189 0.02899 1.22 0.224 0.140268 2.03 0.043heat_ind 0.0278332 2.12 0.034 0.054743 2.68 0.007 0.0247 1.11 0.269 -0.02668 -0.44 0.658windchill_ind 0.0116948 1.1 0.272 -0.00925 -0.65 0.513 0.010339 0.54 0.586 0.080711 1.44 0.150cloud_ind 0.0039237 0.44 0.657 0.015828 1.3 0.192 -0.01171 -0.74 0.460 0.066789 1.53 0.125av_temp -0.0006504 -1.63 0.102 -0.00033 -0.6 0.545 -0.00109 -1.52 0.129 0.001747 0.89 0.372av_hum -0.0001959 -0.74 0.457 -0.00101 -2.8 0.005 -4.1E-05 -0.09 0.931 -0.00173 -1.24 0.214rain_ind 0.0052827 0.61 0.539 0.030242 2.52 0.012 -0.00456 -0.3 0.764 0.031013 0.7 0.481switch -0.0017792 -0.9 0.370 -0.00546 -1.85 0.065 -0.00274 -0.76 0.450 0.007807 1.09 0.275cold_season 0.0043397 0.43 0.669 0.011939 0.82 0.410 -0.00391 -0.22 0.826 0.046624 0.98 0.329warm_season -0.0772267 -6.58 0.000 -0.05443 -3.22 0.001 -0.06244 -2.92 0.004 -0.08557 -1.44 0.150north -0.0309105 -5.39 0.000 0.01261 1.56 0.120 0.018176 1.73 0.083 0.020269 0.44 0.657bad_weather -0.0076171 -0.63 0.526 -0.00894 -0.54 0.591 -0.01035 -0.49 0.622 -0.03433 -0.55 0.580senior 0.1189781 19.05 0.000 0.03505 3.8 0.000 0.067095 5.96 0.000 0.085587 2.39 0.017



2013

Weather, demographic, academicRegression using weather, demographic andacademic variables, excluding athletes

enroll

overall Iowa Contiguous States Non-Contiguous StatesN F(28, 16011) R² N F(28, 9172) R² N F(28, 4418) R² N F( 28, 406) R²

16040 189.39 0.2475 9201 29.6 0.0801 4447 15.15 0.0818 435 3.3 0.1294Coef. t P>t Coef. t P>t Coef. t P>t Coef. t P>t

isu_di -0.00025 -10.510 0.000 0.000 -1.090 0.276 0.001 4.200 0.000 0.000 0.880 0.381temp_ind -0.014 -1.130 0.256 -0.010 -0.620 0.535 -0.034 -1.330 0.183 -0.012 -0.150 0.884snow_ind 0.021 1.280 0.202 0.023 1.070 0.283 -0.003 -0.080 0.940 0.282 2.260 0.025heat_ind 0.041 2.580 0.010 0.078 3.400 0.001 0.044 1.400 0.162 0.057 0.610 0.541windchill_ind 0.005 0.380 0.705 0.005 0.280 0.778 -0.007 -0.230 0.819 -0.044 -0.440 0.664cloud_ind -0.001 -0.090 0.927 0.007 0.520 0.603 -0.034 -1.460 0.144 0.031 0.390 0.695av_temp -0.001 -1.180 0.238 0.000 -0.420 0.674 -0.002 -2.180 0.029 -0.003 -1.040 0.297av_hum -0.001 -2.230 0.026 -0.001 -1.950 0.051 -0.001 -1.170 0.242 -0.001 -0.240 0.809rain_ind 0.022 2.080 0.037 0.025 1.820 0.068 0.023 1.080 0.281 0.011 0.150 0.877switch -0.002 -0.870 0.387 -0.005 -1.610 0.108 -0.003 -0.630 0.527 -0.003 -0.270 0.785cold_season 0.003 0.240 0.808 0.003 0.180 0.856 0.000 -0.020 0.986 -0.085 -1.070 0.286warm_season -0.045 -3.180 0.001 -0.062 -3.220 0.001 -0.011 -0.370 0.711 -0.065 -0.700 0.486senior 0.080 10.490 0.000 0.061 5.850 0.000 0.086 5.490 0.000 0.125 2.330 0.020north -0.002 -0.220 0.825 -0.003 -0.360 0.720 0.050 3.360 0.001 0.088 1.120 0.265bad_weather -0.011 -0.740 0.461 -0.009 -0.480 0.629 -0.002 -0.080 0.939 -0.074 -0.730 0.464agri 0.099 8.910 0.000 0.160 11.210 0.000 0.056 2.250 0.024 -0.035 -0.450 0.650design 0.088 6.530 0.000 0.125 7.030 0.000 0.119 4.190 0.000 -0.146 -1.640 0.102engin 0.110 11.200 0.000 0.141 10.750 0.000 0.185 9.000 0.000 0.021 0.310 0.754humsci 0.105 8.540 0.000 0.125 8.260 0.000 0.134 4.470 0.000 -0.148 -1.690 0.092biz 0.040 2.920 0.003 0.064 3.680 0.000 0.057 1.820 0.068 -0.135 -1.040 0.301minority 0.030 2.530 0.011 0.046 2.960 0.003 0.013 0.510 0.607 0.096 1.370 0.170female -0.021 -2.690 0.007 -0.017 -1.720 0.086 -0.009 -0.550 0.583 -0.066 -1.230 0.218legacy 0.082 8.920 0.000 0.038 3.580 0.000 0.089 3.930 0.000 0.097 1.830 0.069

Academic Prep

-0.095 -26.150 0.000 -0.096 -16.730 0.000 -0.077 -11.540 0.000 -0.111 -5.500 0.000-0.012 -12.170 0.000 -0.007 -4.170 0.000 -0.010 -3.640 0.000 -0.015 -1.840 0.0660.013 2.450 0.014 0.139 6.200 0.000 0.211 6.660 0.000 0.288 3.210 0.001-0.001 -2.380 0.017 -0.003 -5.280 0.000 -0.002 -2.070 0.039 -0.002 -0.510 0.6070.002 30.500 0.000 0.001 4.370 0.000 -0.001 -2.140 0.032 -0.002 -1.090 0.278

_cons 0.546 12.440 0.000 0.265 3.880 0.000 0.503 4.300 0.000 0.904 2.460 0.014



2013

Expectations matter: IA caseIowans only

enroll

Female Male

N F(15, 6938) R² N F(15,6566) R²

6954 5.03 0.0086 6582 2.11 0.0025

Coef. t P>t Coef. t P>t

isu_di 0.0000133 0.24 0.809 0.0000516 0.91 0.364

temp_ind 0.0043364 0.23 0.821 -0.0204216 -1.05 0.292

snow_ind 0.052 1.950 0.051 -0.004 -0.170 0.866

heat_ind 0.073 2.560 0.011 0.040 1.360 0.174

windchill_ind -0.002 -0.110 0.911 -0.017 -0.880 0.381

cloud_ind 0.036 2.100 0.036 -0.003 -0.160 0.875

av_temp 0.000 0.530 0.599 -0.001 -1.350 0.177

av_hum -0.001 -2.560 0.011 -0.001 -1.540 0.124

rain_ind 0.055 3.230 0.001 0.006 0.330 0.744

switch -0.005 -1.180 0.237 -0.006 -1.520 0.129

cold_season 0.044 2.140 0.032 -0.021 -1.030 0.305

warm_season -0.078 -3.370 0.001 -0.030 -1.220 0.223

senior 0.037 2.830 0.005 0.035 2.730 0.006

north 0.013 1.110 0.268 0.011 1.000 0.319

bad_weather -0.058 -2.480 0.013 0.041 1.720 0.085

_cons 0.692 11.790 0.000 0.811 13.570 0.000



2013

Implications

• Elements do make a difference• Not all differences are intuitive• Not all elements impact enrollment• Care matters (windchill findings)• So does timing (visiting as senior vs. junior)



2013

Comments & Questions

Contact [email protected] [email protected]

Thank you for attending this morning!

mailto:[email protected]

mailto:[email protected]

cloudy with a chance of enrollment: the effects of weather on student enrollment behavior

Documents