Teaching/Communication/Extension/Profession,

Debertin, David L.

Huie, John M.

English

Research Papers in Economics

SOUTHERN  JOURNAL OF AGRICULTURAL  ECONOMICS  DECEMBER,  1974
WHAT CAN  THE PUBLIC  SCHOOL DO TO REDUCE  DROPOUT NUMBERS?*
David L.  Debertin and John M. Huie
INTRODUCTION  whether  or  not  to  stay  in  school.  If  two  school
ural  y h  w  fil  t  c  le  hig  s  l  systems  of the  same  size  are  located in  communities Rural  youth  who  fail  to  complete  high  school
often  experience  a  great  deal  of  difficulty  when  of  similar  social and economic makeup, differences in often  experience  a  great  deal  of  difficulty  when
the  observed  number  of dropouts  between  the  two
competing  for  available  jobs.  All rural  youth cannot 
school  systems  may  be  due  to  differences  in hope  to  find employment  at  satisfactory  wage levels  school  systems  may  be  due  to  differences  in
. \  . . -1  Tcharacteristics  of the school systems.
in the  local  community.  Many must leave. It has long  c  o  t 
Clearly,  minimization  of dropout  numbers is not
been  known that economic mobility  is highly related  lrl  m  o  r  r 
to  the  educational  level  of  an  indi  l.  D  g  the  only  objective  of  a  local  school  administrator. to  the  educational  level  of an  individual.  Dropping
However,  it  can be  argued  that  keeping  students  in
out  of  school  at  an  early  age  poses  a  substantial  school  is  one  of the goals of the administrator  of any
deterrent  to  educational  attainment  and  subsequent
public  school.  Consequently,  it  is  appropriate  to
"^  ~mob^~  ^'ilit  ~y.  ^assess  the extent to  which a school administrator can
It  has  been  proposed  that  the  number  of t  hs bn  p d  t  t  n  o  influence  the number of dropouts by altering  school
dropouts  can  be  reduced  by pumping  more  money dropos cn be  r  d  by p  g me  m  y  input  variables  over  which the  administrator  exerts
into  the  public  schools.  Educators  have  contendedt  rl
.-  „  i  . J  J  i  .J  direct control.
that  inexperienced,  poorly  trained,  and  low-paid  direct  control.
teachers  often  found  in  rural  areas can lead  to large  Specific  hypth  t  tt 
numbers  of dropouts.  The  analysis  that  follows was  subsequent analysis are that:
therefore designed  to isolate determinants of dropout
numbers  from  public  schools.  The  model  construes  1.  Dropout  numbers  are  lowest  in  school
the formal  educative process in a production function  districts  with  teachers  at  high  mean
context  as  have  other  studies  [1,  3,  4,  5,  7].  experience,  degree  and  salary  levels.  High
Minimization  of the  number  of dropouts is  assumed  pupil/teacher  ratios are associated with large
to  be  one  of  the  goals  of  the  local  school  numbers of dropouts.
administrator.  Hence, the dropout rate is one possible  2.  Dropout  numbers  are  lowest in high-income
measure  of  an  output.  Inputs  to  the  production  districts  where  a  large  proportion  of
process  consist  of  characteristics  of the  school  and  residents  have  college  degrees.  Rural-urban
community  believed  to  have  an  influence  on  a  differences  in  dropout  numbers  are  also
student's decision  whether or not to stay in school.  thought to exist.
The  basic rationale  for using dropout numbers as
a measure  of educational  output  is  similar to the line
of  reasoning  used  to justify  the  use  of  scores  on  TE
standardized  tests  of  achievement  as  output  To test the  hypothesis that characteristics  of the
measures.l  Presumably,  both  the  school  and  school  and  community  can  influence the  number of
community  can  influence  a  student's  decision  dropouts,  a  multiplicative  "educational  production
David  L.  Debertin  is  assistant  professor  at  the  University  of  Kentucky,  and  John  M.  Huie  is  associate  professor  at  Purdue
University.
*Purdue Agricultural  Experiment Station Journal Paper No. 5622.
1See,  for example  [1, 2,  3, 4,  5, 6, 7,  8,  9,  11,  12].
115function" was estimated.2:  Three socioeconomic  variables also were included
l0  a2  03  in  the  production  function.  Population  density  was
(1)  DROP= a  ENRC  DENS  PTRA  used  as  a  means  of testing  for  possible  rural-urban
differences  in  the  dropout  numbers.  It  is  proposed
EXP  DEG  SAL  GFCO  that  families with high incomes  will tend  to produce
students  less  likely  to  drop  out  of school  than  will
INCO  low-income  families.  Children  from  low-income
families  may  drop  out  of school  at  a very  early  age
where  because  they and their  families place  a  high value  on
current,  rather  than future,  income.  Parents  who  are
DROP  =  The  number  of  students  in  the  college  graduates  are  expected  to  encourage  their
school  district that  dropped  out of  children  to  remain  in  school.  Consequently,  the
school in 1970;  percent  of persons  over  25  who  are college graduates
ENRC  =  Total  enrollment  in  the  school  was included  as  an explanatory  variable  to  act  as  a
district for 1970;  proxy  for  the  value  that  parents  place  on  an
DENS  =  Population  density  in the county in  education.
which  the  school district is located;
PTRA  =  The  pupil/teacher  ratio  in  the  DATA
school district; school~ ~district;  Data  for  the  analysis  consisted  of information
EXP  =  Mean  experience  of teachers  in the  from  264  public  school  districts  in  Indiana  for  the
school district;  school  year  1970-1971.3  Data  on  dropouts  were
DEG  =  Mean  degree  level of teachers in the  obtained  from  a  statewide  survey  on  dropouts
school district;  conducted  during  the  same  school  year.
SAL  =  Mean  salary  level of teachers  in the  Socioeconomic  data  were  obtained  from  the  1970
school district;  U.S.  Census  [10].  Socioeconomic  data  were  for
GFCO  =  Percent  of  persons  over  25  in  the  individual  school  districts,  not  city  or  county
school  district  who  were graduated  averages.  Census  data  for townships  were  aggregated
from college, and  to obtain averages for individual  school districts.
INCO  =  Mean  family  income  for the school  RESULTS
district. The  multiplicative  production  function  (1)  was
Measures  of  school  inputs  are  included  in  the  estimated by transforming the data to logarithms, and
equation  as  explanatory  variables.  The  mean  applying  ordinary  least  squares  to  the  transformed
experience  and degree levels of teachers  in the district  data.  Ordinary  least  squares  estimates  of parameters
are  included  in  order to test hypotheses regarding the  of  the  model  and  associated  standard  errors  are
relationships  between these  characteristics  of teachers  presented  in Table  1, while simple correlations among
and the dropout  numbers.  variables included in the model are presented  in Table
The  mean  salary  level  also  is  included  as  an  2.
additional  measure  of teacher  characteristics,  since it  The  observed  relationships  between  some of the
is  sometimes  asserted  that  schools  with  high  salary  school  input  variables  and  the  dropouts  were  found
schedules  are  able  to  attract  teachers  with  special  to  be  inconsistent  with a  priori expectations.  In this
qualifications  not  measured  by  training  and  regard,  the  findings of the analysis  are similar  to the
experience.  Highly paid, well-trained  and experienced  findings  in recent studies in which achievement  scores
teachers  should  lead  to  few  dropouts.  The  were  used  as  output  measures  [2,  5,  7].  Regression
pupil/teacher  ratio,  a proxy  for class  size, is  a major  coefficients on school inputs found to be significantly
determinant  of the cost of an educational program.  A  different  from  zero in  some  cases  had signs opposite
low  pupil/teacher  ratio  is  expected  to  result  in  few  those suggested by theoretical considerations.
dropouts.  Schools  with  large total enrollments can be  The  pupil/teacher  ratio  was  found  to  be
expected to have large  numbers of dropouts.  significantly  related  to  the  dropout  rate.  However,
2The  multiplicative  functional  form  was  chosen  because  it  allows  for diminishing  returns to inputs.  For example,  a
doubling of teachers' salaries likely  would  result in  a less-than-equivalent  reduction  in dropout numbers.
3There  are  approximately  300  school  districts in  Indiana. The  parameters were  estimated  using  all  school  districts in
Indiana for which  information was  complete.
116Table 1.  ORDINARY  LEAST  SQUARE  ESTIMATES  OF  PARAMETERS  OF  A  MULTIPLICATIVE
PRODUCTION  FUNCTION  FOR THE PREDICTION OF A DROPOUT RATE
Independent  Variables (All  Dependent  Variable is the  90 Percent Confidence
variables are Logrithms)  number of students in the  Limits on Parameter
School District that Dropped  Estimates
ut of School in 1970 (DROP)
Intercept  6.72
Total Enrollment in the  1.30**  +1.22 to + 1.38
School District (ERNC)  (.05)
County Population  Density  .009  -. 067  to  .085
(DENS)  (.046)
Pupil/Teacher  Ratio in the  -. 576*  -1.094 to -. 058
District  (PTRA)  (.314)
Mean  Experience  Level  of  Teach-  .484**  +.159  to  +.809
ers  in  the  District  (EXP)  (.197)
Mean Degree Level of Teachers  -. 14  -1.99 to +1.71
in the District (DEG)  (1.12)
Mean Salary Level of Teachers  -. 857  -. 423 to +2.14
in the District (SAL)  (.777)
Percent of Population in Dis-  -. 163*  -. 303 to -. 023
trict that Graduated from  (.085)
College (GFCO)
Mean Family Income (INCO)  -. 869**  -1.493 to -. 245
(.378)
R
2 =  .79
F  = 121.18
n  =  265
* = Significant at the  .10 level,  two tailed test
**  = Significant  at the .05 level, two tailed test
Standard errors are in parentheses.
the  sign  on the  variable  indicates  that it  was  those  may  need  to  be  allocated  to  uses  other  than  for
school  districts  with  the  largest  pupil/teacher  ratios  reductions  in  the  pupil/teacher  ratio.  Of course,  the
that  ceteris  paribus,  had  the  lowest  dropout  rates.  finding  does  not  necessarily  mean  that  school
This  finding  has implications  for educational finance,  administrators  desiring  to  minimize  the  number  of
for  it  indicates  that  if the  desired  objective  of the  dropouts  can  expand  the  pupil/teacher  ratio
school  administrator  is  to reduce  dropouts,  resources  indefinitely.  Rather, within the range of the data, the
117Table  2.  SIMPLE CORRELATIONS  AMONG  VARIABLES  INCLUDED  IN THE PRODUCTION  FUNCTION
FOR  THE  PREDICTION  OF  A  DROPOUT  RATE  (ALL  VARIABLES  TRANSFORMED  TO
LOGARITHIMS)  a
LENRC  LDENS  LPTRA  LEXP  LDEG  LSAL  LGFCO  LINCO  LDROP
LENRC  1.00  .54  -. 05  -. 05  .46  .62  .38  .46  .86
LDENS  1.00  -. 02  -. 34  .31  .47  .31  .70  .38
LPTRA  1.00  -. 07  -. 09  -. 05  -. 10  -. 05  -. 08
LEXP  1.00  .09  .25  -. 17  -. 45  .09
LDEG  1.00  .66  .45  .30  .36
LSAL  1.00  .36  .39  .51
LGFCO  1.00  .60  .19
LINCO  1.00  .23
LDROP  1.00
aAn "L"  preceeding the variable  name code denotes a log transformation  of the variable.
evidence  suggests that  schools with high pupil/teacher  significantly  related  to  dropout  numbers.  The
ratios  had  fewer  dropouts  than  those  with  lower  coefficient  on  mean  salary  level  was  found  to  be
pupil/teacher ratios.4 negative  and  larger  than  the  standard  error, but  not
The  influence  of the  experience  of teachers  on  significantly  different  from  zero at  even the .20 level.
the  dropouts  also  was found to be inconsistent  with  The  sign  was,  however,  consistent  with  a  priori
anticipated  results.  The  coefficient  was  significantly  considerations  in  that  the  schools  with  the  smallest
different  from  zero,  but  the  sign  was  positive,  not  number  of  dropouts  were  found  to  be  paying  the
negative.  These  results  indicated that  school  districts  highest salary levels.5
hiring  or  retaining  teachers  with the  most experience  School  districts with large total enrollments were
are  also  those  districts  with  the  largest  number  of  found  to  have  significantly  higher  dropout  numbers
dropouts.  The  positive  sign on  experience  is perhaps  than  smaller  districts.  With  total enrollment  in  the
justified  in  that  young  (and  inexperienced)  teachers  regression  equation,  population  density  was  not
may  be  better  able to  relate to high  school  students  found  to be significantly  related to dropout numbers.
than  are  older  and  more  experienced  teachers,  and  Of  course,  districts with  large  total  enrollments  tend
consequently  are  able  to  encourage  students  to  to be located in urban areas.
remain in school.  A  major  determinant  of the number of dropouts
Again,  this  finding  has implications  for resource  was found  to be the percent  of persons in the school
allocation.  If the school administrator's  desired goal is  district  who  had  been  graduated  from  college.
the  minimization  of  dropout  numbers,  evidence  was  Schools  with  low dropout  rates,  as anticipated,  were
not  found  to  suggest  that  the  school  administrator  located  in  communities  in which a high proportion of
needs  to  be  concerned  with  retaining  experienced  the population  had been  graduated from college. The
teachers  on  the  staff.  In  fact,  it  may  be  quite  evidence  supports the hypothesis  that families in such
desirable  for  the  administrator  to  hire  a  share  of  areas  have favorable  attitudes  toward  education,  and
young and inexperienced  teachers each year.  encourage  students to remain in school.
Mean  degree  levels  were  not  found  to  be  Mean  family income also  was found to be related
4 Variation  in  pupil/teacher  ratios  among  Indiana  schools is relatively  low. Sample data had a mean value of 20.37 with
a standard  deviation  of only 2.32.
SAdditional  analysis  was  conducted  in an effort  to determine  why  the signs  on experience  and the pupil/teacher  ratio
were  inconsistent  with  a  priori  expectations.  Observations  were  sorted  in  arrays  according  to pupil  teacher  ratios and  average
teacher  experience.  An  effort  then  was  made  to determine  if additional  explanatory  variables related to pupil/teacher  ratios and
teacher  experience  could  be responsible  for the unexpected  findings.  No additional  variables were identified. A tabular analysis of
the  data  also was  conducted  in  order  to  determine  if the  factorialization  of the data  was  sufficient  to  insure that the regression
had  the  opportunity  to  estimate  the  effect  of experience  and  the  pupil/teacher  ratio  for  various  levels  of the  other variables
included  in the regression equation.  The analysis revealed that factorialization of the data was sufficient.
118to  dropout  numbers.  As  expected,  schools  located in  masters  degrees  other  than  to  minimize  a  dropout
high  income  areas  were  found  to  have  significantly  rate.  However,  the  basic  findings  of  the  analysis
lower  dropout  rates than those located in low income  concur  with a large number of recent studies in which
areas,  lending  support to the contention that children  little  evidence  has  been  found  of  relationships
from low income  families  leave school at an early age  between  major  school  input  variables  (pupil/teacher
because  a  high value  is placed on current, rather than  ratios,  salary  levels,  and  training  and  experience  of
future, income.  teachers)  and  "conventional"  output  measures
~~~CONCLUSIONS  ~(standardized test scores) [1,3,4, 5,6, 7, 8, 9].
Second,  socioeconomic  variables  appear  to
Two  key  conclusions  follow  from  the  evidence  influence dropout rates in a manner similar to that
generated  by  the  analysis.  First, little support was  hypothesized.  Clearly,  a  student's  motivation  and
found for  the belief that school administrators can  interest  in  staying  in school primarily  is conditioned
affect  the dropout rate by altering levels  of school  not  by  the  availability  of  inputs  within  the  local
input variables over which they exert direct control.  public  school, but  rather by the characteristics of the
This  statement  is,  of  course,  true  only  within  the  student's family and community. As evidenced by the
range  of  data.  Pupil/teacher  ratios  cannot  be  results of the analysis, the belief that the allocation of
expanded  indefinitely.  Further,  there  certainly  may  additional  funds  to  public  education  will  reduce
be ample justification for  the hiring of teachers  with  dropout  rates is largely unwarranted.
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WHAT CAN THE PUBLIC SCHOOL DO TO REDUCE DROPOUT NUMBERS?

WHAT CAN THE PUBLIC SCHOOL DO TO REDUCE DROPOUT NUMBERS?

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