Data & Packages

Packages

Data

Clean Prolific Exports for Duplicate Submissions

None of the participating respondents submitted twice.

No one who respondent to one survey responded to the other

Clean Variables

Choice Variables

employer

attention

grants_decide

grants_job

grant_exp

grant_capacity

org_budget

age

gender

race

state

edu

party

Manipulation Check Variables

Thematic Check Variables

Between-Subjects Treatment Values & Order Randomization

Reformat Dataset for Choice-Level Observations

Add in Treatment Variables

Order Variables Neatly

Analysis

compare_coef <- function(m1, m2, terms) {
  stopifnot(all(terms %in% intersect(names(coef(m1)), names(coef(m2)))))

  # extract coefficient estimates and SEs from each model
  b1 <- coef(summary(m1))[terms, "Estimate"]
  se1 <- coef(summary(m1))[terms, "Std. Error"]

  b2 <- coef(summary(m2))[terms, "Estimate"]
  se2 <- coef(summary(m2))[terms, "Std. Error"]

  # difference in coefficients and its SE
  diff   <- b1 - b2
  seDiff <- sqrt(se1^2 + se2^2)   # independent-sample formula
  z      <- diff / seDiff
  p      <- 2 * (1 - pnorm(abs(z)))

  # tidy output
  data.frame(
    term     = terms,
    b_model1 = b1,
    b_model2 = b2,
    diff     = diff,
    se_diff  = seDiff,
    z        = z,
    p_value  = p,
    row.names = NULL
  )
}

Establish Base LPM

This model tests H1 - 3.

Hypothesis 1: Managers are more willing to apply for grants with greater award amounts.
Hypothesis 2:
Hypothesis 3:


	Baseline LPM
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.581***
	(0.047)
Increased Application Complexity	−0.179***
	(0.047)
More Frequent Reporting	−0.074
	(0.047)
Num.Obs.	2007
R2	0.573
R2 Adj.	0.519
Respondent Fixed Effects	Yes

## 
## Linear hypothesis test:
## amount - complexity = 0
## 
## Model 1: restricted model
## Model 2: choice ~ 0 + amount + complexity + reporting + factor(PROLIFIC_PID)
## 
##   Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
## 1   1782 403.79                                  
## 2   1781 388.20  1    15.591 71.529 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Linear hypothesis test:
## amount - reporting = 0
## 
## Model 1: restricted model
## Model 2: choice ~ 0 + amount + complexity + reporting + factor(PROLIFIC_PID)
## 
##   Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
## 1   1782 399.79                                  
## 2   1781 388.20  1    11.584 53.146 4.636e-13 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Linear hypothesis test:
## complexity - reporting = 0
## 
## Model 1: restricted model
## Model 2: choice ~ 0 + amount + complexity + reporting + factor(PROLIFIC_PID)
## 
##   Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
## 1   1782 391.27                                  
## 2   1781 388.20  1    3.0693 14.081 0.0001807 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

These findings support H1 and H2, but not H3.

Segment by Award Amount


	Lower Award Amount	Higher Award Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.058	−0.377***
	(0.052)	(0.066)
More Frequent Reporting	0.031	−0.188**
	(0.052)	(0.066)
Num.Obs.	892	669
R2	0.570	0.887
R2 Adj.	0.425	0.829
Respondent Fixed Effects	Yes	Yes

##         term    b_model1   b_model2      diff    se_diff        z      p_value
## 1 complexity -0.05829596 -0.3766816 0.3183857 0.08380393 3.799173 0.0001451796
## 2  reporting  0.03139013 -0.1883408 0.2197309 0.08380393 2.621965 0.0087424510

Segment by Reporting Requirements


	Less Frequent Reporting	More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.511***	0.654***
	(0.072)	(0.063)
Increased Application Complexity	−0.018	−0.288***
	(0.072)	(0.063)
Num.Obs.	669	892
R2	0.662	0.735
R2 Adj.	0.490	0.646
Respondent Fixed Effects	Yes	Yes

##         term    b_model1   b_model2       diff    se_diff         z     p_value
## 1     amount  0.51121076  0.6538117 -0.1426009 0.09556346 -1.492211 0.135643717
## 2 complexity -0.01793722 -0.2878924  0.2699552 0.09556346  2.824878 0.004729858

Segment by Application Complexity


	Reduced Application Complexity	Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.565***	0.565***
	(0.071)	(0.060)
More Frequent Reporting	−0.009	−0.135*
	(0.071)	(0.060)
Num.Obs.	669	892
R2	0.748	0.724
R2 Adj.	0.620	0.631
Respondent Fixed Effects	Yes	Yes

##        term    b_model1   b_model2         diff    se_diff            z
## 1    amount  0.56502242  0.5650224 1.221245e-15 0.09279155 1.316117e-14
## 2 reporting -0.00896861 -0.1345291 1.255605e-01 0.09279155 1.353146e+00
##     p_value
## 1 1.0000000
## 2 0.1760089

Segment by Sector

Base Model by Sector


	Nonprofit	Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.579***	0.590***
	(0.054)	(0.096)
Increased Application Complexity	−0.157**	−0.251**
	(0.054)	(0.096)
More Frequent Reporting	−0.089+	−0.024
	(0.054)	(0.096)
Num.Obs.	1539	468
R2	0.567	0.599
R2 Adj.	0.511	0.545
Respondent Fixed Effects	Yes	Yes

##         term    b_model1    b_model2        diff   se_diff           z
## 1     amount  0.57894737  0.58974359 -0.01079622 0.1103688 -0.09781952
## 2 complexity -0.15672515 -0.25128205  0.09455691 0.1103688  0.85673596
## 3  reporting -0.08888889 -0.02435897 -0.06452991 0.1103688 -0.58467542
##     p_value
## 1 0.9220756
## 2 0.3915908
## 3 0.5587660

Segment by Sector and Award Amount


	Nonprofit, Lower Amount	Nonprofit, Higher Amount	Local Government, Lower Amount	Local Government, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.047	−0.327***	−0.096	−0.538***
	(0.059)	(0.075)	(0.110)	(0.139)
More Frequent Reporting	0.000	−0.187*	0.135	−0.192
	(0.059)	(0.075)	(0.110)	(0.139)
Num.Obs.	684	513	208	156
R2	0.570	0.888	0.585	0.886
R2 Adj.	0.425	0.830	0.439	0.826
Respondent Fixed Effects	Yes	Yes	Yes	Yes

##         term      b_model1   b_model2      diff    se_diff        z     p_value
## 1 complexity -4.678363e-02 -0.3274854 0.2807018 0.09494626 2.956428 0.003112251
## 2  reporting  1.987151e-16 -0.1871345 0.1871345 0.09494626 1.970952 0.048729385

##         term    b_model1   b_model2      diff   se_diff        z    p_value
## 1 complexity -0.09615385 -0.5384615 0.4423077 0.1769113 2.500167 0.01241349
## 2  reporting  0.13461538 -0.1923077 0.3269231 0.1769113 1.847949 0.06460967

##         term      b_model1    b_model2        diff  se_diff          z
## 1 complexity -4.678363e-02 -0.09615385  0.04937022 0.124729  0.3958199
## 2  reporting  1.987151e-16  0.13461538 -0.13461538 0.124729 -1.0792630
##     p_value
## 1 0.6922379
## 2 0.2804705

##         term   b_model1   b_model2        diff   se_diff          z   p_value
## 1 complexity -0.3274854 -0.5384615 0.210976158 0.1573374 1.34091509 0.1799480
## 2  reporting -0.1871345 -0.1923077 0.005173189 0.1573374 0.03287958 0.9737706

Segment by Sector and Reporting Requirements


	Nonprofit, Less Frequent Reporting	Nonprofit, More Frequent Reporting	Local Government, Less Frequent Reporting	Local Government, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.515***	0.643***	0.500**	0.688***
	(0.082)	(0.071)	(0.153)	(0.130)
Increased Application Complexity	−0.047	−0.257***	0.077	−0.388**
	(0.082)	(0.071)	(0.153)	(0.130)
Num.Obs.	513	684	156	208
R2	0.679	0.729	0.593	0.756
R2 Adj.	0.516	0.637	0.378	0.670
Respondent Fixed Effects	Yes	Yes	Yes	Yes

##         term    b_model1   b_model2       diff   se_diff         z    p_value
## 1     amount  0.51461988  0.6432749 -0.1286550 0.1088424 -1.182029 0.23719405
## 2 complexity -0.04678363 -0.2573099  0.2105263 0.1088424  1.934230 0.05308487

##         term   b_model1   b_model2       diff   se_diff          z    p_value
## 1     amount 0.50000000  0.6884615 -0.1884615 0.2005679 -0.9396396 0.34740245
## 2 complexity 0.07692308 -0.3884615  0.4653846 0.2005679  2.3203345 0.02032279

##         term    b_model1   b_model2        diff  se_diff           z   p_value
## 1     amount  0.51461988 0.50000000  0.01461988 0.173361  0.08433201 0.9327925
## 2 complexity -0.04678363 0.07692308 -0.12370670 0.173361 -0.71357857 0.4754878

##         term   b_model1   b_model2        diff   se_diff          z   p_value
## 1     amount  0.6432749  0.6884615 -0.04518668 0.1483918 -0.3045094 0.7607399
## 2 complexity -0.2573099 -0.3884615  0.13115160 0.1483918  0.8838199 0.3767935

Segment by Sector and Application Complexity


	Nonprofit, Reduced Complexity	Nonprofit, Increased Complexity	Local Government, Reduced Complexity	Local Government, Increased Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.573***	0.564***	0.538***	0.569***
	(0.081)	(0.069)	(0.147)	(0.118)
More Frequent Reporting	0.000	−0.138*	−0.038	−0.123
	(0.081)	(0.069)	(0.147)	(0.118)
Num.Obs.	513	684	156	208
R2	0.730	0.720	0.792	0.740
R2 Adj.	0.593	0.625	0.683	0.649
Respondent Fixed Effects	Yes	Yes	Yes	Yes

##        term     b_model1   b_model2        diff   se_diff          z   p_value
## 1    amount 5.730994e-01  0.5637427 0.009356725 0.1067852 0.08762195 0.9301772
## 2 reporting 9.332922e-16 -0.1380117 0.138011696 0.1067852 1.29242370 0.1962105

##        term    b_model1   b_model2        diff   se_diff          z   p_value
## 1    amount  0.53846154  0.5692308 -0.03076923 0.1886684 -0.1630863 0.8704505
## 2 reporting -0.03846154 -0.1230769  0.08461538 0.1886684  0.4484873 0.6538015

##        term     b_model1    b_model2       diff   se_diff         z   p_value
## 1    amount 5.730994e-01  0.53846154 0.03463788 0.1679302 0.2062635 0.8365851
## 2 reporting 9.332922e-16 -0.03846154 0.03846154 0.1679302 0.2290329 0.8188434

##        term   b_model1   b_model2         diff   se_diff           z   p_value
## 1    amount  0.5637427  0.5692308 -0.005488079 0.1371068 -0.04002776 0.9680710
## 2 reporting -0.1380117 -0.1230769 -0.014934773 0.1371068 -0.10892801 0.9132596

Appendices

Power Analysis

##          n       type_s exp_typeM amce power alpha levels delta0
## 1 612.0732 2.254154e-05  1.140122  0.1   0.8   0.1      2   0.45

For the base mode, I only need 612 effective observations to have 80% power to detect an amce of 0.10 at alpha = 0.10.

## 
##      Multiple regression power calculation 
## 
##               u = 51
##               v = 187.4496
##              f2 = 0.15
##       sig.level = 0.05
##           power = 0.8

We have enough power to detect a medium effect size

Sample Demographics

Categorical demographics: Overall vs. Sector
Variable	Level	Count (Overall)	Percent (Overall)	Count (Local Gov)	Percent (Local Gov)	Count (Nonprofit)	Percent (Nonprofit)
edu	Associate Degree (e.g., AA, AS)	15	6.7	6	11.5	9	5.3
edu	Bachelor’s Degree (e.g., BA, BS)	84	37.7	21	40.4	63	36.8
edu	Doctoral Degree (e.g., JD, MD, PhD)	23	10.3	2	3.8	21	12.3
edu	High school degree or equivalent (e.g., GED)	2	0.9	1	1.9	1	0.6
edu	Master’s Degree (e.g., MA, MS, MPA, MBA)	78	35.0	11	21.2	67	39.2
edu	Some college credit, no degree	17	7.6	10	19.2	7	4.1
edu	Trade/technical/vocational training	4	1.8	1	1.9	3	1.8
gender	Man	79	35.4	27	51.9	52	30.4
gender	Non-binary	2	0.9	0	0.0	2	1.2
gender	Woman	142	63.7	25	48.1	117	68.4
party	Democrat	115	51.6	25	48.1	90	52.6
party	Independent/No Party Affiliation	55	24.7	11	21.2	44	25.7
party	Other (please specify)	7	3.1	1	1.9	6	3.5
party	Republican	46	20.6	15	28.8	31	18.1
race	American Indian/Alaskan Native	3	1.4	1	1.9	2	1.2
race	Asian	14	6.4	2	3.8	12	7.1
race	Black	24	10.9	8	15.4	16	9.5
race	Hispanic	16	7.3	7	13.5	9	5.4
race	Other Race (please specify)	4	1.8	2	3.8	2	1.2
race	White	159	72.3	32	61.5	127	75.6

Organization Budget Distribution (ordered high → low): Overall vs. Sector
Budget Level	Count (Overall)	Count (Local Gov)	Count (Nonprofit)	Percent (Overall)	Percent (Local Gov)	Percent (Nonprofit)
≥1B	18	6	12	9.5	14.0	8.2
750M–1B	6	0	6	3.2	0.0	4.1
500–750M	7	1	6	3.7	2.3	4.1
250–500M	7	2	5	3.7	4.7	3.4
100–250M	6	1	5	3.2	2.3	3.4
75–100M	14	2	12	7.4	4.7	8.2
50–75M	12	5	7	6.3	11.6	4.8
25–50M	12	3	9	6.3	7.0	6.1
10–25M	16	6	10	8.4	14.0	6.8
7.5–10M	16	6	10	8.4	14.0	6.8
5–7.5M	11	2	9	5.8	4.7	6.1
2.5–5M	23	0	23	12.1	0.0	15.6
1–2.5M	11	2	9	5.8	4.7	6.1
750K–1M	7	2	5	3.7	4.7	3.4
500–750K	4	2	2	2.1	4.7	1.4
250–500K	8	1	7	4.2	2.3	4.8
<250K	12	2	10	6.3	4.7	6.8

State Distribution: Overall vs. Sector
State	Count (Overall)	Count (Local Gov)	Count (Nonprofit)	Percent (Overall)	Percent (Local Gov)	Percent (Nonprofit)
New York	23	7	16	10.3	13.5	9.4
Florida	18	7	11	8.1	13.5	6.4
Pennsylvania	17	3	14	7.6	5.8	8.2
California	16	3	13	7.2	5.8	7.6
Texas	14	5	9	6.3	9.6	5.3
Illinois	11	0	11	4.9	0.0	6.4
Michigan	11	1	10	4.9	1.9	5.8
Massachusetts	10	0	10	4.5	0.0	5.8
New Jersey	9	4	5	4.0	7.7	2.9
Georgia	7	2	5	3.1	3.8	2.9
Indiana	7	1	6	3.1	1.9	3.5
North Carolina	7	1	6	3.1	1.9	3.5
Ohio	6	0	6	2.7	0.0	3.5
Virginia	6	1	5	2.7	1.9	2.9
Colorado	5	2	3	2.2	3.8	1.8
Maryland	5	1	4	2.2	1.9	2.3
Washington	5	1	4	2.2	1.9	2.3
Oklahoma	4	0	4	1.8	0.0	2.3
Tennessee	4	1	3	1.8	1.9	1.8
Delaware	3	2	1	1.3	3.8	0.6
Louisiana	3	1	2	1.3	1.9	1.2
Minnesota	3	2	1	1.3	3.8	0.6
Nebraska	3	1	2	1.3	1.9	1.2
Oregon	3	1	2	1.3	1.9	1.2
South Carolina	3	1	2	1.3	1.9	1.2
Connecticut	2	0	2	0.9	0.0	1.2
Kansas	2	0	2	0.9	0.0	1.2
Kentucky	2	1	1	0.9	1.9	0.6
Vermont	2	0	2	0.9	0.0	1.2
Wisconsin	2	0	2	0.9	0.0	1.2
Alabama	1	0	1	0.4	0.0	0.6
Arkansas	1	1	0	0.4	1.9	0.0
Iowa	1	0	1	0.4	0.0	0.6
Missouri	1	1	0	0.4	1.9	0.0
Nevada	1	0	1	0.4	0.0	0.6
New Hampshire	1	0	1	0.4	0.0	0.6
Rhode Island	1	0	1	0.4	0.0	0.6
South Dakota	1	0	1	0.4	0.0	0.6
West Virginia	1	1	0	0.4	1.9	0.0
Wyoming	1	0	1	0.4	0.0	0.6

Numeric demographics: Overall vs. Sector
Variable	N (Overall)	Mean (Overall)	SD (Overall)	Median (Overall)	Min (Overall)	Max (Overall)	N (Local Gov)	Mean (Local Gov)	SD (Local Gov)	Median (Local Gov)	Min (Local Gov)	Max (Local Gov)	N (Nonprofit)	Mean (Nonprofit)	SD (Nonprofit)	Median (Nonprofit)	Min (Nonprofit)	Max (Nonprofit)
age	223	42.97	11.51	42	4	71	52	44.65	11.45	44.0	23	71	171	42.46	11.49	41	4	71
Duration..in.seconds.	223	499.55	241.38	426	186	1851	52	538.77	252.15	454.5	268	1465	171	487.63	236.80	420	186	1851

Grant Experience / Capacity (respondent-level; NA counted as no): Overall vs. Sector
Variable	Count (Overall)	Percent (Overall)	Count (Local Gov)	Percent (Local Gov)	Count (Nonprofit)	Percent (Nonprofit)
grant_capacity_1	127	57.0	29	55.8	98	57.3
grant_capacity_2	124	55.6	29	55.8	95	55.6
grant_capacity_3	118	52.9	28	53.8	90	52.6
grant_capacity_4	69	30.9	22	42.3	47	27.5
grant_capacity_5	159	71.3	37	71.2	122	71.3
grant_exp	167	74.9	36	69.2	131	76.6
grant_exp_federal	104	46.6	19	36.5	85	49.7
grant_exp_foundation	125	56.1	19	36.5	106	62.0
grant_exp_local	61	27.4	16	30.8	45	26.3
grant_exp_state	77	34.5	19	36.5	58	33.9
grants_decide	136	61.0	29	55.8	107	62.6
grants_job	69	30.9	13	25.0	56	32.7

Manipulation Checks

2x2 Table of Perceived vs. Assigned Sector Treatment
Perceived Treatment	Local Government	Nonprofit
Local Government	23.32	0.45
Nonprofit	0.00	76.23

##                   
##                    Local Government Nonprofit
##   Local Government              468         9
##   Nonprofit                       0      1530

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  sector_contingency
## X-squared = 1952.1, df = 1, p-value < 2.2e-16

Manipulation between-subjects worked.

## [1] 0.08520179

## 
##    0    1 
##  171 1836

## Warning: Unknown or uninitialised column: `mani`.

## < table of extent 0 >

Only about 9% of the sample failed the manipulation check on the treatment.

Attention Check

## [1] 0.004484305

Over 99% passed the attention check.

Thematic Checks

##                             mean diff_from_4       p_value
## themes_amount_1_num     6.345291   2.3452915  0.000000e+00
## themes_complexity_1_num 4.775785   0.7757848 1.854962e-154
## themes_complexity_2_num 4.932735   0.9327354 4.411294e-229
## themes_complexity_3_num 5.058296   1.0582960 2.130235e-300
## themes_complexity_4_num 5.269058   1.2690583  0.000000e+00
## themes_reporting_1_num  5.269058   1.2690583 1.739165e-281
## themes_reporting_2_num  4.816143   0.8161435 4.373970e-150

All thematic checks passed.

Robustness Checks

Analysis on grants_decide = 1

Establish Base LPM


	Respondents Managing Grants
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.640***
	(0.059)
Increased Application Complexity	−0.182**
	(0.059)
More Frequent Reporting	−0.112+
	(0.059)
Num.Obs.	1224
R2	0.589
R2 Adj.	0.536
Respondent Fixed Effects	Yes

Segment by Award Amount


	Lower Award Amount	Higher Award Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.056	−0.397***
	(0.065)	(0.082)
More Frequent Reporting	0.012	−0.235**
	(0.065)	(0.082)
Num.Obs.	544	408
R2	0.556	0.896
R2 Adj.	0.405	0.843
Respondent Fixed Effects	Yes	Yes

Segment by Reporting Requirements


	Less Frequent Reporting	More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.603***	0.699***
	(0.094)	(0.077)
Increased Application Complexity	−0.029	−0.287***
	(0.094)	(0.077)
Num.Obs.	408	544
R2	0.654	0.752
R2 Adj.	0.477	0.668
Respondent Fixed Effects	Yes	Yes

Segment by Application Complexity


	Reduced Application Complexity	Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.588***	0.643***
	(0.093)	(0.077)
More Frequent Reporting	−0.015	−0.196*
	(0.093)	(0.077)
Num.Obs.	408	544
R2	0.717	0.728
R2 Adj.	0.572	0.636
Respondent Fixed Effects	Yes	Yes

Segment by Sector

Base Model by Sector


	Nonprofit	Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.658***	0.572***
	(0.066)	(0.131)
Increased Application Complexity	−0.176**	−0.207
	(0.066)	(0.131)
More Frequent Reporting	−0.120+	−0.083
	(0.066)	(0.131)
Num.Obs.	963	261
R2	0.594	0.572
R2 Adj.	0.542	0.512
Respondent Fixed Effects	Yes	Yes

Segment by Sector and Award Amount


	Nonprofit, Lower Amount	Nonprofit, Higher Amount	Local Government, Lower Amount	Local Government, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.026	−0.393***	−0.166	−0.414*
	(0.072)	(0.091)	(0.151)	(0.190)
More Frequent Reporting	0.007	−0.224*	0.028	−0.276
	(0.072)	(0.091)	(0.151)	(0.190)
Num.Obs.	428	321	116	87
R2	0.554	0.901	0.574	0.879
R2 Adj.	0.402	0.850	0.418	0.813
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Reporting Requirements


	Nonprofit, Less Frequent Reporting	Nonprofit, More Frequent Reporting	Local Government, Less Frequent Reporting	Local Government, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.617***	0.738***	0.552*	0.552**
	(0.103)	(0.087)	(0.228)	(0.169)
Increased Application Complexity	−0.037	−0.308***	0.000	−0.207
	(0.103)	(0.087)	(0.228)	(0.169)
Num.Obs.	321	428	87	116
R2	0.681	0.755	0.542	0.745
R2 Adj.	0.518	0.671	0.289	0.652
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Application Complexity


	Nonprofit, Reduced Application Complexity	Nonprofit, Increased Application Complexity	Local Government, Reduced Application Complexity	Local Government, Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.654***	0.645***	0.345+	0.634***
	(0.104)	(0.088)	(0.201)	(0.165)
More Frequent Reporting	0.019	−0.196*	−0.138	−0.193
	(0.104)	(0.088)	(0.201)	(0.165)
Num.Obs.	321	428	87	116
R2	0.709	0.728	0.758	0.728
R2 Adj.	0.560	0.635	0.624	0.629
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Analysis on grants_job = 1

Establish Base LPM


	Respondents in Grant-Related Jobs
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.623***
	(0.084)
Increased Application Complexity	−0.180*
	(0.084)
More Frequent Reporting	−0.110
	(0.084)
Num.Obs.	621
R2	0.578
R2 Adj.	0.522
Respondent Fixed Effects	Yes

Segment by Award Amount


	Lower Award Amount	Higher Award Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.064	−0.406**
	(0.093)	(0.124)
More Frequent Reporting	0.006	−0.232+
	(0.093)	(0.124)
Num.Obs.	276	207
R2	0.552	0.879
R2 Adj.	0.397	0.816
Respondent Fixed Effects	Yes	Yes

Segment by Reporting Requirements


	Less Frequent Reporting	More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.551***	0.701***
	(0.127)	(0.111)
Increased Application Complexity	0.058	−0.284*
	(0.127)	(0.111)
Num.Obs.	207	276
R2	0.682	0.735
R2 Adj.	0.516	0.643
Respondent Fixed Effects	Yes	Yes

Segment by Application Complexity


	Reduced Application Complexity	Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.580***	0.603***
	(0.122)	(0.106)
More Frequent Reporting	−0.116	−0.180+
	(0.122)	(0.106)
Num.Obs.	207	276
R2	0.758	0.742
R2 Adj.	0.632	0.652
Respondent Fixed Effects	Yes	Yes

Segment by Sector

Base Model by Sector


	Nonprofit	Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.654***	0.492*
	(0.092)	(0.206)
Increased Application Complexity	−0.193*	−0.123
	(0.092)	(0.206)
More Frequent Reporting	−0.118	−0.077
	(0.092)	(0.206)
Num.Obs.	504	117
R2	0.586	0.546
R2 Adj.	0.531	0.474
Respondent Fixed Effects	Yes	Yes

Segment by Sector and Award Amount


	Nonprofit, Lower Amount	Nonprofit, Higher Amount	Local Government, Lower Amount	Local Government, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.061	−0.393**	−0.077	−0.462
	(0.103)	(0.139)	(0.219)	(0.271)
More Frequent Reporting	0.025	−0.286*	−0.077	0.000
	(0.103)	(0.139)	(0.219)	(0.271)
Num.Obs.	224	168	52	39
R2	0.522	0.877	0.651	0.894
R2 Adj.	0.354	0.813	0.510	0.827
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Reporting Requirements


	Nonprofit, Less Frequent Reporting	Nonprofit, More Frequent Reporting	Local Government, Less Frequent Reporting	Local Government, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.607***	0.704***	0.308	0.692*
	(0.130)	(0.122)	(0.380)	(0.272)
Increased Application Complexity	0.036	−0.296*	0.154	−0.231
	(0.130)	(0.122)	(0.380)	(0.272)
Num.Obs.	168	224	39	52
R2	0.717	0.740	0.566	0.712
R2 Adj.	0.568	0.649	0.295	0.595
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Application Complexity


	Nonprofit, Reduced Application Complexity	Nonprofit, Increased Application Complexity	Local Government, Reduced Application Complexity	Local Government, Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.607***	0.671***	0.462	0.308
	(0.136)	(0.117)	(0.276)	(0.247)
More Frequent Reporting	−0.071	−0.221+	−0.308	0.000
	(0.136)	(0.117)	(0.276)	(0.247)
Num.Obs.	168	224	39	52
R2	0.754	0.744	0.788	0.744
R2 Adj.	0.625	0.655	0.655	0.640
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Analysis on grant_exp = 1

Establish Base LPM


	Respondents with Grant Experience
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.602***
	(0.054)
Increased Application Complexity	−0.173**
	(0.054)
More Frequent Reporting	−0.075
	(0.054)
Num.Obs.	1503
R2	0.579
R2 Adj.	0.525
Respondent Fixed Effects	Yes

Segment by Award Amount


	Lower Award Amount	Higher Award Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.032	−0.383***
	(0.059)	(0.076)
More Frequent Reporting	0.044	−0.216**
	(0.059)	(0.076)
Num.Obs.	668	501
R2	0.563	0.889
R2 Adj.	0.415	0.832
Respondent Fixed Effects	Yes	Yes

Segment by Reporting Requirements


	Less Frequent Reporting	More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.515***	0.681***
	(0.083)	(0.071)
Increased Application Complexity	0.000	−0.301***
	(0.083)	(0.071)
Num.Obs.	501	668
R2	0.655	0.742
R2 Adj.	0.479	0.655
Respondent Fixed Effects	Yes	Yes

Segment by Application Complexity


	Reduced Application Complexity	Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.599***	0.587***
	(0.083)	(0.070)
More Frequent Reporting	0.012	−0.144*
	(0.083)	(0.070)
Num.Obs.	501	668
R2	0.731	0.720
R2 Adj.	0.595	0.625
Respondent Fixed Effects	Yes	Yes

Segment by Sector

Base Model by Sector


	Nonprofit	Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.610***	0.572***
	(0.061)	(0.115)
Increased Application Complexity	−0.189**	−0.117
	(0.061)	(0.115)
More Frequent Reporting	−0.087	−0.033
	(0.061)	(0.115)
Num.Obs.	1179	324
R2	0.575	0.596
R2 Adj.	0.520	0.540
Respondent Fixed Effects	Yes	Yes

Segment by Sector and Award Amount


	Nonprofit, Lower Amount	Nonprofit, Higher Amount	Local Government, Lower Amount	Local Government, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.041	−0.382***	0.000	−0.389*
	(0.065)	(0.085)	(0.135)	(0.166)
More Frequent Reporting	0.026	−0.214*	0.111	−0.222
	(0.065)	(0.085)	(0.135)	(0.166)
Num.Obs.	524	393	144	108
R2	0.571	0.888	0.538	0.892
R2 Adj.	0.425	0.831	0.373	0.833
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Reporting Requirements


	Nonprofit, Less Frequent Reporting	Nonprofit, More Frequent Reporting	Local Government, Less Frequent Reporting	Local Government, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.519***	0.696***	0.500*	0.628***
	(0.090)	(0.081)	(0.204)	(0.151)
Increased Application Complexity	−0.046	−0.327***	0.167	−0.206
	(0.090)	(0.081)	(0.204)	(0.151)
Num.Obs.	393	524	108	144
R2	0.683	0.739	0.561	0.757
R2 Adj.	0.520	0.650	0.323	0.670
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Application Complexity


	Nonprofit, Reduced Application Complexity	Nonprofit, Increased Application Complexity	Local Government, Reduced Application Complexity	Local Government, Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.641***	0.588***	0.444*	0.583***
	(0.094)	(0.079)	(0.181)	(0.147)
More Frequent Reporting	0.031	−0.145+	−0.056	−0.139
	(0.094)	(0.079)	(0.181)	(0.147)
Num.Obs.	393	524	108	144
R2	0.732	0.710	0.736	0.752
R2 Adj.	0.595	0.612	0.593	0.663
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Analysis on grant_exp_federal = 1

Establish Base LPM


	Respondents with Federal Grant Experience
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.653***
	(0.067)
Increased Application Complexity	−0.136*
	(0.067)
More Frequent Reporting	−0.115+
	(0.067)
Num.Obs.	936
R2	0.597
R2 Adj.	0.546
Respondent Fixed Effects	Yes

Segment by Award Amount


	Lower Award Amount	Higher Award Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.050	−0.308**
	(0.072)	(0.095)
More Frequent Reporting	−0.008	−0.192*
	(0.072)	(0.095)
Num.Obs.	416	312
R2	0.541	0.895
R2 Adj.	0.384	0.841
Respondent Fixed Effects	Yes	Yes

Segment by Reporting Requirements


	Less Frequent Reporting	More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.673***	0.687***
	(0.103)	(0.089)
Increased Application Complexity	0.019	−0.198*
	(0.103)	(0.089)
Num.Obs.	312	416
R2	0.686	0.741
R2 Adj.	0.524	0.653
Respondent Fixed Effects	Yes	Yes

Segment by Application Complexity


	Reduced Application Complexity	Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.577***	0.667***
	(0.103)	(0.086)
More Frequent Reporting	−0.077	−0.198*
	(0.103)	(0.086)
Num.Obs.	312	416
R2	0.709	0.755
R2 Adj.	0.559	0.672
Respondent Fixed Effects	Yes	Yes

Segment by Sector

Base Model by Sector


	Nonprofit	Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.660***	0.625***
	(0.074)	(0.153)
Increased Application Complexity	−0.161*	−0.025
	(0.074)	(0.153)
More Frequent Reporting	−0.121	−0.088
	(0.074)	(0.153)
Num.Obs.	765	171
R2	0.593	0.622
R2 Adj.	0.540	0.566
Respondent Fixed Effects	Yes	Yes

Segment by Sector and Award Amount


	Nonprofit, Lower Amount	Nonprofit, Higher Amount	Local Government, Lower Amount	Local Government, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.045	−0.353**	−0.074	−0.105
	(0.080)	(0.106)	(0.174)	(0.215)
More Frequent Reporting	−0.002	−0.212*	−0.032	−0.105
	(0.080)	(0.106)	(0.174)	(0.215)
Num.Obs.	340	255	76	57
R2	0.546	0.893	0.519	0.910
R2 Adj.	0.389	0.837	0.335	0.857
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Reporting Requirements


	Nonprofit, Less Frequent Reporting	Nonprofit, More Frequent Reporting	Local Government, Less Frequent Reporting	Local Government, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.659***	0.711***	0.737*	0.579**
	(0.109)	(0.100)	(0.286)	(0.191)
Increased Application Complexity	−0.024	−0.254*	0.211	0.053
	(0.109)	(0.100)	(0.286)	(0.191)
Num.Obs.	255	340	57	76
R2	0.711	0.737	0.589	0.777
R2 Adj.	0.561	0.646	0.350	0.692
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Application Complexity


	Nonprofit, Reduced Application Complexity	Nonprofit, Increased Application Complexity	Local Government, Reduced Application Complexity	Local Government, Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.612***	0.666***	0.421*	0.674**
	(0.117)	(0.095)	(0.204)	(0.196)
More Frequent Reporting	−0.024	−0.205*	−0.316	−0.168
	(0.117)	(0.095)	(0.204)	(0.196)
Num.Obs.	255	340	57	76
R2	0.701	0.746	0.779	0.793
R2 Adj.	0.546	0.659	0.649	0.713
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Test assumptions about grant_capacity

## 
## Attaching package: 'psych'

## The following object is masked from 'package:car':
## 
##     logit

## The following object is masked from 'package:modelsummary':
## 
##     SD

## The following objects are masked from 'package:ggplot2':
## 
##     %+%, alpha

## Factor Analysis using method =  minres
## Call: fa(r = grant_vars_all, nfactors = 1, scores = "regression", fm = "minres", 
##     cor = "tet")
## Standardized loadings (pattern matrix) based upon correlation matrix
##                   MR1   h2    u2 com
## grant_capacity_1 0.87 0.75 0.246   1
## grant_capacity_2 0.97 0.93 0.068   1
## grant_capacity_3 0.89 0.79 0.210   1
## grant_capacity_4 0.82 0.68 0.323   1
## grant_capacity_5 0.36 0.13 0.871   1
## 
##                 MR1
## SS loadings    3.28
## Proportion Var 0.66
## 
## Mean item complexity =  1
## Test of the hypothesis that 1 factor is sufficient.
## 
## df null model =  10  with the objective function =  4.32 with Chi Square =  8663.85
## df of  the model are 5  and the objective function was  0.63 
## 
## The root mean square of the residuals (RMSR) is  0.1 
## The df corrected root mean square of the residuals is  0.14 
## 
## The harmonic n.obs is  1439 with the empirical chi square  266.07  with prob <  2e-55 
## The total n.obs was  2007  with Likelihood Chi Square =  1267.77  with prob <  6.1e-272 
## 
## Tucker Lewis Index of factoring reliability =  0.708
## RMSEA index =  0.355  and the 90 % confidence intervals are  0.339 0.371
## BIC =  1229.75
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy             
##                                                    MR1
## Correlation of (regression) scores with factors   0.99
## Multiple R square of scores with factors          0.98
## Minimum correlation of possible factor scores     0.95

## 
## Reliability analysis   
## Call: alpha(x = grant_vars)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean  sd median_r
##       0.84      0.83    0.79      0.55   5 0.0059 0.61 0.4     0.55
## 
##     95% confidence boundaries 
##          lower alpha upper
## Feldt     0.83  0.84  0.85
## Duhachek  0.83  0.84  0.85
## 
##  Reliability if an item is dropped:
##                  raw_alpha std.alpha G6(smc) average_r S/N alpha se   var.r
## grant_capacity_1      0.81      0.80    0.73      0.57 4.1   0.0074 3.3e-03
## grant_capacity_2      0.77      0.76    0.68      0.51 3.2   0.0089 1.8e-05
## grant_capacity_3      0.79      0.79    0.71      0.55 3.7   0.0081 1.3e-03
## grant_capacity_4      0.80      0.80    0.73      0.57 4.0   0.0076 3.4e-03
##                  med.r
## grant_capacity_1  0.57
## grant_capacity_2  0.52
## grant_capacity_3  0.57
## grant_capacity_4  0.57
## 
##  Item statistics 
##                     n raw.r std.r r.cor r.drop mean   sd
## grant_capacity_1 1872  0.82  0.80  0.69   0.63 0.61 0.49
## grant_capacity_2 1683  0.85  0.85  0.79   0.72 0.66 0.47
## grant_capacity_3 1530  0.81  0.82  0.73   0.68 0.69 0.46
## grant_capacity_4 1512  0.81  0.80  0.69   0.65 0.41 0.49
## 
## Non missing response frequency for each item
##                     0    1 miss
## grant_capacity_1 0.39 0.61 0.07
## grant_capacity_2 0.34 0.66 0.16
## grant_capacity_3 0.31 0.69 0.24
## grant_capacity_4 0.59 0.41 0.25

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
## -1.3908 -1.3908  0.4693  0.0000  1.0622  1.0622     819

## 
## ===============================================
##                         Dependent variable:    
##                     ---------------------------
##                        grant_capacity_index    
## -----------------------------------------------
## sectorNonprofit              -0.233***         
##                               (0.069)          
##                                                
## Constant                     0.180***          
##                               (0.061)          
##                                                
## -----------------------------------------------
## Observations                   1,188           
## R2                             0.010           
## Adjusted R2                    0.009           
## Residual Std. Error      0.996 (df = 1186)     
## F Statistic          11.420*** (df = 1; 1186)  
## ===============================================
## Note:               *p<0.1; **p<0.05; ***p<0.01

Being a nonprofit is associated with a 1/4 standard deviation reduction in the grant capacity index.

Establish Base LPM


	Lower Grant Capacity	Higher Grant Capacity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.688***	0.543***
	(0.096)	(0.078)
Increased Application Complexity	−0.356***	−0.050
	(0.096)	(0.078)
More Frequent Reporting	−0.164+	−0.002
	(0.096)	(0.078)
Num.Obs.	477	711
R2	0.578	0.602
R2 Adj.	0.521	0.550
Respondent Fixed Effects	Yes	Yes

Segment by Award Amount

Effects of Complexity and Reporting by Grant Capacity and Award Amount
	Lower Capacity, Lower Amount	Lower Capacity, Higher Amount	Higher Capacity, Lower Amount	Higher Capacity, Higher Amount
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.211+	−0.642***	0.078	−0.177*
	(0.107)	(0.135)	(0.079)	(0.087)
More Frequent Reporting	−0.053	−0.340*	0.099	−0.101
	(0.107)	(0.135)	(0.079)	(0.087)
Num.Obs.	212	159	316	237
R2	0.575	0.885	0.646	0.935
R2 Adj.	0.426	0.825	0.524	0.901
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Reporting Requirements

Effects of Award Amount and Application Complexity by Grant Capacity and Reporting Frequency
	Lower Capacity, Less Frequent Reporting	Lower Capacity, More Frequent Reporting	Higher Capacity, Less Frequent Reporting	Higher Capacity, More Frequent Reporting
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.528***	0.789***	0.481***	0.615***
	(0.143)	(0.127)	(0.134)	(0.105)
Increased Application Complexity	−0.189	−0.494***	0.101	−0.170
	(0.143)	(0.127)	(0.134)	(0.105)
Num.Obs.	159	212	237	316
R2	0.647	0.744	0.633	0.749
R2 Adj.	0.461	0.655	0.443	0.663
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Application Complexity

Effects of Award Amount and Reporting by Grant Capacity and Application Complexity
	Lower Capacity, Reduced Application Complexity	Lower Capacity, Increased Application Complexity	Higher Capacity, Reduced Application Complexity	Higher Capacity, Increased Application Complexity
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.642***	0.653***	0.608***	0.527***
	(0.143)	(0.117)	(0.133)	(0.107)
More Frequent Reporting	−0.075	−0.215+	0.076	−0.056
	(0.143)	(0.117)	(0.133)	(0.107)
Num.Obs.	159	212	237	316
R2	0.780	0.721	0.677	0.725
R2 Adj.	0.664	0.624	0.509	0.630
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector

Base Model by Sector

Base Model by Sector × Grant Capacity
	Lower Capacity, Nonprofit	Lower Capacity, Local Government	Higher Capacity, Nonprofit	Higher Capacity, Local Government
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.679***	0.727***	0.541***	0.550***
	(0.108)	(0.202)	(0.091)	(0.156)
Increased Application Complexity	−0.381***	−0.247	−0.029	−0.110
	(0.108)	(0.202)	(0.091)	(0.156)
More Frequent Reporting	−0.195+	−0.027	−0.023	0.060
	(0.108)	(0.202)	(0.091)	(0.156)
Num.Obs.	387	90	531	180
R2	0.556	0.676	0.605	0.599
R2 Adj.	0.496	0.621	0.553	0.540
Respondent Fixed Effects	Yes	Yes	Yes	Yes

Segment by Sector and Award Amount

Effects of Complexity and Reporting by Sector × Amount × Grant Capacity
	Lower Capacity, Nonprofit (Lower Amount)	Lower Capacity, Nonprofit (Higher Amount)	Lower Capacity, Local Gov (Lower Amount)	Lower Capacity, Local Gov (Higher Amount)	Higher Capacity, Nonprofit (Lower Amount)	Higher Capacity, Nonprofit (Higher Amount)	Higher Capacity, Local Gov (Lower Amount)	Higher Capacity, Local Gov (Higher Amount)
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Increased Application Complexity	−0.223+	−0.698***	−0.160	−0.400+	0.081	−0.068	0.070	−0.500*
	(0.121)	(0.159)	(0.230)	(0.224)	(0.090)	(0.096)	(0.167)	(0.188)
More Frequent Reporting	−0.102	−0.372*	0.160	−0.200	0.054	−0.068	0.230	−0.200
	(0.121)	(0.159)	(0.230)	(0.224)	(0.090)	(0.096)	(0.167)	(0.188)
Num.Obs.	172	129	40	30	236	177	80	60
R2	0.580	0.868	0.580	0.953	0.662	0.940	0.615	0.927
R2 Adj.	0.431	0.797	0.400	0.921	0.545	0.909	0.469	0.884
Respondent Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

Segment by Sector and Reporting Requirements

Effects of Award Amount and Application Complexity by Sector × Reporting × Grant Capacity
	Lower Capacity, Nonprofit (Less Frequent Reporting)	Lower Capacity, Nonprofit (More Frequent Reporting)	Lower Capacity, Local Gov (Less Frequent Reporting)	Lower Capacity, Local Gov (More Frequent Reporting)	Higher Capacity, Nonprofit (Less Frequent Reporting)	Higher Capacity, Nonprofit (More Frequent Reporting)	Higher Capacity, Local Gov (Less Frequent Reporting)	Higher Capacity, Local Gov (More Frequent Reporting)
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.465**	0.805***	0.800*	0.720*	0.508**	0.607***	0.400	0.640**
	(0.155)	(0.145)	(0.340)	(0.263)	(0.154)	(0.119)	(0.277)	(0.221)
Increased Application Complexity	−0.279+	−0.544***	0.200	−0.280	0.102	−0.139	0.100	−0.260
	(0.155)	(0.145)	(0.340)	(0.263)	(0.154)	(0.119)	(0.277)	(0.221)
Num.Obs.	129	172	30	40	177	236	60	80
R2	0.682	0.726	0.567	0.823	0.664	0.755	0.513	0.736
R2 Adj.	0.511	0.629	0.278	0.748	0.487	0.669	0.232	0.636
Respondent Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

Segment by Sector and Application Complexity

Effects of Award Amount and Reporting by Sector × Application Complexity × Grant Capacity
	Lower Capacity, Nonprofit (Reduced Complexity)	Lower Capacity, Nonprofit (Increased Complexity)	Lower Capacity, Local Gov (Reduced Complexity)	Lower Capacity, Local Gov (Increased Complexity)	Higher Capacity, Nonprofit (Reduced Complexity)	Higher Capacity, Nonprofit (Increased Complexity)	Higher Capacity, Local Gov (Reduced Complexity)	Higher Capacity, Local Gov (Increased Complexity)
Standard errors in parentheses. + p < 0.10, * p < 0.05, p < 0.01, * p < 0.001.
Higher Award Amount	0.651***	0.619***	0.600	0.800**	0.678***	0.519***	0.400	0.550**
	(0.157)	(0.130)	(0.357)	(0.277)	(0.155)	(0.128)	(0.260)	(0.189)
More Frequent Reporting	−0.047	−0.219+	−0.200	−0.200	0.034	−0.058	0.200	−0.050
	(0.157)	(0.130)	(0.357)	(0.277)	(0.155)	(0.128)	(0.260)	(0.189)
Num.Obs.	129	172	30	40	177	236	60	80
R2	0.781	0.711	0.779	0.768	0.663	0.713	0.722	0.764
R2 Adj.	0.664	0.608	0.632	0.668	0.485	0.614	0.561	0.675
Respondent Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

Regress Budget onto Sector

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##   1.000   6.000   9.000   9.016  12.000  17.000     297

## [1] 4.633595

## 
## ===============================================
##                         Dependent variable:    
##                     ---------------------------
##                           org_budget_num       
## -----------------------------------------------
## sectorNonprofit              -0.701***         
##                               (0.267)          
##                                                
## Constant                     9.558***          
##                               (0.235)          
##                                                
## -----------------------------------------------
## Observations                   1,710           
## R2                             0.004           
## Adjusted R2                    0.003           
## Residual Std. Error      4.626 (df = 1708)     
## F Statistic           6.876*** (df = 1; 1708)  
## ===============================================
## Note:               *p<0.1; **p<0.05; ***p<0.01

## [1] 0.1602592

Being a nonprofit is also associated with reduction in organization budgets of about one-sixth of a standard deviation.

Cost of Compliance Analysis

Corbin M. Walls

2025-10-09

Data & Packages

Packages

Data

Clean Prolific Exports for Duplicate Submissions

Clean Variables

Choice Variables

employer

attention

grants_decide

grants_job

grant_exp

grant_capacity

org_budget

age

gender

race

state

edu

party

Manipulation Check Variables

Thematic Check Variables

Between-Subjects Treatment Values & Order Randomization

Reformat Dataset for Choice-Level Observations

Add in Treatment Variables

Order Variables Neatly

Analysis

Establish Base LPM

Segment by Award Amount

Segment by Reporting Requirements

Segment by Application Complexity

Segment by Sector

Base Model by Sector

Segment by Sector and Award Amount

Segment by Sector and Reporting Requirements

Segment by Sector and Application Complexity

Appendices

Power Analysis

Sample Demographics

Manipulation Checks

Attention Check

Thematic Checks

Robustness Checks

Analysis on grants_decide = 1

Establish Base LPM

Segment by Award Amount

Segment by Reporting Requirements

Segment by Application Complexity

Segment by Sector

Base Model by Sector

Segment by Sector and Award Amount

Segment by Sector and Reporting Requirements

Segment by Sector and Application Complexity

Analysis on grants_job = 1

Establish Base LPM

Segment by Award Amount

Segment by Reporting Requirements

Segment by Application Complexity

Segment by Sector

Base Model by Sector

Segment by Sector and Award Amount

Segment by Sector and Reporting Requirements

Segment by Sector and Application Complexity

Analysis on grant_exp = 1

Establish Base LPM

Segment by Award Amount

Segment by Reporting Requirements

Segment by Application Complexity

Segment by Sector

Base Model by Sector

Segment by Sector and Award Amount

Segment by Sector and Reporting Requirements

Segment by Sector and Application Complexity

Analysis on grant_exp_federal = 1

Establish Base LPM

Segment by Award Amount

Segment by Reporting Requirements

Segment by Application Complexity