Benchmarking Labor Courts: An Efficiency Frontier Analysis

Variable	Meaning	Type of Variable	Unit
OUT-GOING	Total Solved Cases in the year	Output	Number/Year
TRAMITING	Total Stopped Cases in the year	Output	Number/Year
SENTENCED	Total Sentences in the year	Output	Number/Year
EXISTENT	Initial Stock of Cases in the year	Input	Number/Year
INCOMING	Total Incoming Cases in the Year	Input	Number/Year
RE-INCOMING	Total Re-Incoming Cases in the Year	Input	Number/Year
CASELOAD	Total Cases (existent + incoming + re-incoming) in the year	Input	Number/Year
PROF	Total Staff with College Degree	Input	Number/Year
NOPROF	Total of Personnel with no College Degree	Input	Number/Year
SENSTAFF	Seniority of all Personnel in Months	Environmental	Months
SENJUDGE	Seniority of Judges in Months	Environmental	Months
AGESTAFF	Age of All Personnel in Months	Environmental	Months
AGEJUDGE	Age of Judges in Months	Environmental	Months
SURROGATE	Surrogate Judge (1 yes, 0 no)	Environmental	Dummy
TENURED	Proportion of Tenured Personnel on Total	Environmental	Proportion
PROMOTION	Average Time to Promotion in Months	Environmental	Months
FEMALE	Proportion of Female Personnel on Total	Environmental	Proportion
APPEALED	1/Re-Incoming	Quality	Proportion
BACKLOG	Average time spent from incoming to sentenced	Quality	Days
PRODUCTIVITYSTAFF	Ratio Sentenced/Staff	Quality	Proportion

[i] Source: Own Elaboration based on data provided by the PJN.

Informative needs to estimate operative efficiency in courts of justice.
Source: Own Elaboration.

Table 2

Descriptive Statistics of the Database (2006–2012).

Variable (Short Denomination)	Observations	Average	Standard Deviation	Minimum	Maximum
OUT-COMING	560	400.59	85.62	232.00	778.00
TRAMITING	560	712.06	329.74	155.00	1746.00
SENTENCED	560	200.43	49.16	82.00	541.00
EXISTENT	560	589.48	265.92	136.00	1406.00
INCOMING	560	509.56	135.87	288.00	839.00
RE-INCOMING	560	12.20	16.86	0.00	134.00
CASELOAD	560	1111.26	373.39	471.00	2133
PROF	560	7.38	2.14	2.00	13.00
NOPROF	560	5.07	1.99	0.00	10.00
SENSTAFF	560	220.56	29.29	122.26	309.58
SENJUDGE	560	348.90	134.25	0.00	744.12
AGESTAFF	560	536.94	35.29	438.06	684.59
AGEJUDGE	560	705.10	105.93	425.60	1003.23
SURROGATE	560	0.27	0.44	0.40	1.00
TENURED	560	0.81	0.15	0.40	1.00
PROMOTION	560	108.68	25.37	49.76	206.89
DEGREE	560	0.60	0.13	0.22	1.00
FEMALE	560	0.65	0.14	0.20	1.00
APPEALED	560	0.29	0.30	0.01	1.00
BACKLOG	560	511.41	167.51	169.40	1029.14
PRODUCTIVITYSTAFF	560	17.56	8.06	7.56	64.67

[i] Source: Own Elaboration based on data provided by the PJN.

Table 3

Results: Efficiency Scores and Efficient Units.

Model A1 CRS	2006	2007	2008	2009	2010	2011	2012
Average	0.866	0.854	0.879	0.875	0.910	0.852	0.899
Standard Deviation	0.071	0.072	0.069	0.069	0.066	0.078	0.073
Mean Deviation	0.053	0.053	0.052	0.050	0.051	0.061	0.055
Coefficient of Variation	0.082	0.085	0.079	0.079	0.073	0.092	0.082
# Efficient Courts	5	4	6	6	6	6	6
Model B1 VRS	2006	2007	2008	2009	2010	2011	2012
Average	0.893	0.926	0.912	0.918	0.935	0.887	0.934
Standard Deviation	0.070	0.054	0.055	0.057	0.052	0.070	0.058
Mean Deviation	0.055	0.045	0.043	0.043	0.043	0.058	0.047
Coefficient of Variation	0.078	0.058	0.061	0.063	0.056	0.079	0.062
# Efficient Courts	12	13	9	14	15	9	18

[i] Source: Own Elaboration.

Table 4

Descriptive Statistics and Correlation among Efficiency Scores and Labor Productivity.

Variable	Observations	Mean	Std. Dev.	Minimum	Maximum
A1	560	0.8764	0.0739	0.5780	1.00
B1	560	0.9151	0.0620	0.6810	1.00
PRODUCTIVITYSTAFF	560	17.55	8.06	7.5600	64.67
Correlation	A1	B1	Productivity
A1	1.0000
B1	0.6794	1.0000
PRODUCTIVITYSTAFF	0.1973	0.3958

[i] Source: Own Elaboration.

Table 5

Characterization of Courts by Quartiles of Efficiency (2006–2012).

STATISTIC/QUARTILE	SENTENCED	PROF	NOPROF	CASELOAD	APPEALED	BACKLOG	A1	B1	SENTENCED/STAFF
Avg 1Q	198	6.7	4.3	1200	0.28	622	0.9607	0.9772	20.93
Avg 2Q	205	7.7	5.5	1137	0.25	547	0.8992	0.9257	16.06
Avg 3Q	206	7.9	5.3	1100	0.25	490	0.8609	0.8961	16.14
Avg 4Q	194	7.3	5.2	1007	0.20	386	0.7851	0.8616	17.11
Std dev 1Q	22	0.3	0.4	39	0.11	16	0.0097	0.0092	2.90
Std dev 2Q	11	0.5	0.2	44	0.12	18	0.0013	0.0058	1.69
Std dev 3Q	12	0.3	0.4	53	0.12	34	0.0017	0.0083	1.13
Std dev 4Q	8	0.3	0.3	63	0.10	31	0.0067	0.0107	2.75

[i] Source: Own Elaboration.

Table 6

Explanatory Variables of DEA Efficiency Scores (Model A1).

Independent Variables	Coefficient	Std. Err.	P > \|t\|
A1 Scores (dependent)
SENSTAFF	0.00129808	0.0010917	0.235
SENSTAFFSQ	–1.483E-06	2.47E-06	0.548
AGESTAFF	0.00089526	0.0018486	0.628
AGESTAFFSQ	–9.55E-07	1.65E-06	0.564
TENURED	0.00981791	0.0185248	0.596
FEMALE	0.00524788	0.0338406	0.877
SENJUDGE	–0.00027219**	0.0001352	0.045
SENJUDGESQ	3.115E-07	2.18E-07	0.153
AGEJUDGE	0.00075295*	0.0004291	0.08
AGEJUDGESQ	–5.442E-07*	2.96E-07	0.067
SURROGATE	0.01871086***	0.0068849	0.007
YEAR
2007	–0.01222047	0.0076017	0.109
2008	0.01407364*	0.0075221	0.062
2009	0.00878915	0.0076876	0.254
2010	0.04176085***	0.0078122	0
2011	–0.01864879**	0.0081705	0.023
2012	0.02696162***	0.0084966	0.002
CONSTANT	0.23151226	0.4728159	0.625
N	560
F-statistic	8.02
Rsq	0.22752614

[i] * p < .1; ** p < .05; *** p < .01.

Source: Own Elaboration.

Table 7

Characterization of Courts by Quartiles of Efficiency and Environment (2006–2012).

STATISTIC/QUAR-TILE	Avg 1Q	Avg 2Q	Avg 3Q	Avg 4Q	Std dev 1Q	Std dev 2Q	Std dev 3Q	Std dev 4Q
A1 EFFICIENCY SCORES	0,9607	0,8992	0,8609	0,7851	0,0097	0,0013	0,0017	0,0067
SENSTAFF	222	226	219	215	4	3	4	6
AGESTAFF	548	542	531	526	9	6	5	6
SENJUDGE*	338	354	354	350	26	30	28	27
AGEJUDGE*	719	709	699	694	21	15	15	11
SURROGATE*	0,33	0,29	0,21	0,24	0,04	0,11	0,17	0,12
TENURED	0,83	0,82	0,80	0,79	0,01	0,02	0,02	0,01
FEMALE	0,61	0,67	0,67	0,65	0,03	0,03	0,02	0,02
AGESTAFFSQ	302009	294844	283004	278312	10423	7567	5462	6250
AGEJUDGESQ*	526929	512367	500582	493566	29182	28577	22369	22516
SENSTAFFSQ	50585	51566	48524	47337	2484	1081	1985	2394
SENJUDGESQ	136543	142806	142688	136853	31538	36886	34336	19658

[i] * Significant variables in the regression model.

Source: Own Elaboration.

Table A1

Summary of Literature Review.

Author	Method (See Section 3)	Yearly sample	Period	Place	Outputs	Inputs	Environmental
Beenstock and Haitovsky (2004)	Regression	25	1964–95	Israel	Case completion	Cases lodged, cases pending, number of judges
Bhattacharya and Smyth (2001)	Regression	28	1999	Australia	Citations in jurisprudence	Age, age square
Pedraja-Chaparro and Salinas-Jiménez (1996)	DEA	21	1991	Spain	Cases ending in Judgement; cases ending in another resolution	Judges, Staff
Deyneli (2012)	DEA, two stages	22	2006	22 European Countries	Resolved cases	Judges, Staff	Judge salaries, judge education and number of courts
Dimitrova-Grajzl et al (2012)	Regression	360	2008	Slovenia	Resolved cases	Judges, staff	Education, experience, salary, gender, recent promotion, imminent promotion
Elbialy and García Rubio (2011)	DEA	22	2010	Egypt	Resolved cases	Judges, staff, computers per court
Espasa and Esteller-Moré (2011)	SFA	119	2005–2009	Catalonia, Spain	Resolved cases	Staff	Various considering vacancies, temporary workers, vacancies, pending cases, trends, immigrants percentage
Falavigna et al. (2015)	DEA, directional function	309	2009–2011	Italy	Resolved cases	Judges	Court delays
Ferrandino (2014)	DEA	20	1993–2008	Florida, USA	Resolved cases per judge	Judges
Ferro et al. (2018)	DEA, two stages	82	2006–2010	Argentina	Resolved cases	Professional staff, non-professional staff, age, seniority	Workload
Finocchiaro-Castro and Guccio (2018)	DEA, two stages			Italy	Resolved civil cases, resolved criminal cases	Judges, Staff, Civil caseload and Criminal caseload
Fusco et al (2018)	DEA	26	2005–2011	Italy	Enrolled trials, unresolved trials, resolved trials	Magistrates, Wiretapping expenses
Gorman and Ruggiero (2009)	DEA	151	2001	USA	Felony jury verdicts, felony cases closed, misdemeanor cases closes, population	Prosecutors, other staff	Median income, minority population, bachelor’s degree
Guzowska and Strack (2010)	DEA	45	2007	Poland	Completed criminal cases, criminal cases discontinued, refusal to institute proceedings	Specialists, auxiliary staff, other inputs, various costs measures
Hagstedt and Proos (2008)	DEA	21	2006–2007	Sweden	Case settled per 1000 inhabitants	Wages, administrative costs
Ippoliti and Ramello (2016)	DEA, two stages	103	2009–2011	Italy	Resolved cases	Judges, Pending cases, Incoming cases	Technical efficiency score
Kittelsen and Førsund (1992)	DEA, Malmquist	107	1983–86	Norway	Seven crime categories	Judges, Staff
Lewin et al (1982)	DEA	30		North Carolina, USA	Number of judgements, number of cases pending less than 90 days	Caseload, Number of district attorneys and staff, Days of a court held, Number of misdemeanors within the caseload, Size of population
Major (2015)	DEA	26	2013	Poland	Resolved cases	Judges, Assistants, Officials
Mattsson et al. (2018)	DEA, Malmquist, Bootstrap	48	2012–2015	Sweden	Resolved civil cases, resolved criminal, real estate and environmental cases and resolved matters	Judges, Clerks, Other personnel, Office space
Nissi and Rapposelli (2010)	DEA	26	2008	Italy	Finished cases	Number of Judges, New cases filed during the year, Number of pending cases (filed+pending=caseload)
Odhiambo (2014)	FDH	119	2014–2016	Kenya	Civil cases criminal cases	Filed cases, staff
Pedraja-Chaparro and Salinas-Jiménez (1996)	DEA	21	1991	Spain	Cases fully resolved, other resolved cases	Number of Judges, Number of staff
Rushid (2018)	Stochastic Distance Function	102	2000–2016	Sweden	Resolved criminal cases, resolved civil cases, resolved matters	Judges, Clerks, Other personnel (full time equivalent)
Santos and Amado (2014)	DEA	223	2007–2011	Portugal	43 different case types (civil jurisdiction)	Judges, Staff
Schneider (2005)	DEA, two stages	9	1980–1998	Germany	Number of cases	Judges, Caseload	Judges salaries, training and number of courts
Tulkens (1993)	FDH	187	1983–85	Belgium	Civil and commercial settled cases, Family arbitration sessions held, minor offense cases settled	Staff
Yeung (2018)	DEA	27	2009–2015	Brazil	Number of decisions, weighted by workload	Judges, Staff
Yeung and Azevedo (2011)	DEA	27		Brazil	Number of first and second instance judgements	Judges, Staff

[i] References: DEA = Data Envelopment Analysis; SFA = Stochastic Frontier Analysis; FDH = Free Disposal Hull.

Source: Own Elaboration.

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.36745/ijca.313 | Journal eISSN: 2156-7964

Journal RSS Feed

Language: English

Page range: 7 - 7

Published on: Aug 10, 2020

Published by: International Association for Court Administration

In partnership with: Paradigm Publishing Services

Keywords:

Courts,

Efficiency,

Benchmarking,

Data Envelopment Analysis

© 2020 Gustavo Ferro, Victoria Oubiña, Carlos Romero, published by International Association for Court Administration
This work is licensed under the Creative Commons Attribution 3.0 License.

Volume 11 (2020): Issue 2

Benchmarking Labor Courts: An Efficiency Frontier Analysis

Figures & Tables

Table 1

Diagram 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table A1

Paradigm

My account