DOES QUICK MEAN BETTER? - Law and Economics Conference

DOES QUICK MEAN BETTER?
MEASURING THE DETERRENT EFFECT OF THE ‘24 HOURS COURTS’
Kamil JOŃSKI
(Warsaw School of Economics)
I. INTRODUCTION
The introduction of the accelerated procedure known as ’24 hours courts’ into polish Code of
Criminal Procedure (PL: KPK)1 had been one of the most controversial reform in this field
during recent years.’24 hours courts’ was expected to be an effective tool to deter hooligans
and to improve criminal courts efficiency. However the project was widely criticized by
criminologists and criminal procedure experts2.
This paper contributes to the discussion about a deterrent effect of the ’24 hours courts’ by
providing econometric assessment of this effect. In light of fact that the most significant part
of ’24 hours court’ caseload are crimes described in article 178a Criminal Code – driving a
motor vehicle with blood levels of alcohol in excess of a legal limit, research methodology is
based on the number of road accidents caused by intoxicated drivers.
The basic model specification provides strong evidence about statistically significant deterrent
effect of the ’24 hours courts’. Also after controlling for another factors affecting number of
people who drive a motor vehicle while intoxicated, especially random road checks, the effect
remains statistically significant but estimated coefficient slightly decrease. These findings can
be interpreted as an empirical confirmation, that introduction of the ’24 hours courts’ has a
deterrent effects. However existing research, based on descriptive statistics, seriously
overestimated that effect.
1
Ustawa z dnia 6 czerwca 1997 r. - Kodeks postępowania karnego (Dz. U. 1997 nr 89 poz. 555) e. g. prof. Z. Hołda’s interview with ‘Dziennik Gazeta Prawna’, Należy znieść 24-godzinne sądy, DGP, 30 Oct.
2007 2
1 II. ‘24 HOURS COURTS’ – INSTITUTIONL BACKGROUND
The accelerated criminal procedure was introduced to the Polish Code of Criminal Procedure
in Chapter 51 (since 12 March 2007). There is possibility to use it, when simultaneously (a)
offender was arrested while committing a crime or shortly after that, so no complex evidence
procedure is required, (b) the potential penalty is not bigger than five years imprison and (c)
the rendition from the Police to the court takes up to 24 hours (Article 517b § 1. Code of
Criminal Procedure). The offender can be sentenced up to two years imprison (Article 517 g §
3), he has the right to use the services of defense counsel (private or paid by taxpayers)
(Article 517 j) and has the right to appeal within 7 days after the sentence (Article 517 h § 3).
During the trial, judge can order breaks but totally not longer than 14 days (Article 517 f).
The establishing of the ’24 hours courts’ required also some changes in prosecutor offices and
courts organization. Especially, it states prosecutors3, judicial4 and attorneys5 duties. In courts
with 35 or more judges there are duties from 8 AM to 8 PM, and in courts with 50 or more
judges even 24 hours ones.
The introduction of ’24 hours courts’ has two main goals:
• To improve court efficiency (by moving simple cases from normal proceedings which requires more formal steps - to the accelerated ones)6. However it was
expressed, that ’24 hours courts’ may became to be a ‘competition for well-designed
simplified procedures already existing in the Code of Criminal Procedure)’7.
• To create additional deterrent incentives for hooligans (by shortening delay between
the crime and the penalty8). Assumption, that speedy trial generates additional
deterrence incentives, is implied by Becker’s (1968) economic theory of crime, where
expected cost of a crime is discounted using individual discount rate and time of delay
before the penalty is imposed.
3
Rozporządzenie Ministra Sprawiedliwości z dnia 23 lutego 2007 r. zmieniające rozporządzenie - Regulamin
wewnętrznego urzędowania powszechnych jednostek organizacyjnych prokuratury (Dz. U. 2007 nr 38 poz. 250) 4
Rozporządzenie Ministra Sprawiedliwości z dnia 23 lutego 2007 r. Regulamin urzędowania sądów
powszechnych (Dz. U. 2007 nr 38 poz. 249) 5
Rozporządzenie Ministra Sprawiedliwości z dnia 22 lutego 2007 r. w sprawie zapewnienia oskarżonemu
możliwości korzystania z pomocy obrońcy, jego wyboru w postępowaniu przyspieszonym oraz organizacji
dyżurów adwokackich (Dz. U. 2007 nr 38 poz. 248) 6
Z. Ziobro in: Sądy 24-godzinne już latem, Dziennik Gazeta Prawna, 5 April 2006 7
prof. Z. Hołda’s interview with ‘Dziennik Gazeta Prawna’, Należy znieść 24-godzinne sądy, DGP, 30 Oct.
2007 8
Czabański J., (2009) 2 In practice, ’24 hours courts’ became to be seen as a spectacular failure. Instead of hooligans,
majority of the defendants were intoxicated car or even bike drivers. Also costs of the new
solution were seriously underestimated. Especially attorneys duties turned out to be a serious
burden for taxpayers9. According to the Police, additional cost of usage accelerated procedure
in one case reach approximately 600 PLN (≈150 Euro)10.
’24 hours courts’ also meet another problems, such as serious constitutional doubts
concerning Police right to hold a defendant in arrest up to the accelerated trial11.
On the contrary, solution widely criticized by the experts was warmly welcomed by public.
Survey conducted for Ministry of Justice indicated, that 71 percent of the respondents heard
about ’24 hours courts’ and over 47 percent believe, that they work properly (only 24 percent
expressed opposite opinion). People who assessed ’24 hours courts’ as good working argued
that they provides fast adjudication (60,5 percent) and operates efficiently (27,3 percent).
People who expressed opposite opinion said usually that ’24 hours courts’ are only PR
activity (19,1 percent), they focus on irrelevant issues (18,8 percent) and that they violate the
right to defend (17,2 percent)12. However there is necessarily to underline that Polish society
is characterized by high expectations about the severity of the law.
III. THE MODEL
In light of fact that the most significant part of ’24 hours courts’ offenders are intoxicated
drivers, the measurement methodology is based on the frequency of this crimes. Examined
crimes are penalized in art. 178a of the Criminal Code – driving a motor vehicle with blood
levels of alcohol in excess of a legal limit.
However, there is pointless to analyze the number of recorded crimes. This value can not
reflect the actual number of drunken drivers, because it is affected by the number of Police
road checks (and their effectiveness in identifying drunken drivers).
Similar to the approach described by Czabański (2009), applied model uses the number of
road accidents caused by intoxicated drivers (al_acc) as a proxy for criminal activity.
9
Bilans sądów 24 godzinnych, Dziennik Gazeta Prawna, 8 May 2007 Sądy 24 godzinne będą wolniejsze, ale tańsze, ‘Rzeczpospolita’ Daily, 6 Jul 2008 11
Sądy 24 godzinne do Trybunału, Dziennik Gazeta Prawna, 17 May 2007 12
Raport końcowy, Badanie opinii publicznej na temat wizerunku wymiaru sprawiedliwości, oceny reformy
wymiaru sprawiedliwości, aktualnego stanu świadomości społecznej w zakresie alternatywnych sposobów
rozwiązywani sporów oraz praw osób pokrzywdzonych przestępstwem, Warsaw, February 2009, p. 47 - 49 10
3 At this point there is valuable to point that literature describes two sorts of policies aimed at
reducing the frequency of driving while intoxicated. The first (indirect) is controlling alcohol
consumption (e.g. by taxation or imposing age limitations in access to the alcohol). The
second one is based on deteriorating potential drivers13. Both policies were empirically
examined to explore their abilities to control the problem. Researchers proved that
deteriorating legislation can be effective14.
For example Kenkel (1993) concluded that
“Simulating a substantial increase in the number of [US] states with deterrence laws, drunk
driving is predicted to decrease by almost 20 percent. To achieve comparable reduction
through alcohol-control policies instead involves a national minimum legal drinking age of
21 and new taxes to increase alcohol prices by 23 percent”15.
However this study differs from them substantially, because its purpose is to measure
deterrent effect of the ’24 hours courts’, not to evaluate policies designed for reducing drunk
driving (it was not a primary objective of the ’24 hours courts’ introduction). Examination of
the number of accidents caused by intoxicated drivers was used only as a measurement tool
(the proxy for criminal activity).
Also it is crucial to realize, that number of accidents caused by intoxicated drivers depends
not only from the number of intoxicated drivers, but also from many other ‘objective’ factors
like roads quality or weather conditions, just to name few. To capture all these factors, the
model contains the variable dr_acc - the total number of accidents caused by drivers16. Figure
1. presents the correlations between the number of accidents caused by intoxicated drivers and
(a) total number of accidents caused by drivers and (b) total number of road accidents
(tot_cc).
As can be seen, the first one is better explanatory variable – it explains almost 80 percent of
the alc_acc variance (because total number of accidents captures several other accidents
causes e. g. cyclists and pedestrians).
13
Kenkel D., (1993), Driving and Deterrence: the Effectiveness and Social Costs of Alternative Policies, Journal
of Law and Economics, Vol. 36, No. 2, p. 877 14
They used both, state level data about road accidents e.g. Nichols J., Ross L., (1989), and surveys micro data –
Kenkel D., (1993) 15
Kenkel D., (1993), p. 879 16
Instead of total number of accidents used in the same purpose by Czabański (2009) 4 Figure 1 Correlations between variables alc_acc, dr_acc and tot_acc
Source: Own calculations based on published Police data
Figure 2. offers a visual image of the fallowing time series: (a) the number of accidents
caused by intoxicated drivers (left side hand variable in the model – al_acc), (b) the total
number of accidents caused by drivers (dr_acc), and (c) the residuals from the equation (1).
al_acc = α + β dr_acc + ε
(1)
As can be seen, the residuals significantly decrease during winters. This seasonality can be
explain by popular drinking patterns.
Figure 2 Number of accidents caused by drivers (right axis), the number of accidents caused
by intoxicated drivers and its seasonality (residuals) in years 2006 - 2009
Source: Own calculations based on published Police data
5 According to above, the baseline model specification is given by the equation (2):
al_acc = α + β dr_acc + γ season + δ 24_court + ε
(2)
where season is a seasonal dummy variable (1 in period from March to October, 0 otherwise),
and 24_court is a dummy variable for existence of the ‘24 hours courts’.
The baseline model was estimated using OLS on monthly time series. Starting observation is
Jan 2006 and the final one is Dec 2009. All used data was obtained from published Police
statistics17. Table 1. presents descriptive statistics for all variables.
Table 1 Descriptive statistics for all variables used in models
dr_acc
3741,00
2004,00
3102,60
496,67
3232,00
Max
Min
Mean
St. Dev.
Median
alc_acc
397,00
151,00
283,31
66,64
286,00
season
1,00
0,00
-
24_court
Police
456833,67 1,00
348553,33 0,00
402528,40 32476,00 391550 -
hype
1,00
0,00
-
Source: Own calculations based on published Police data
IV. RESULTS
Table 2 The baseline model estimation results
Independent variable:
dr_acc
season
24_court
N
R square
Doornik- Hansen test
No Autocorrelation
No colinearity
White test
alc_acc
0,100 ***
(0,007)
45,662 ***
(7,826)
-27,017 ***
(6,956)
48
0,90
OK
OK
OK
OK
The model includes constant
Level of statistical significance: *p < .10 **p < .05 ***p < .01
Source: Own calculations
17
Kmenda Główna Policji (2006), (2007), (2008), (2009). 6 Table 2 presents results of the baseline model OLS estimation. The variable 24_court shows
statistically significant negative impact on the number of traffic accidents caused by drunken
drivers (It can be said that ’24 hours courts’ introduction has decreased the number of
accidents caused by intoxicated drivers about 2718 per month). All tests were performed with
the level of statistical significance 0,05.
V. ROBUSTNESS
The evidence from the baseline model strongly suggests that ’24 hours courts’ introduction
has influenced the number of accidents caused by intoxicated drivers in statistically
significant way (which means that it deter potential intoxicated drivers). This section presents
robustness tests of this finding.
It can be expected, that three key factors omitted in the baseline equation could cause
observed effect.
The first one is the subjectively expected number of the Police road checks and sobriety
controls. The variable Police contains the average number of Police road checks in given
month. The data was collected from the Police Central Command (Komenda Główna Policji)
via official request for public information. Figure 3 gives a visual view of these data in
examined period (it presents also the number of Police sobriety controls – this data has been
collected since Q3 2007)
Figure 3 Police road checks and sobriety controls in examined period
Source: Police Central Command (KGP) unpublished data
18
With standard error 7 7 One of the main weaknesses of Police variable is its original quarterly frequency. However it
also can be seen as its strength, when we consider drivers imperfect information (about the
Police activities) and reverse causality issues.
Second factor is a possible long term change in drinking patterns, which makes drunk driving
less socially accepted. Table 3 describes details of two comparable (more or less) surveys
conducted in Poland during examined period.
Table 3 Ratio of citizens who drove after alcohol consumption – surveys evidences
Survey conducted
March 2006
January 2010
Sample size
1500
400
Company
TNS OBOP
Method
Pen & Pencil Interview
Drove intoxicated:
At least one time
17 percent
19 percent
More than one time
12 percent
9 percent
Source: TNS OBOP (2006), Fabryka Komunikacji Społecznej (2010)
With respect to the differences in the sample size, there is no evidence, that any social change
happened.
The third factor that may affected the results is a ‘media hype’ around the introduction of ’24
hours courts’. Similarly like the first problem, the impact of media hype, can be captured in
the model by adding another control variable. However, measuring such unobservable think
like media hype is quite complex issue. One very interesting approach, popularized in
econometrics by Varian and Choi (2009) is to use Google Trends as a quantitative proxy of
network users activities. Application of this approach to media hype measurement is
especially valuable, because it capture not media activity19 but, explicitly, the audience
response on it.
Figure 3 presents values of the Google Search Volume Index20 for terms ‘24’ and ‘sądy’ (PL:
courts). The media hype around ’24 hours courts’ is represented by simultaneous peak in both
19
Competing approach may be to prepare some index on the basis of news release frequency The procedure of data scaling and normalizing is described in
http://www.google.com/intl/en/trends/about.html#18 20
8 charts21. It can be seen, that it corresponds with ’24 hours courts’ introduction in 12 March
2007. To assess the deterrent effect of this hype, there was additional dummy variable hype
(value 1 for March 2007, 0 otherwise) included to the baseline model specification.
Figure 3 Google Search Volume Index for terms ‘24’ and ‘sądy’ (PL: courts)
Source: Google Trends, http://www.google.com/trends
Table 4 presents the estimation results for baseline model and its extensions described in this
section. There is visible, that all coefficients have expected signs (results for Police road
checks corresponding with previous studies e.g. Kenkel (1993)), and that even after
controlling for additional factors the variable 24_court remains statistically significant.
However the estimated coefficient decrease from 2722 to 2123. Also there is no evidence, that
media hype around ’24 hours courts’ establishing influenced the number of road accidents
caused by intoxicated drivers (it hs expected negative coefficient, but there is not statistically
different from zero).
21
There is only one such visible simultaneous peak in booth charts With standard error 7 23
With standard error 7 22
9 Table 4 Robustness tests results
Independent variable:
Dr_acc
Season
Court
Alc_acc
Alc_acc
0,100 ***
(0,007)
45,662 ***
(7,826)
-27,017 ***
(6,956)
0,094 ***
(0,008)
46,624 ***
(7,620)
-21,953 ***
(7,265)
-0,0002 *
(0,0001)
0,092
(0,008)
48,321 ***
(7,728)
-20,781 ***
(7,305)
-0,0002 **
(0,0001)
-25,629
(22,022)
48
0,900
OK
OK
OK
OK
48
0,908
OK
OK
OK
OK
48
0,911
OK
OK
OK
OK
Police
Hype
N
R square
Doornik- Hansen test
No Autocorrelation
No colinearity
White test
Alc_acc
All models included constant
Level of statistical significance: *p < .10 **p < .05 ***p < .01
Source: Own calculations
VI. CONCLUIONS
This paper provides econometric attempt to assess ’24 hours courts’ deterrence effect.
Applied methodology relies on the number of accidents caused by intoxicated drivers, as a
proxy for total number of citizens who operate of a motor vehicle while intoxicated (after
control for other factors such as roads quality and weather conditions).
Ran regressions provides strong and robust evidences that ’24 hours courts’ introduction has
impacted the frequency of criminal behaviors in statistically significant way (it seems to
reduce the number of accidents caused by intoxicated drivers bout almost 21 per month)24.
Additionally, estimates can not provide evidences that the ‘media hype’ around ’24 hours
courts’ influenced on the drivers criminal behaviors.
However, even baseline specification proving, that existing estimates of this effect was
seriously overstated. After controlling for Police road checks, measured effect decrease, but it
remains its statistical significance.
24
However it would be valuable to include in the model some data about performance of ’24 hours courts’,
especially the ratio of simple cases resolved in this institution. 10 VII.
REFERENCES
1. Becker G., (1968), Crime and Punishment: An Economic Approach, Journal of
Political Economy, 76, p. 169 – 217, available at:
http://www.law-economics.cn/book/81.pdf
2. Czabański J., (2009), Odstraszający efekt sądów 24 godzinnych. Available at
http://jacek.czabanski.net.
Shorter
version
of
this
paper
was
printed
in
‘Rzeczpospolita’ Daily 21. May 2009
3. Fabryka Komunikacji Społecznej, (2010), Kampania „Piłeś? – Nie Jedź!” 2009
Wyniki badania ewaluacyjnego, presentation available at:
http://www.pijodpowiedzialnie.pl/pliki/RAPORT_kampania%20PNJ%202009.pdf
4. Kenkel D., (1993), Driving and Deterrence: the Effectiveness and Social Costs of
Alternative Policies, Journal of Law and Economics, Vol. 36, No. 2, p. 877, available
at: http://www.jstor.org/stable/725811
5. Komenda Główna Policji, (2006) Wypadki drogowe w Polsce w 2006 roku,
Warszawa, available at:
http://www.policja.pl/portal/pol/8/6714/Wypadki_drogowe_w_Polsce_w_2006_r.html
6. Komenda Główna Policji, (2007) Wypadki drogowe w Polsce w 2007 roku,
Warszawa, available at:
http://www.policja.pl/portal/pol/8/21830/Wypadki_drogowe_w_Polsce_w_2007_r.ht
ml
7. Komenda Główna Policji, (2008) Wypadki drogowe w Polsce w 2008 roku,
Warszawa, available at:
http://www.policja.pl/portal/pol/8/43149/Wypadki_drogowe_w_Polsce_w_2008_r.ht
ml
8. Komenda Główna Policji, (2009) Wypadki drogowe w Polsce w 2009 roku,
Warszawa, available at:
http://dlakierowcow.policja.pl/portal/dk/807/47493/Wypadki_drogowe__raporty_rocz
ne.html
11 9. Nichols J., Ross L., (1989), The Effectiveness of Legal Sanctions in Dealing with
Drinking Drivers, in: Surgeon General’s workshop on Drunk Driving: Background
Papers 93 (U.S. Department of Health and Human Services, 1989), available at:
http://profiles.nlm.nih.gov/NN/B/C/Y/B/_/nnbcyb.pdf
10. TNS OBOP, (2006), Raport z badania ilościowego przeprowadzonego na zlecenie
Krajowej Rady Bezpieczeństwa Ruchu Drogowego, presentation available at:
http://www.krbrd.gov.pl/download/pdf/prezenacja_piles_nie_jedz_konf_pras_060706.
pdf
11. Varian Hal R., Choi Hyunyoung, (2009), Predicting the Present with Google Trends,
Google Research Blog http://googleresearch.blogspot.com/2009/04/predictingpresent-with-google-trends.html. Available at SSRN:
http://ssrn.com/abstract=1659302
12. ---------------, Raport końcowy, Badanie opinii publicznej na temat wizerunku wymiaru
sprawiedliwości, oceny reformy wymiaru sprawiedliwości, aktualnego stanu
świadomości społecznej w zakresie alternatywnych sposobów rozwiązywani sporów
oraz praw osób pokrzywdzonych przestępstwem, Warsaw, February 2009, available
at: http://www.edukacjaprawnicza.pl/images/files/090320_raportpokl.pdf
1. Ustawa z dnia 6 czerwca 1997 r. - Kodeks postępowania karnego (Dz. U. 1997 nr 89
poz. 555)
2. Rozporządzenie Ministra Sprawiedliwości z dnia 22 lutego 2007 r. w sprawie
zapewnienia oskarżonemu możliwości korzystania z pomocy obrońcy, jego wyboru w
postępowaniu przyspieszonym oraz organizacji dyżurów adwokackich (Dz. U. 2007 nr
38 poz. 248)
3. Rozporządzenie Ministra Sprawiedliwości z dnia 23 lutego 2007 r. zmieniające
rozporządzenie - Regulamin wewnętrznego urzędowania powszechnych jednostek
organizacyjnych prokuratury (Dz. U. 2007 nr 38 poz. 250)
4. Rozporządzenie Ministra Sprawiedliwości z dnia 23 lutego 2007 r. Regulamin
urzędowania sądów powszechnych (Dz. U. 2007 nr 38 poz. 249)
12 13