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Education and Crime: A Panel Data Analysis of the Czech Republic
Název práce v češtině:
Název v anglickém jazyce: Education and Crime:
A Panel Data Analysis of the Czech Republic
Klíčová slova: education, crime, employment, GDP, gender ratio, age, the Czech Republic, panel data, fixed-effect, GMM
Klíčová slova anglicky: education, crime, employment, GDP, gender ratio, age, the Czech Republic, panel data, fixed-effect, GMM
Akademický rok vypsání: 2013/2014
Typ práce: diplomová práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: Mgr. Pavla Růžičková
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 18.06.2014
Datum zadání: 18.06.2014
Datum a čas obhajoby: 22.06.2015 00:00
Místo konání obhajoby: IES
Datum odevzdání elektronické podoby:11.05.2015
Datum proběhlé obhajoby: 22.06.2015
Oponenti: prof. RNDr. Jiří Hlaváček, CSc.
 
 
 
Kontrola URKUND:
Předběžná náplň práce
Motivation:

There was an important change in Czech education system in the end of the 20th century. The private elementary education have been in existence since 1990, and the tertiary/university education has also been allowed to be provided privately since 1999. This deregulation of educational institutes can be considered as a big progress in Czech education development.
According to the statistics from Czech Statistical Office (Český statistický úřad, ČSÚ) and the Ministry of Education, Youth and Sports (Ministerstvo školství, mládeže a tělovýchovy, MŠMT), the number of higher education institutes (vysokoškolské studium) has rapidly increased, from merely 13 in 1999/2000 to 32 in 2013/2014. Apart from it, there is one fifth of population with higher education degree in 2013, two times higher than the rate in 1993. From the statistics, it is not difficult to see how fast the educational development is in the Czech Republic.
As the ratio of high-education attainment has been rising in recent years, people started to pay more attention to its quality and discuss the influence on the society. In this thesis, I am going to focus mainly on the effect of educational levels on crime rates in the Czech Republic, with the consideration of economic and demographic information. The data of thirteen Czech regions from 2005 to 2012 will be collected for the analysis. I plan to use fixed effect model/random effect model, and then generalized method of moments (GMM) to verify the assumption that, within an area, the higher educational attainment of its residents, better economic situation and lower male ratio to population will lead to lower crime rates.

Hypotheses:

#1: Higher educational attainment leads to lower crime rates.
#2: Better economy (higher income, higher employment rate) leads to lower crime rates.
#3: Males tend to commit more crimes than females.

Methodology:

In this thesis I am going to use fixed effect model/random effect model and GMM to check the relationship between educational attainment and crime rates in different Czech regions. In addition, I add other economic and demographic variables such as gender, age, employment rate and income into the regression to see their influence on crimes.
The data is mainly collected from the Czech Statistical Office, among thirteen regions of the Czech Republic in the period of 2005-2012. The regional data contains yearly information of educational attainment ratio, crime rates, sex and age ratio, average personal income and employment rate. With the data, I expect to observe the relationship between crime rates and educational attainment, as well as macroeconomic and demographic factors.
Since the data I use for the analysis is panel data, simply using OLS may cause ignorance of individual and time difference, and then lead to coefficient inconsistency. In order to avoid this problem, it is necessary to apply either fixed effect model or random effect model (Chen, 2008). And based on the result of Hausman test, the model can be chosen to fit our panel data best.
However, there is possible criminal inertia and the joint endogeneity problem among variables. Both can make coefficients inconsistent, and thereby the result may be unreliable (Lio & Lu, 2011). Therefore, it is important to further consider this dynamic phenomenon. It can be achieved by adding the lag-dependent variable, in other words, the GMM estimator, into the regressions, which is considered as an ideal method for the panel data analysis (Fajnzylber, Lederman & Loayza, 2002) (Buonanno & Leonida, 2009).

Core Bibliography:

1.Buonanno, P., Leonida, L. (2009). Non-market effects of education on crime: Evidence from Italian regions. Economics of Education Review, vol. 28(issue 1), pp. 11-17.
2.Chen, Y. (2008). Higher Education and Crime Rate - A Panel Data Analysis in Taiwan (Master Thesis). National Taiwan University.
3.Fajnzylber, P., Lederman, D., Loayza, N. (2002). Inequality and Violent Crime*: Bringing Inequality Back In. The Journal of Law and Economics, vol. 45(issue 1), pp. 238-253.
4.Lio, M., Lu, C. (2011). Income Inequality and Crime: A Study Based on Regional Dynamic Panel Data from Taiwan.Taiwan Economic Review, vol.39 no.2, pp. 243-276.
5.Lochner, L., Moretti, E. (2001). The effect of education on crime: Evidence from prison inmates, arrests, and self-reports (No. w8605). National Bureau of Economic Research.
6.Lochner, L. (2011). Non-production benefits of education: Crime, health, and good citizenship (No. w16722). National Bureau of Economic Research.
7.Statistical Yearbooks (2005-2013), Retrieved on September 28, 2014 from the Czech Statistical Office Database, access: http://www.czso.cz/eng/edicniplan.nsf/aktual/ep-1
8.The education system in the Czech Republic. (2012). (2nd ed., 35 s., Editor Leona Gergelová Šteigrová). Prague: Ministry of Education, Youth and Sports.
Předběžná náplň práce v anglickém jazyce
Motivation:

There was an important change in Czech education system in the end of the 20th century. The private elementary education have been in existence since 1990, and the tertiary/university education has also been allowed to be provided privately since 1999. This deregulation of educational institutes can be considered as a big progress in Czech education development.
According to the statistics from Czech Statistical Office (Český statistický úřad, ČSÚ) and the Ministry of Education, Youth and Sports (Ministerstvo školství, mládeže a tělovýchovy, MŠMT), the number of higher education institutes (vysokoškolské studium) has rapidly increased, from merely 13 in 1999/2000 to 32 in 2013/2014. Apart from it, there is one fifth of population with higher education degree in 2013, two times higher than the rate in 1993. From the statistics, it is not difficult to see how fast the educational development is in the Czech Republic.
As the ratio of high-education attainment has been rising in recent years, people started to pay more attention to its quality and discuss the influence on the society. In this thesis, I am going to focus mainly on the effect of educational levels on crime rates in the Czech Republic, with the consideration of economic and demographic information. The data of thirteen Czech regions from 2005 to 2012 will be collected for the analysis. I plan to use fixed effect model/random effect model, and then generalized method of moments (GMM) to verify the assumption that, within an area, the higher educational attainment of its residents, better economic situation and lower male ratio to population will lead to lower crime rates.

Hypotheses:

#1: Higher educational attainment leads to lower crime rates.
#2: Better economy (higher income, higher employment rate) leads to lower crime rates.
#3: Males tend to commit more crimes than females.

Methodology:

In this thesis I am going to use fixed effect model/random effect model and GMM to check the relationship between educational attainment and crime rates in different Czech regions. In addition, I add other economic and demographic variables such as gender, age, employment rate and income into the regression to see their influence on crimes.
The data is mainly collected from the Czech Statistical Office, among thirteen regions of the Czech Republic in the period of 2005-2012. The regional data contains yearly information of educational attainment ratio, crime rates, sex and age ratio, average personal income and employment rate. With the data, I expect to observe the relationship between crime rates and educational attainment, as well as macroeconomic and demographic factors.
Since the data I use for the analysis is panel data, simply using OLS may cause ignorance of individual and time difference, and then lead to coefficient inconsistency. In order to avoid this problem, it is necessary to apply either fixed effect model or random effect model (Chen, 2008). And based on the result of Hausman test, the model can be chosen to fit our panel data best.
However, there is possible criminal inertia and the joint endogeneity problem among variables. Both can make coefficients inconsistent, and thereby the result may be unreliable (Lio & Lu, 2011). Therefore, it is important to further consider this dynamic phenomenon. It can be achieved by adding the lag-dependent variable, in other words, the GMM estimator, into the regressions, which is considered as an ideal method for the panel data analysis (Fajnzylber, Lederman & Loayza, 2002) (Buonanno & Leonida, 2009).

Core Bibliography:

1.Buonanno, P., Leonida, L. (2009). Non-market effects of education on crime: Evidence from Italian regions. Economics of Education Review, vol. 28(issue 1), pp. 11-17.
2.Chen, Y. (2008). Higher Education and Crime Rate - A Panel Data Analysis in Taiwan (Master Thesis). National Taiwan University.
3.Fajnzylber, P., Lederman, D., Loayza, N. (2002). Inequality and Violent Crime*: Bringing Inequality Back In. The Journal of Law and Economics, vol. 45(issue 1), pp. 238-253.
4.Lio, M., Lu, C. (2011). Income Inequality and Crime: A Study Based on Regional Dynamic Panel Data from Taiwan.Taiwan Economic Review, vol.39 no.2, pp. 243-276.
5.Lochner, L., Moretti, E. (2001). The effect of education on crime: Evidence from prison inmates, arrests, and self-reports (No. w8605). National Bureau of Economic Research.
6.Lochner, L. (2011). Non-production benefits of education: Crime, health, and good citizenship (No. w16722). National Bureau of Economic Research.
7.Statistical Yearbooks (2005-2013), Retrieved on September 28, 2014 from the Czech Statistical Office Database, access: http://www.czso.cz/eng/edicniplan.nsf/aktual/ep-1
8.The education system in the Czech Republic. (2012). (2nd ed., 35 s., Editor Leona Gergelová Šteigrová). Prague: Ministry of Education, Youth and Sports.
 
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