# Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal
## 3 Data and Methods
### Study Area and Data
#### 3.1.2 Demographic and Socioeconomic Data
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variable** & **Description** & **Mean** & \begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} & **Minimum** & **Maximum** & \begin{tabular}{c} **Correlation** \\ **(\(p\)-Value)** \\ \end{tabular} \\ \hline Young resident population & Rate of individuals between 15 and 24 years old (source: PORDATA) & 10.274 & 1.362 & 6.488 & 13.973 & \begin{tabular}{c} \(-0.0934\) \\ (0.1204) \\ \end{tabular} \\ \hline Retention and dropout rates in basic education & Rate of students’ failure and early school & & & & & \\  & leavers from basic education in the education & 3.137 & 2.098 & 0 & 12.1 & \begin{tabular}{c} \(0.1507\) \\ (0.0119) \\ \end{tabular} \\ \hline \multirow{4}{*}{Gross enrollment rate} & Students enrolled in a given level of education, regardless of age, expressed as a percentage of the official school-age & 108.875 & 14.916 & 72.1 & 181.9 & \begin{tabular}{c} \(0.1934\) \\ (0.0012) \\ \end{tabular} \\  & population corresponding to the same level & & & & & \\  & of education (source: DGEEC) & & & & & \\ \hline Conventional dwellings & Ratio between the number of conventional dwellings & & & & & \\  & & surface of that territory in Km\({}^{2}\) & 165.585 & 443.799 & 5.6 & 3708.8 & \begin{tabular}{c} \(0.4543\) \\ (\(<\)0.0001) \\ \end{tabular} \\ \hline Guaranteed Minimum Income and Social Integration Benefit & Beneficiaries of the Guaranteed Minimum total resident population aged 15 and over (\%) (source: PORDATA) & 2.988 & 1.988 & 0.4 & 15.5 & \begin{tabular}{c} \(0.0291\) \\ (0.6290) \\ \end{tabular} \\ \hline \multirow{4}{*}{Purchasing power per capita} & This composite indicator aims to indicate purchasing power on a daily basis in per capita terms in the different municipalities, using the figure for Portugal as a reference (index number in \% with a value of 100 on the country average) (source: PORDATA) & 80.519 & 18.677 & 55.3 & 219.6 & \begin{tabular}{c} \(0.6174\) \\ (\(<\)0.0001) \\ \end{tabular} \\ \hline \multirow{4}{*}{Monthly remuneration of employees} & Average gross amount, before deduction of taxes and social security contributions, in cash or in-kind, paid regularly in the reference period and corresponding to the normal working period, in euros & & & & \\  & & & & & \\  & & & & & \\  & & & & & \\ \hline \multirow{4}{*}{Unemployment rate} & Unemployment registered at the public employment office in total of resident population aged 15 to 64 (\%) & 6.482 & 2.328 & 3.0 & 15.8 & \
\begin{tabular}{c} \(-0.0500\) \\ (0.4061) \\ \end{tabular} \\  & & & & & & \\  & & & & & \\ \hline \multirow{4}{*}{Foreign population} & Foreign population with legal resident status as a percentage of the resident population (source: PORDATA) & 2.970 & 3.932 & 0.3 & 26.6 &
\begin{tabular}{c} \(0.6379\) \\ (\(<\)0.0001) \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of variables, descriptive statistics, and [PERSON]’s correlation test with property crime rates. municipalities. Hence, those variables were only discarded from a few regression models that were investigated. The density of conventional dwellings is higher in the metropolitan areas of Lisbon and Porto. The southern municipalities and Lisbon have a higher proportion of foreign population. Unemployment figures and the numbers of beneficiaries of income from government assistance were found to be identically distributed, which was expected since unemployed individuals usually benefit from Guaranteed Minimum Income and Social Integration Benefits. Lower amounts of monthly remuneration were observed in the inland municipalities, while northern and coastal regions showed higher rates of young resident population. Purchasing power and variables characterizing population education exhibited a dispersed pattern across municipalities. The Variance Inflation Factor (VIF) values of the nine variables were smaller than 3, indicating no evidence of multicollinearity between them. Therefore, all of them were considered in the regression models.