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EN
Suicide rates in Europe have in the recent years reached a disturbingly high level, sparking frequent discussions on the topic of mental health and suicide prevention, which significantly affect not only individuals but also their environment. The aim of this paper was to analyse the impact of the socio-economic situation on suicide rates using panel data analysis. The study presents an overview of the related literature and the definitions of essential terms concerning suicide, as well as the socio-economic factors determining suicide rates. The parameters of a fixed effects model were estimated, interpreted and compared with the results of earlier research. The analysis of the selected dataset showed that GDP per capita and the Gini coefficient have a negative and statistically insignificant impact on suicide rates. On the other hand, the conducted research showed that high divorce and unemployment rates, risk of poverty, social exclusion and excessive alcohol consumption proved to be statistically significant, thus increasing suicide rates.
PL
Decyzje inwestorów na rynku mieszkaniowym są sumą ich subiektywnych oczekiwań. Wiążą się one z możliwościami finansowymi nabywców, modą na daną lokalizację, zakresem i aktywnością działań deweloperskich na danym terenie oraz indywidualnymi potrzebami uwarunkowanymi sytuacją rodzinną czy przyzwyczajeniami. Nie bez znaczenia są również: poczucie bezpieczeństwa, prestiżu mieszkania w danej dzielnicy oraz walory sąsiedztwa pozytywnie oddziałujące na komfort mieszkania w takim otoczeniu. Lokalizacja nieruchomości w przestrzeni jest jedną z najistotniejszych determinant jej wartości. Wzajemne oddziaływanie nieruchomości jest szczególnie widoczne w preferencjach nabywców na rynku, a w efekcie przekłada się na natężenie transakcji w atrakcyjnych lokalizacjach, a także na ich cenę transakcyjną. Z drugiej strony przestrzeń, a zatem i sąsiedztwo zabudowy mieszkaniowej ulega w czasie powolnym, jednak często istotnym przekształceniom. Dotychczasowe priorytety nabywców również ewoluują w czasie. Stąd celem artykułu jest zbadanie stabilności w czasie preferencji nabywców mieszkań w odniesieniu do wyboru lokalizacji w obrębie miasta. Do realizacji postawionego celu zaproponowano modele ze zmiennymi parametrami (fixed effects models). W artykule wykorzystano dane dotyczące sprzedaży mieszkań w Szczecinie zawarte w aktach notarialnych zgromadzonych w Rejestrze Cen i Wartości Urzędu Miasta w Szczecinie.
EN
The housing market investors’ decisions are caused by their subjective expectations. These decisions are to do with financial resources, activity of local developers and buyers’ individual needs connected to the size of their household or their specific habits, as well as a sense of security and prestige of the neighborhood. The localization of a property is one of the most significant determinants of its price because of its spatial constancy. The attributes of a given residential area influence the value of properties and this phenomenon can be observed through intensity of transactions and transaction prices. On the other hand, the neighborhood’s influence changes over time. These changes are sometimes slow but could be very substantial. That is why buyers’ preferences can also change over time. The aim of this research is the analysis of the temporal stability of buyers’ localization preferences on the housing market in Szczecin. The fixed effects model, which allows for the comparison of changes in apartments’ prices in residential areas, has been applied. The data came from notarial deeds, from registers of real estate prices and values concerning transactions on the housing market in Szczecin.
EN
The hypothesis about positive influence of lower tax rate was tested on the Russian small businesses of construction and manufacturing sectors. The period from 2006 to 2014 includes the three-year gap, during which the net income tax rate was the same for all Russian regions, and the six-year interval of regionally differentiated tax rates. Quantitative estimates of the consequences of tax change without time lag, with time lags 1 and 2 year were made on the basis of double logarithmic regressions with fixed effects. Positive effect of lower tax rate was documented. The number of enterprises was the indicator, which was influenced most. A regional tax rate decrease by 1 per cent results in an increase of the number of small enterprises by 0.1-0.2%. This effect becomes evident in the first year of regional tax rate change and remains on the same level during the following two years. 1% decrease in tax rate led to 0.1% increase in the turnover of the company. Tax stimulus led to an increase of employment in manufacturing industry (the coefficient of elasticity is 0.1), while the impact on employment in construction sector was not identified. There is a potential for expanding tax revenues to the Russian budget system by increasing the taxation base with the help of the positive effect from tax rate reduction.
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