Croatian Review of Economic, Business and Social Statistics

Trends and drivers of housing affordability in the EU: Insights from panel data analysis

Josip Arnerić — 2024-12-02

Housing affordability is a crucial issue that affects both individual and societal well-being. Affordable housing ensures that households can meet their basic living needs without experiencing undue financial stress. It influences labor mobility, consumer spending, economic growth, and resilience. Typically, housing affordability is measured by the proportion of household income spent on housing costs, including rent or mortgage payments, utilities, and maintenance. However, no single metric is universally accepted (cost-to-income ratio, residual income approach or subjective measures assessing households' perceptions of their housing affordability). These diverse indicators reflect the complexity of housing affordability and highlight the need for comprehensive analysis using multiple metrics, which is the purpose of this paper. Panel analysis of the socio-economic and demographic demand and supply drivers of housing affordability is essential for developing effective policies that ensure all citizens have access to adequate and affordable housing, as many European Union countries have faced a housing affordability crisis characterized by rising housing prices, housing costs and insufficient housing units supply.

Pregled potencijalnih ekonomskih učinaka razvoja 5G infrastrukture - slučaj Hrvatske

Tajana Barbić — 2024-11-28

U radu su navedene potencijalne ekonomske prednosti implementacije 5G infrastrukture u Republici Hrvatskoj kroz kritički pregled relevantne literature. Pojava 5G infrastrukture obećava transformativne promjene u različitim sektorima, preoblikovanje industrija i poticanje gospodarskog rasta. Brojne su studije i istraživanja koja predviđaju da će 5G imati značajan ekonomski utjecaj, otvarajući nova tržišta i mogućnosti za rast u mnogim industrijama kroz stvaranje novih poslova, poboljšanje produktivnosti i poticanje globalnog ekonomskog rasta. Ovaj rad predstavlja regulatorni okvir za 5G infrastrukturu u Hrvatskoj i EU, uz identificiranje potencijalnih koristi koje bi različite industrije i slučajevi korištenja mogli imati od implementacije 5G mreže i povezanih digitalnih mobilnih tehnologija. Cilj ovog rada je dati detaljan i kritički pregled takvih istraživanja te se posebno kroz analizu dostupne literature fokusirati na ključne sektore u Republici Hrvatskoj kod kojih bi potencijalne koristi od 5G mreže bile najveće. Ti sektori uključuju proizvodnju, IKT, usluge javnog sektora, trgovinu na veliko i malo, financije i osiguranje, prijevoz i skladištenje, kao i turizam. Doprinos rada sastoji se u identifikaciji i kompilaciji potencijalnih izazova implementacije 5G mreže iz postojeće literature.

The impact of urbanisation on poverty reduction in South Africa: A non-linear ARDL approach

Mercy T. Musakwa — 2024-11-28

The asymmetric impact of urbanisation on poverty reduction was examined for South Africa employing data from 1990 to 2022. The study was motivated by the need to establish the effects of positive and negative shocks on poverty reduction. The study used the non-linear autoregressive distributed lag model (NARDL). The study is timely as it is conducted at a time when most countries, including South Africa, are trying to recover from the COVID-19 global pandemic, which led to a surge in poverty levels. The study found that positive and negative shocks of urbanisation are only instrumental in poverty reduction in the short run. In the long run, positive and negative shocks of urbanisation have no significant effect whatsoever on poverty reduction. The study also found that the effects of positive shocks were more dominant than negative shocks on poverty reduction. The findings of the study point to the importance of urbanisation in poverty reduction in the short run. Policy implications are discussed.

Maximum lq-likelihood estimator of the heavy-tailed distribution parameter

Mohammed Ridha Kouider — 2024-11-28

Studying the extreme value theory (EVT) involves multiple main objectives, among them the estimation of the tail index parameter. Some estimation methods are used to estimate the tail index parameter like maximum likelihood estimation (MLE). Additionally, the Hill estimator is one type of maximum likelihood estimator, which is a more robust with a large sample than a small sample. This research proposes the construction of an alternative estimator for the parameter of the heavy-tailed distribution using the maximum lq-likelihood estimation (MLqE) approach in order to adapt the ML and Hill estimator with the small sample. Furthermore, the maximum lq-likelihood estimator asymptotic normality is established. Moreover, several simulation studies in order to compare the MLq estimator with the ML estimators are provided. In the excesses over high suitable threshold values the number of the largest observation k will lead to an efficient estimate of the Hill estimator. For this, selection of k in the Hill estimator was investigated using the method of the quantile type 8 which is effective with the hydrology data. The performance of the Hill estimator and the lq-Hill estimator is subsequently compared by employing real relies with the distribution of hydrology data.