Croatian Review of Economic, Business and Social Statistics
e-ISSN 2459-5616 ISSN 1849-8531 https://doi.org/10.62366/crebss Publisher: Croatian Statistical Association Trg J. F. Kennedyja 6 10000 Zagreb, Croatia e-mail: journal@hsd-stat.hr Published semiannualy since 2015
Entrepreneurship and aggregate productivity
This paper examines the contribution of entrepreneurial activity to aggregate productivity in eleven post-socialist new European Union member states over the period 2005-2019. Building on Baumol's distinction between productive and unproductive entrepreneurship, it addresses two questions: whether measures of entrepreneurial activity are correlated with aggregate productivity, and whether that correlation is positive or negative, thereby allowing productive and unproductive entrepreneurship to be distinguished empirically. Productivity is measured by GDP per person employed and GDP per hour worked, entrepreneurial activity by the Global Entrepreneurship Monitor's National Entrepreneurship Context Index, and the institutional environment by the burden of government regulation. Estimating a linear dynamic panel with a one-step generalized method of moments estimator, the analysis finds that the entrepreneurial environment is positively and significantly associated with both productivity measures, while a heavier regulatory burden is negatively associated with them. These results identify the prevailing entrepreneurship in the sample as productive in Baumol's sense. The contribution is twofold: conceptually, the paper offers a theory-to-measurement bridge for the Baumolian framework, and empirically, it documents the entrepreneurship-productivity nexus for a panel of new EU member states.
Copyright (c) 2026 retained by the author(s) https://creativecommons.org/licenses/by-nc-nd/4.0
Hybrid ARIMA-machine learning models for predicting inflation and economic growth in Nigeria
Accurate forecasting of inflation and economic growth remains a critical policy challenge for Nigeria, where volatile macroeconomic conditions, structural breaks, and persistent shocks have rendered traditional univariate methods increasingly unreliable. This paper develops and evaluates a family of hybrid ARIMA-machine learning models for predicting Nigeria's consumer price index (CPI) and gross domestic product (GDP) growth rates using monthly data from January 2010 to December 2024. The hybrid framework decomposes each series into a linear component captured by ARIMA and a nonlinear residual component captured by one of three machine learning algorithms, i.e. artificial neural network (ANN), support vector regression (SVR), and random forest (RF). Rolling-window out-of-sample experiments demonstrate that all hybrid models substantially outperform their standalone counterparts. The ARIMA-ANN hybrid achieves the lowest root mean square error (RMSE) of 0.324 for inflation forecasting, compared with 0.517 for standalone ARIMA and 0.468 for standalone ANN. For GDP growth, the ARIMA-RF hybrid achieves RMSE 0.187, a 34% improvement over ARIMA alone. Diebold-Mariano tests confirm that all forecast improvements are statistically significant at the 1% level. The results support hybrid modelling as a viable path toward more reliable macroeconomic forecasting in emerging economies characterized by structural instability and regime switching.
Pokazatelj očekivane zaposlenosti u predviđanju promjena na hrvatskom tržištu rada
Cilj rada je teorijski i metodološki analizirati prognostička svojstva pokazatelja očekivane zaposlenosti EEI (engl. Employment Expectations Indicator) u kontekstu predviđanja promjena na hrvatskom tržištu rada, pri čemu se testira hipoteza o EEI-ju kao vodećem indikatoru kratkoročnih promjena. Empirijsko istraživanje provedeno je na sekundarnim, sezonski prilagođenim mjesečnim vremenskim nizovima Europske komisije i Državnog zavoda za statistiku od siječnja 2016. do prosinca 2025. godine. Primjenom testa Grangerove uzročnosti unutar autoregresijskog modela s distribuiranim pomacima (ARDL), analiziran je vremenski pomak djelovanja EEI-ja, s primarnim fokusom na prognoziranje smjera, a ne intenziteta promjene broja zaposlenih u kratkom roku od dva mjeseca. Rezultati modeliranja indiciraju da uključivanje varijable EEI, uz specifikaciju do uključivo dvaju mjesečnih pomaka, statistički značajno doprinosi prognostičkoj kvaliteti i poboljšanju predikcije. Time rad pruža preliminarne dokaze o prediktivnoj valjanosti ovog pokazatelja te ostvaruje znanstveni i aplikativni doprinos kroz oblikovanje pouzdanog analitičkog instrumentarija za potrebe makroekonomskog planiranja i kreiranja ekonomskih politika.
Comparative ocean temperature forecasting using SARIMA, ETS and LSTM
Accurate ocean temperature forecasting is essential for understanding long-term environmental variability and supporting ecological decision-making. This study evaluates the performance of SARIMA (Seasonal Autoregressive Integrated Moving Average), ETS (Error Trend Seasonality), and LSTM (Long Short-Term Memory) models for predicting ocean temperature using historical time series data from the CalCOFI programme. The dataset was preprocessed using seasonal decomposition and stationarity analysis, and forecasting accuracy was assessed using MAPE (Mean Absolute Percentage Error), RMSE (Root Mean Squared Error), and MSE (Mean Squared Error). The results indicate that LSTM produced the most accurate and stable forecasts overall, achieving lower RMSE and MAPE values at most stations and depths. It effectively captured nonlinear behavior, seasonal variability, and extreme temperature fluctuations. SARIMA demonstrated a strong capability to model trend and seasonality, while ETS generated smoother forecasts but with comparatively higher error values. Residual diagnostics further confirmed LSTM’s superior ability to learn complex temporal dependencies present in ocean temperature data. This study contributes to a comparative evaluation of classical statistical and deep learning models for ecological time series forecasting and provides evidence supporting the application of LSTM for improved oceanographic prediction and environmental monitoring.
Lokalna prostorna analiza indeksa razvijenosti jedinica lokalne samouprave u Hrvatskoj
Regionalne nejednakosti u Hrvatskoj rezultat su složenog međudjelovanja prostorne udaljenosti te povijesnih, društvenih i gospodarskih čimbenika. Cilj ovoga rada jest prostorno-statistički ispitati indeks razvijenosti svih 556 jedinica lokalne samouprave u Republici Hrvatskoj, uzimajući u obzir ne samo njihove pojedinačne vrijednosti, nego i geografski položaj te obilježja susjednog okruženja. U tu svrhu primijenjena je eksplorativna prostorna analiza podataka (ESDA), s posebnim naglaskom na globalni Moranov indeks i lokalne indikatore prostorne povezanosti. Rezultati potvrđuju postojanje globalne umjerene do jake pozitivne prostorne autokorelacije indeksa razvijenosti, što upućuje na značajno grupiranje prostornih jedinica sličnih razvojnih obilježja. Lokalnom prostornom analizom identificirano je pet klastera, koji se u radu sistematiziraju u četiri skupine: razvijene jedinice (HH klaster), nerazvijene jedinice (LL klaster), prostorne izdvojenice (HL i LH klaster) te prijelaznu skupinu statistički neznačajnih jedinica. Takva raspodjela klastera otkriva izraženu zapadno-istočnu razvojnu polarizaciju u Jadranskoj i Kontinentalnoj Hrvatskoj. Procjena efektivne veličine uzorka, koja je znatno manja od nominalnog broja lokalnih jedinica, dodatno naglašava važnost uvažavanja prostorne ovisnosti u empirijskim analizama. Rad doprinosi razumijevanju prostorne dimenzije regionalnih nejednakosti te pruža argumente za oblikovanje razvojnih politika na funkcionalno i prostorno širem teritorijalnom obuhvatu.
Razlike u percepcijama rizika od katastrofa i informacijskim izvorima između hrvatskih studenata i referentnih skupina
U uvjetima sve izraženijih klimatskih i sigurnosnih prijetnji, otpornost postaje društveni prioritet. Stoga, ovaj rad analizira svijest o rizicima od katastrofa i preferencije izvora informacija među hrvatskim studentima poslovne ekonomije te ih uspoređuje s referentnim skupinama studenata i općom populacijom u EU-27 i Republici Hrvatskoj. Rezultati istraživanja provedenog na kriterijskom uzorku studenata Ekonomskog fakulteta Sveučilišta u Zagrebu, uz primjenu Eurobarometar metodologije, potvrđuju da hrvatski studenti imaju statistički značajno višu svijest o rizicima od katastrofa (81,2%) u odnosu na studente EU-27 država članica (66,9%) te opću populaciju EU-27 i Republike Hrvatske, što korelira s visokim udjelom osobnog iskustva katastrofe (81%). Analiza informiranja otkriva postojanje hibridnog modela: uz dominaciju digitalnih kanala, studenti značajno koriste nacionalne medije, što ukazuje na informacijsku zrelost i potragu za vjerodostojnim sadržajem. Doprinos rada očituje se u identifikaciji visoke percepcije rizika od katastrofa kao pozitivnog kapitala koji potiče buduće donositelje odluka na rano prepoznavanje signala opasnosti. Rezultati ukazuju na nužnost transformacije postojeće svijesti u konkretnu operativnu spremnost, sugerirajući strateško preusmjeravanje resursa s informativnih kampanja na provedbu praktičnih treninga i simulacija.
Copyright (c) 2025 retained by the author(s) https://creativecommons.org/licenses/by-nc-nd/4.0
Korelacijska analiza ESG ocjene i pokazatelja profitabilnosti i investiranja u Hrvatskoj
U radu se istražuje povezanost ESG ocjene, kao mjere učinkovitosti održivog, okolišnog i društveno odgovornog upravljanja, s pokazateljem profitabilnosti koji odražava uspješnost poslovanja temeljenu na računovodstvenim kategorijama te s pokazateljem investiranja koji odražava tržišnu vrijednost. Cilj je utvrditi je li uspješno upravljanje ESG pitanjima povezano s većom profitabilnošću poslovanja i većom atraktivnošću dionica poduzeća, u skladu s pretpostavkama Direktive o korporativnom izvještavanju o održivosti (CSRD). Na uzorku od devet hrvatskih nefinancijskih kotirajućih društava iz različitih djelatnosti za promatrano razdoblje od 2020. do 2023. godine provedene su dvije korelacijske analize, a korištene varijable uključuju Bloomberg ESG ocjenu, neto rentabilnost imovine kao odabranog pokazatelja profitabilnosti te ukupnu rentabilnost dionice kao odabranog pokazatelja investiranja. Rezultati analize ukazali su na izostanak statistički značajne povezanosti između ESG ocjene i neto rentabilnosti imovine, odnosno ukupne rentabilnosti dionice u Republici Hrvatskoj. Navedeno implicira da prakse održivosti u Hrvatskoj još nisu dovoljno razvijene da bi se njihove prednosti odrazile na druge poslovne segmente u kratkom roku.
Predviđa li CROBEXturist dionički indeks promjene na hrvatskom turističkom tržištu?
Analizom povezanosti CROBEXturist indeksa i broja dolazaka turista ispituje se potencijal financijskih tržišta za predviđanje turističke sezone u Hrvatskoj. Sukladno tome, glavni istraživački cilj je utvrditi je li CROBEXturist značajan prediktor turističke sezone u Hrvatskoj u narednom razdoblju od najviše godine dana. Empirijsko istraživanje provedeno je analizom odnosa između mjesečnog broja dolazaka turista i mjesečnih srednjih vrijednosti CROBEXturist indeksa u razdoblju od siječnja 2014. do studenog 2024. godine. Grangerovim testom uzročnosti utvrđeno je da promjene u CROBEXturist indeksu statistički značajno predviđaju turističke dolaske s vremenskim pomacima od 5, 10 i 11 mjeseci što ukazuje na srednjoročnu i dugoročnu prediktivnu moć ovog indeksa. Procijenjeni su različiti ARIMAX, SARIMA i SARIMAX modeli od kojih se, uzimajući u obzir najmanju prognostičku pogrešku, najreprezentativnijim pokazao SARIMAX model s pomakom od pet mjeseci kao egzogenom varijablom. Empirijska potvrda prediktivne moći CROBEXturist indeksa ključni je znanstveni doprinos rada i omogućuje razumijevanje povezanosti financijskih tržišta i realnog sektora u Hrvatskoj. Istraživanjem je potvrđeno da investitori vrlo dobro predviđaju turistička kretanja te da je tržište kapitala pouzdan izvor signala za turističke tvrtke o nadolazećim trendovima na turističkom tržištu.
Frailty model and dependence structure for bivariate survival data
Copulas and their uses in statistics, namely biostatistics, are a relatively new field of research. When modeling the dependence structure between a vector random variable's joint distribution and marginal distributions, copulas are crucial. In this article, we discuss recent research on this theory and how it can potentially used to analyze multivariate survival data. Lastly, an example of such a method is shown using an application on bivariate survival data from research that was examined using the SAS software's Proc Copula approach.
Kauzalna analiza u ekonometriji primjenom Hilbertovog prostora reproducirajućih jezgri
Predložen je postupak određivanja nelinearne uzročne povezanosti dviju varijabli njihovim mapiranjem u Hilbertov prostor reproducirajućih jezgri RKHS (engl. Reproducible Kernel Hilbert Space). Analiza bivarijabilnih zavisnosti dio je razvoja kauzalnih modela umjetne inteligencije sa svrhom upravljanja složenim sustavima. Poznavanje kauzalnosti su ključne informacije na kojima se temelji dijagnostika, predviđanje posljedica i donošenje poslovnih odluka. Određivanje kauzalne relacije varijabli vrši se procjenom empirijske gustoće vjerojatnosti KDE (engl. Kernel Density Estimation) u RKHS prostoru. Procjena smjera kauzalne veze provodi se Nadaraya-Watson aproksimacijom i usporedbom Pearsonove korelacija varijabli X i Y i modela u RKHS prostoru, XH(Y) i YH(X). Predloženi postupak testiran je na nizu primjera: model neurona, simulacijom složenih bivarijabilnih modela s heteroskedastičnim poremećajima, na poznatim podacima sa Sveučilišta u Tüebingenu, marketinškim "Datarium" podacima učinka društvenih mreža, i zavisnosti burzovnih indeksa S&P500 i VIX. Također je provedena analiza strukture kauzalne povezanosti rodnog jaza osobnih dohodaka na podacima američke informatičke tvrtke. Neutvrđenost smjera kauzalne veze indicirana je preklapanjem intervala pouzdanosti Pearsonovih korelacija. Za linearne sustave zbog simetričnosti uvjetovanih distribucija u oba smjera, predloženom metodom smjer kauzalne veze nije moguće jednoznačno odrediti.
Kalendarski učinci rebalansiranja na Zagrebačkoj burzi
U radu se istražuju kalendarski učinci rebalansiranja na Zagrebačkoj burzi (ZSE) analizom dnevnih prinosa indeksa CROBEX i CROBIS u razdoblju od rujna 2003. do ožujka 2025. Pomoću regresijske analize i simulirane investicijske strategije ispituje se predviđaju li sustavne razlike u prinosima između dionica i obveznica na početku mjeseca korekcije prinosa na kraju mjeseca. Rezultati ukazuju na negativnu povezanost između razlika prinosa u prvoj i zadnjoj trećini mjeseca, što potvrđuje postojanje kalendarskog efekta rebalansiranja. Predloženom investicijskom strategijom ostvaruju se znatno bolji rizikom prilagođeni prinosi, sa Sharpeovim omjerom dvostruko većim od strategije "kupi i drži" indeks CROBEX. Robusnost rezultata utvrđena je analizom osjetljivosti na vremenski okvir rebalansiranja, pri čemu se najbolji prinosi ostvaruju upravo pet dana prije kraja mjeseca. Suprotno tome, placebo efekt s rebalansiranjem početkom mjeseca pokazuje slabije rezultate, što sugerira da je isti povezan s institucionalnim aktivnostima krajem mjeseca. Dobiveni nalazi pružaju uvid u vremensku osjetljivost strategija rebalansiranja i ukazuju na mogućnosti poboljšanja prinosa izranjajućih tržišta.
Income's moderating effect on the 4P's influence on purchase intention: The Garnier cosmetics case
The paper presents how the marketing mix elements influence the customers' purchase intention in the context of Garnier cosmetic products and looks at the moderating role of customer income. The marketing mix or 4P can be a way to create profitable marketing strategies and motivate customers to purchase a product. A sample of 230 respondents was included in a survey analysis. The data were analyzed with partial least squares structural equation modeling (PLS-SEM). The results showed only the product element of marketing mix had significant effect on purchase intention. Regarding the moderating effect of income, the lower-income respondents showed higher price sensitivity while promotion had influence on higher-income respondents. The study contributes to certain extent to beauty industry marketing strategies on example of a well-known global brand.
The impact of population ageing on economic growth in developing countries: Panel ARDL evidence
The study aims to analyse the economic effects of population ageing in Japan, Spain, Italy, the United States, South Korea, Germany, France, the United Kingdom, and Canada using the panel ARDL (Autoregressive Distributed Lag) model. GDP per capita was adopted as the dependent variable, while the independent variables included the proportion of the population over 65, health expenditure, the dependency rate, and the level of investment as a proportion of GDP. The results showed varying effects of ageing on economic growth. It had a positive impact in some of the countries under study (the USA, South Korea, and Germany) and a negative impact in others (Spain, Italy, and Japan). Health spending was also found to be an economic burden, while fixed investment was shown to be critical in supporting economic growth. The study recommends improving education and training to increase productivity, embracing innovation and technology, enhancing health systems through preventive care, and implementing flexible policies, such as encouraging women's participation in the labour market and promoting migration.
Moral tribalism as a mediator between religiosity and interest sensitivity among financial consumers
The main purpose of this study was to investigate the mediating effect of moral tribalism on the relationship between religiosity and interest sensitivity (defined as the tendency to avoid financial instruments involving interest). A pilot research was conducted with 204 participants, followed by the main research involving 831 participants. Both sets of data were collected in Turkey through convenience sampling and voluntary participation via an online survey. According to the results of structural equation modelling, religiosity is positively associated with moral tribalism, and both religiosity and moral tribalism significantly predict interest sensitivity. Furthermore, moral tribalism plays a mediating role, exerting a positive and indirect effect of religiosity on interest sensitivity. Statistical tests were also conducted to examine differences in variable levels based on respondents' demographic characteristics. The results indicated that levels of religiosity were higher among males, married individuals, and those with lower educational attainment. Likewise, moral tribalism was found to be higher among married individuals and those aged 20-30. Additionally, men and individuals with lower education levels exhibited higher levels of interest sensitivity compared to others.
Dohodovna konvergencija Hrvatske unutar Europske unije: empirijska analiza frakcijske integracije
Rad analizira dohodovnu konvergenciju Hrvatske u razdoblju od 2000. do 2024. godine prema četiri skupine zemalja: EU15, NMS8, NMS12 i SE4. Korištenjem metodologije vremenskih nizova i frakcijske integracije, istražuje se pripadnost Hrvatske različitim konvergencijskim klubovima unutar Europske unije. Rezultati pokazuju da Hrvatska konvergira prema dohodovnim razinama EU15 i SE4, s procijenjenim parametrima frakcijske integracije od 0,87 i 0,95. To ukazuje na spor, ali postojan konvergencijski proces. Međutim, konvergencija prema NMS8 i NMS12 nije potvrđena, s parametrima iznad 1, što sugerira trajne dohodovne razlike. Ovi nalazi impliciraju da se Hrvatska ekonomski približava starim članicama EU i zemljama južne Europe, ali ne i novim zemljama članicama.
Maximum lq-likelihood estimator of the heavy-tailed distribution parameter
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.
Copyright (c) 2024 retained by the author(s) https://creativecommons.org/licenses/by-nc-nd/4.0
The impact of urbanisation on poverty reduction in South Africa: A non-linear ARDL approach
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.
Pregled potencijalnih ekonomskih učinaka razvoja 5G infrastrukture - slučaj Hrvatske
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.
Trends and drivers of housing affordability in the EU: Insights from panel data analysis
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.
The direct and indirect effects of financial influencer credibility on investment intention
In this study, the effect of financial influencer credibility on risky investment intention was researched. It was also evaluated whether confidence had a mediating role in this effect. In this context, data was collected from a total of 1000 participants between April and June 2023, based on convenience sampling and volunteering. The scale for financial influencer credibility, the independent variable, was developed within the scope of this study. In this regard, both exploratory and confirmatory factor analyzes were conducted on the collected data, and then the research model was tested using CB-SEM. Acording to the findings, the direct effect of financial influencer credibility on risky investment intention was found to be positive and statistically significant. In addition, according to the mediation analysis, it was determined that confidence has a mediating role in the effect of financial influencer credibility on risky investment intention, and there is partial mediation. As a result, with this study, the concept of influencer was discussed financially for the first time and its impact on investor decisions was revealed.
Unlocking educational paths: Influential factors of Bosnia and Herzegovina’s students performance
This paper explores the influence of socio-economic status on the education performance of male and female students in Bosnia and Herzegovina, utilizing data from the 2018 Programme for International Student Assessment (PISA). The study defines key terms such as education, socio-economic status, and international student assessments, emphasizing the significance of a quality educational system for societal development. By employing three models for science literacy, mathematics, and reading, the results indicate that parents' education and possession of cultural goods significantly impact student achievements. Students with higher-educated parents and who possess more books at home perform better in PISA tests. The gender variable however is found not to be statistically significant. The study emphasizes the significance of a "quiet study space", suggesting that students with such an environment achieve higher science test scores. While causality is not established, the analysis provides insights into the initial impact of socio-economic status on student achievements. The paper advocates for continued participation in international assessments project like PISA to monitor educational achievements and inform evidence-based policy making. The findings underscore practical implications for educational policymakers, and recommendations to enhance Bosnia and Herzegovina's educational system.
Performance analysis of the Croatian video game industry: Expansion amidst the COVID-19 pandemic
The Croatian video game industry demonstrated substantial growth amid the challenges posed by the COVID-19 pandemic. A descriptive statistics approach was utilized, encompassing all enterprises in the Croatian video game industry. Statistical tests for proportions significance were then applied to assess player satisfaction on the Steam platform with video games developed and/or published by the Croatian video game industry. The analysis indicated a concentration of the industry in Zagreb, accounting for 50% of enterprises and 77.4% of employees in 2022. Over the period from 2018 to 2022, total net profit surged from €4.95 million to €12.37 million. However, the average net profit per enterprise experienced a modest increase from €0.12 million to €0.15 million during the same period. Notably, 21% of enterprises maintained the highest AAA rating. County-level comparisons revealed insights into net profit, total revenue, and expenses. On Steam plaform, players recommended remarkable 89% of video games developed or published by the Croatian industry.
Uloga kvalitete institucija i financijske pismenosti u prihvaćanju kriptovaluta
Ovaj rad istražuje utjecaj institucija na prihvaćenost kriptovaluta u zemlji s obzirom na razinu financijske pismenosti stanovništva zemlje. Rezultati istraživanja su pokazali da u zemljama s manjom financijskom pismenošću institucije imaju veći utjecaj na trgovinu s kriptovalutama. Kontrola korupcije, stabilnost vlade, socioekonomski uvjeti, demokracija i kvaliteta birokracije imaju negativan utjecaj, dok zakon i red, involviranost vojske u politiku i sukobi imaju pozitivan utjecaj. S druge strane, kod zemalja s većom financijskom pismenošću utjecaj institucija je manje izražen i uglavnom je negativan. Rast cijene Bitcoina motivira stanovništvo da se uključi u trgovinu kriptovalutama bez obzira na financijsku pismenost. Nadalje, kod država s većom financijskom pismenošću rast prometa na tržištu kapitala potiče dionike da uključe i kriptovalute u svoj portfelj, dok je kod zemalja s manjom financijskom pismenošću ta veza negativna. Ovi rezultati su dodatno potvrđeni i analizom zemalja s obzirom na financijsku inkluziju, koja se u literaturi često povezuje s financijskom pismenošću.
Uloga produktivnosti ustanova rehabilitacije u hrvatskom zdravstvenom turizmu: primjena Malmquist indeksa
Razvoj zdravstvenog turizma ponajviše je definiran globalnim zdravstvenim trendovima, koji osim promjena odnosa potrošača prema zdravlju, uključuju personalizaciju zdravstvenih usluga, implementaciju novih tehnologija i inovacija te održive medicinske prakse. Dodatno, ponuda zdravstvenog turizma se intenzivirala uslijed COVID-19 pandemije i stoga zdravstveni turizam ima veliki potencijal postati jedan od vodećih turističkih proizvoda. Sukladno navedenim razvojnim potencijalom, ali i trendovima na koje pružatelji usluga moraju odgovoriti, cilj rada je istražiti ukupnu faktorsku produktivnost lječilišta i specijalnih bolnica za medicinsku rehabilitaciju u Hrvatskoj tijekom razdoblja 2016. - 2021. Time će se utvrditi je li se u promatranom periodu promijenila produktivnost navedenih zdravstvenih ustanova, koje pružaju pretežito lječilišne usluge i na međunarodnom tržištu te koji su uzroci mogućih promjena. U tu je svrhu korištena analiza omeđivanja podataka (AOMP) i Malmquist indeks produktivnosti (MI). U promatranom je razdoblju ukupna faktorska produktivnost rasla za 1,63% godišnje kao rezultat pozitivnih tehnoloških promjena u prosjeku od 0,55%, dok je tehnička djelotvornosti porasla za 0,42%. Stoga se zaključuje kako su ustanove zdravstvenog turizma, inovacijama poboljšale usluge u skladu s navedenim trendovima, uz istodoban rast relativne tehničke djelotvornosti, koji pak ukazuje na poboljšanje djelotvornosti upravljačkih tijela u istim tim ustanovama.
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A comparison of multilevel ordinal regression models in the analysis of police force ratings
In the literature several methods have been developed to model ordinal data while considering their natural ordering. However, this study sought to compare two possible link functions for the multilevel ordinal regression using males' ratings of the police forces in Uganda as an outcome variable. Variables were obtained from the UNGBS database (Uganda National Governance Baseline Survey). The highest proportion of males rated the police as good (40.9%) followed by fair (24.96%), poor (19.1%), and lastly very good (15.1%). The multilevel ordered logistic regression model with both individual and contextual variables had the lowest AIC compared to other models, fitting the data best. All the likelihood ratio test results indicated that there was significant variation in males' ratings of the police forces across districts. Hence, males from the same district were significantly more similar compared to males from another districts. Researchers using data collected by applying multi-stage sampling or any form of nesting should consider multilevel or mixed-effects models.
Effects of women decision making power on rural children nutritional status in Ogun State of Nigeria
Women's authority over specific family decisions tends to increase their financial security and power, which has an impact on their children's general health and well-being. A multistage sampling process was employed to choose 120 households. Primary data on the children's nutritional status, the household's socioeconomic characteristics, and women decision making were gathered using a well-structured questionnaire. The children's mean body mass index was 9.62 kg/m2, indicating underweight. It was also demonstrated that women had little influence over the quantity of farm produce consumed or sold, nor the number and spacing of their children. On the other hand, rural women make decisions about the daily diet of the home, the education of the children, the kind of medical assistance the child receives while ill, and the amount of parental guidance the youngster receives. However, the women decision making index (WDMI) which measures the negotiating power of women was 0.537. With the age of the mother, gender of child, women decision making index, farm size, farmers association, and farming experience influencing the children nutritional status. Therefore, as it tends to improve the nutritional outcomes for children, it is advised that women be given more control.
The role of labour productivity within Algeria's sustainable economic development: Findings from agricultural sector
Despite Algeria's abundant natural resources, achieving sustainable growth and prosperity remains challenging. Amid this, labour productivity within the agricultural sector stands as a silent warrior, holding within its grasp the secrets to propel the Algerian economy forward. Therefore, this study tries to uncover the pivotal role of labour productivity in Algeria's agricultural sector as a beacon for sustainable economic development. Using an autoregressive distributed lag (ARDL) model from 1990-2021, the results reveal that agricultural gross production value, inflation, and population growth are significant determinants of GDP per capita in the short-run, while agricultural value added per worker also emerges as an essential long-run driver. However, agricultural employment is shown to have an insignificant impact, indicating declines in the sector's workforce and neglect in recent years. Overall, the analysis confirms the hypotheses of either short-term or long-term connections between labour productivity and sustainable economic development within Algeria's agricultural sector. These findings illuminate a pathway that suggests revitalising the labour productivity within Algeria's agricultural sector could be a key lever in transforming Algeria's economic landscape towards a more prosperous and sustainable future.
The safe haven feature of gold in the recent crisis: Rolling regression approach
The global repercussions of the COVID-19 pandemic had a substantial adverse impact on the overall economy, resulting in equity markets decline worldwide. Amidst this turbulent environment, plagued with uncertainty, investors have redirected their attention towards secure assets to protect their capital. In that context the main objective is to reevaluate whether gold still demonstrates the qualities of a safe haven investment during unprecedented events like the COVID-19 pandemic and the Ukrainian war, events distinct from past crisis we have experienced for example 2008 and 1987. For the same reason, a rolling regression between gold and the S&P500 index was employed, taking into account the time-varying properties of daily returns and opting for an optimal window size. The findings indicate that significant neg[1]ative slope coefficients coincide with the COVID-19 pandemic and the initiation of the Ukrainian war. These results offer empirical evidence that gold continues to maintain a robust position as a safe haven in the perception of investors. Nevertheless, it is essential to emphasize that there is no universally applicable safe haven; the safety features of different assets fluctuate over time, depending on the specific market conditions and the nature of financial turmoil.
Foreign direct investment, foreign aid and economic growth nexus in Kenya: A cointegration and causality analysis
The increasing role of foreign capital inflows in reducing the disparity between government revenues and costs as well as impellent economic growth has motivated this study to establish the direction of causality between foreign direct investment (FDI), foreign aid, and economic growth in Kenya. By using annual time series data from 1970 to 2020 within bounds testing approach to cointegration and the error correction model ECM-based Granger-causality, the study found a bidirectional causality between foreign aid and economic growth in the short run and a unidirectional causal flow from foreign aid to economic growth in the long run. The results also support evidences of bidirectional causality between FDI and foreign aid in the short run and a unidirectional causal flow from foreign aid to FDI in the long run. However, the study found no causal relationship between FDI and economic growth, irrespective of whether the causality test is conducted in the short run or in the long run. These empirical findings are encouragement to policy makers in Kenya to carefully channel foreign aid in productive sectors to positively influence economic growth and foreign direct investment, as most relevant targets in achieving Vision 2030 and the Sustainable Development Goals (SDGs).