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An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy
No full textCoronavirus disease (COVID-2019) is a severe ongoing novel pandemic that is spreading quickly across the world. Italy, that is widely considered one of the main epicenters of the pandemic, has registered the highest COVID-2019 death rates and death toll in the world, to the present day. In this article I estimate an autoregressive integrated moving average (ARIMA) model to forecast the epidemic trend over the period after April 4, 2020, by using the Italian epidemiological data at national and regional level. The data refer to the number of daily confirmed cases officially registered by the Italian Ministry of Health (www.salute.gov.it) for the period February 20 to April 4, 2020. The main advantage of this model is that it is easy to manage and fit. Moreover, it may give a first understanding of the basic trends, by suggesting the hypothetic epidemic’s inflection point and final size
The relationship between labor market institutions and innovation in 177 European regions over the period 2000–2015
No full textThe main goal of this paper is to investigate the relationship between labor market institutions (LMIs) and patents in 177 NUTS-1 and NUTS-2 European regions. Fixed effects models, ordinary least squares (OLS), the generalized method of moments estimation of the fixed effects (FE-GMM), multilevel modeling (MLM), and spatial models are employed. Patents are negatively correlated with EPL and union density and positively associated with wage bargaining coverage and centralization. As a result, a uniform wage that is higher than the competitive wage can enable the Schumpeterian creative destruction process, forcing firms to invest in innovation to remain in the market. Spatial analysis emphasizes that regional proximity promotes the flow of knowledge and increases the chance of innovation. Interactions also matter. Increased bargaining power and coordination, in particular, may outweigh the negative consequences of isolated EPL reforms. Thus, policies that strengthen wage-setting institutions are required in Europe to boost innovation
Ripensare la funzione di produzione neoclassica
No full textCobb-Douglas aggregate production function surely represents the cornerstone of the neoclassical theory. However, its good fit implies the respect for a series of unrealistic and increasingly restrictive hypothesis. So, this article attempts to summarize and to analyze the most important objections to Cobb-Douglas function raised by heterodox economists
An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy
No full textCoronavirus disease (COVID-2019) is a severe ongoing novel pandemic that is spreading quickly across the world. Italy, that is widely considered one of the main epicenters of the pandemic, has registered the highest COVID-2019 death rates and death toll in the world, to the present day. In this article I estimate an autoregressive integrated moving average (ARIMA) model to forecast the epidemic trend over the period after April 4, 2020, by using the Italian epidemiological data at national and regional level. The data refer to the number of daily confirmed cases officially registered by the Italian Ministry of Health (www.salute.gov.it) for the period February 20 to April 4, 2020. The main advantage of this model is that it is easy to manage and fit. Moreover, it may give a first understanding of the basic trends, by suggesting the hypothetic epidemic's inflection point and final size
The impact of public healthcare system on COVID-19 mortality rate in selected European and South Caucasian countries
No full textThis study investigated the relationship between public healthcare-related features, vaccination rates, and COVID-19 mortality rates in 44 European and South Caucasian countries. The COVID-19 mortality rates were averaged from 21 November 2021 to 4 December 2021, coinciding with the height of the fourth wave of the pandemic. A cross-sectional analysis was conducted using the ordinary least squares (OLS) estimator, the spatial autoregressive (SAR) model, and the spatial error (SEM) model. A cluster analysis was then performed to identify homogeneous groupings of nations exhibiting escalating risk variables for COVID-19 mortality. The results indicated that public health expenditure, healthcare personnel, pharmacists, universal health coverage (UHC), and COVID-19 vaccination rates exhibited significant negative correlations with COVID-19 mortality rates, while out-of-pocket (OOP) spending and the saturation of ordinary and intensive care unit (ICU) beds demonstrated significant positive correlations with COVID-19 mortality rates. Cluster analysis indicated that post-communist and post-Soviet European nations with more decentralized and predominantly private insurance-based healthcare systems exhibited the highest risk variables for COVID-19 mortality. In contrast, Nordic European countries with universal healthcare systems demonstrated the lowest risk. Consequently, nations with publicly funded comprehensive healthcare systems have shown greater efficacy in reducing COVID-19 death rates while alleviating the strain on national healthcare systems. These policy recommendations may be beneficial in the event of similar shocks in the future
The determinants of COVID-19 case fatality rate (CFR) in the Italian regions and provinces: An analysis of environmental, demographic, and healthcare factors
No full textThe Italian government has been one of the most responsive to COVID-2019 emergency, through the adoption of quick and increasingly stringent measures to contain the outbreak. Despite this, Italy has suffered a huge human and social cost, especially in Lombardy. The aim of this paper is dual: i) first, to investigate the reasons of the case fatality rate (CFR) differences across Italian 20 regions and 107 provinces, using a multivariate OLS regression approach; and ii) second, to build a "taxonomy" of provinces with similar mortality risk of COVID-19, by using the Ward's hierarchical agglomerative clustering method. I considered health system metrics, environmental pollution, climatic conditions, demographic variables, and three ad hoc indexes that represent the health system saturation. The results showed that overall health care efficiency, physician density, and average temperature helped to reduce the CFR. By the contrary, population aged 70 and above, car and firm density, air pollutants concentrations (NO2, O-3, PM10, and PM2.5), relative average humidity, COVID-19 prevalence, and all three indexes of health system saturation were positively associated with the CFR. Population density, social vertical integration, and altitude were not statistically significant. In particular, the risk of dying increases with age, as 90 years old and above had a three-fold greater risk than the 80-to-89 years old and four-fold greater risk than 70-to-79 years old. Moreover, the cluster analysis showed that the highest mortality risk was concentrated in the north of the country, while the lowest risk was associated with southern provinces. Finally, since prevalence and health system saturation indexes played the most important role in explaining the CFR variability, a significant part of the latter may have been caused by the massive stress of the Italian health system. (C) 2020 Elsevier B.V. All rights reserved
Economic growth and GHG reduction: a global issue
Full text linkThe environmental sustainability is probably one of the most controversial topics of national policy agendas. The needs to combine economic growth and well-being, have forced governments to introduce tools for reducing CO2 emission and avoiding climate change. This paper aims to assess the effectiveness of these measures in the 1990-2014 period for a sample of 188 countries; and to analyze the determinants of CO2 in the 2000-2014 period for a sample of 175 countries. The results suggest that i) richest countries have a GDP elasticity of CO2 greater than that of poorest countries; and ii) GDP, energy consumption, urbanization, agricultural development, tourism and depletion of natural resources are directly correlated to CO2, while forest area, alternative energy, trade openness and FDI inflows are inversely related to CO2
I costi della criminalità organizzata nel settore agroalimentare italiano
Full text linkDagli anni ’90 il settore agroalimentare italiano è minacciato da un inquietante fenomeno: la criminalità organizzata attiva nel settore ambientale. In questo articolo esaminiamo la relazione fra la pressione eco-criminale e l’indice dei prezzi al consumo degli alimenti e delle bevande analcoliche per le 20 regioni italiane e per 80 province. A livello regionale come proxy delle attività dell’eco-mafia costruiamo un indice di eco-criminalità usando dati pubblicati da Legambiente. A livello provinciale utilizziamo quattro variabili: estorsioni, contraffazione, contrabbando e incendi boschivi. L’analisi mostra che l’eco-mafia può influenzare consistentemente l’intero settore agroalimentare, causando un aumento dei prezzi alimentari, soprattutto nel mezzogiorno. Al contrario, nel centro-nord il riciclaggio sembra ridurre i prezzi alimentari, attraverso il reinvestimento dei proventi illeciti in aziende con forti vantaggi di costo.
From the 1990s the Italian agribusiness sector is threatened by a disturbing phenomenon: organized crime in the agribusiness sector.. In this paper we examine the relationship between eco-criminal pressure and consumer food and non-alcoholic drinks price index for the 20 Italian regions and 80 Italian provinces. At regional level, as a proxy for eco-mafia’s activities we build an ad hoc eco-criminal index using data from Legambiente. At the province level we use four variables: extortions, counterfeiting, contraband and woods fire. The analysis shows that the eco-mafia can consistently affect the whole agribusiness sector, causing an increase in food prices, especially in the South of the country. By contrast, in the Centre-North of Italy, money laundering seems to reduce food prices for consumers through the reinvestment of illicit proceeds in firms with strong cost advantages.
JEL codes: K42, Q11, Q13
Keywords: cost of crime, agro-mafia, money laundering, food price
Quando la produttività è limitata dalla bilancia dei pagamenti. Una riflessione sulle relazioni fra centro e periferia nell’unione monetaria europea a partire dall’equazione della produttività di Sylos Labini
Full text linkDa cosa dipende il gap di produttività fra paesi core e paesi periferici nell’Eurozona? L’articolo propone una rivisitazione dell’equazione della produttività di Paolo Sylos Labini per dar conto del fenomeno della crescita vincolata dalla bilancia dei pagamenti messo in luce da Anthony Thirlwall. L’analisi cerca di verificare se gli squilibri commerciali fra centro e periferia nell’Eurozona sono rilevanti per comprendere il divario crescente della produttività fra le due aree. I risultati ottenuti sembrano confermare la presenza di un vincolo estero di natura tecnologica che grava sulla periferia. Questo vincolo presenta una correlazione significativa con il gap di produttività fra centro e periferia anche a seguito delle ristrutturazioni dei processi produttivi che hanno interessato i paesi periferici.What does the productivity gap between core and peripheral countries in the Eurozone depend on? The article proposes a revisiting of Paolo Sylos Labini’s productivity equation aimed at analyzing the phenomenon of balance of payments constrained growth highlighted by Anthony Thirlwall. The analysis tries to verify whether the trade imbalances between the center and the periphery of the Eurozone are relevant to understand the increasing gap in productivity between the two areas. The results seem to confirm the presence of a foreign technological constraint on the periphery. This constraint exhibits a significant correlation with the productivity gap between the center and the periphery, even after the restructuring of production processes undergone in the peripheral countries
Forecasting of GDP Growth in the South Caucasian Countries Using Hybrid Ensemble Models
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Open AccessArticle
Forecasting of GDP Growth in the South Caucasian Countries Using Hybrid Ensemble Models
by Gaetano Perone 1,2,*ORCID andManuel A. Zambrano-Monserrate 3ORCID
1
Department of Economics and Management, University of Pisa, Via Cosimo Ridolfi 10, 56124 Pisa, Italy
2
Kutaisi International University, Akhalgazrdoba Ave. Lane 5/7, 4600 Kutaisi, Georgia
3
Universidad Espíritu Santo, Samborondón 0901952, Ecuador
*
Author to whom correspondence should be addressed.
Econometrics 2025, 13(3), 35; https://doi.org/10.3390/econometrics13030035
Submission received: 29 June 2025 / Revised: 1 September 2025 / Accepted: 2 September 2025 / Published: 10 September 2025
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Abstract
This study aimed to forecast the gross domestic product (GDP) of the South Caucasian nations (Armenia, Azerbaijan, and Georgia) by scrutinizing the accuracy of various econometric methodologies. This topic is noteworthy considering the significant economic development exhibited by these countries in the context of recovery post COVID-19. The seasonal autoregressive integrated moving average (SARIMA), exponential smoothing state space (ETS) model, neural network autoregressive (NNAR) model, and trigonometric exponential smoothing state space model with Box–Cox transformation, ARMA errors, and trend and seasonal components (TBATS), together with their feasible hybrid combinations, were employed. The empirical investigation utilized quarterly GDP data at market prices from Q1-2010 to Q2-2024. According to the results, the hybrid models significantly outperformed the corresponding single models, handling the linear and nonlinear components of the GDP time series more effectively. Rolling-window cross-validation showed that hybrid ETS-NNAR-TBATS for Armenia, hybrid ETS-NNAR-SARIMA for Azerbaijan, and hybrid ETS-SARIMA for Georgia were the best-performing models. The forecasts also suggest that Georgia is likely to record the strongest GDP growth over the projection horizon, followed by Armenia and Azerbaijan. These findings confirm that hybrid models constitute a reliable technique for forecasting GDP in the South Caucasian countries. This region is not only economically dynamic but also strategically important, with direct implications for policy and regional planning
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