16 research outputs found

    Reply to Notes on: “The Generalised Index Numbers”

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    Generalised Index Numbers, Basket Factor, Indicator Function

    Chinese entrepreneurship in context: specialization, localization and their impact on Italian industrial districts

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    Chinese migration flows represent a relatively new phenomenon in Italy. Its entrepreneurial nature is reflected in massive flows Chinese businessman employed both in manufacturing and commercial activities, with a dense concentration in correspondence of some industrial districts. The aim of the paper is to shed some light on current Chinese specialization of economic activities and localization across Italian regions and industrial districts, to test interpretative research hypothesis on Chinese entrepreneurship models and identify agglomeration forces underlying the emergence of so-called Chinese ethnic businesses. Some reflections on the manufacturing and commercial attitude of Chinese entrepreneurship will also be considered. The utilization of native-Chinese entrepreneurs as unit of observation represents an innovative methodological contribution based on ASIA-ISTAT archives. The exercise of explorative analysis based on data processing and spatial analysis will finally highlight business migration patterns, which represent new socio-economic challenges for Italian industrial districts

    The Generalised Index Numbers

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    [En] The aim of the paper is to redefine, the notational aspect of the traditional formulas of the, numbers index theory. After having defined the total value index, the “generalised Index Numbers” (g-IN) are introduced and the “indicator function of the copresent” and the Basket factor are defined. [It] L’obiettivo dell’articolo Ăš ridefinire, dal punto di vista della notazione, le tradizionali formule della teoria dei numeri indice. Dopo aver definito l’indice di valore totale si introducono i “generalised Index Numbers” (g-IN) e si definiscono la “funzione indicatrice dei co-presenti” ed il fattore “Basket”. [Fr] Le principal objectif de l’article est redĂ©finir, du point de vue de la notation, les traditionnelles formules de la thĂ©orie des nombres indice. AprĂšs avoir dĂ©fini l'indice de valeur totale on introduit les «generalised Index Numbers» (g-IN) et, en relation aux g-IN, on dĂ©finit: la «fonction indicatrice des co-prĂ©sents» et le facteur «Basket».Generalised Index Numbers, Basket Factor, Indicator Function

    Sectorial Selling Product and Sectorial Operating Revenue: an Approach Ă  la Leontief

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    [En] The main aim is to create a bridge between the typical aggregates of business account and the equivalent derived by the SNA. Using the I-O of Leontief model, the two business concepts of “sectorial selling product” and “sectorial operating revenue” will be expressed through the SNA aggregates. [It] L’obiettivo che ci si propone Ăš quello di mettere in relazione gli aggregati tipici di un bilancio aziendale con i corrispondenti desumibili dalla contabilitĂ  nazionale. A tal fine, usando il modello Input-Output di Leontief, si procederĂ  a definire, in termini di contabilitĂ , due concetti tipicamente aziendali: la “produzione vendibile” settoriale ed i “proventi netti” settoriali. [Fr] Le but principal est celui de mettre en relation les agrĂ©gats typiques d'un budget d'entreprise avec ses Ă©quivalents dans la comptabilitĂ© nationale. À tel fin, en employant le modĂšle I-O de Leontief, on procĂ©dera Ă  dĂ©finir, en termes de comptabilitĂ©, deux concepts typiquement d'entreprise: la «production sectorielle commercialisable» et le «chiffre d'affaires de secteur».Input-Output, Selling Product, Operating Revenue, Sector, Business

    Chinese entrepreneurship in context: specialization, localization and their impact on Italian industrial districts

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    Chinese migration flows represent a relatively new phenomenon in Italy. Its entrepreneurial nature is reflected in massive flows Chinese businessman employed both in manufacturing and commercial activities, with a dense concentration in correspondence of some industrial districts. The aim of the paper is to shed some light on current Chinese specialization of economic activities and localization across Italian regions and industrial districts, to test interpretative research hypothesis on Chinese entrepreneurship models and identify agglomeration forces underlying the emergence of so-called Chinese ethnic businesses. Some reflections on the manufacturing and commercial attitude of Chinese entrepreneurship will also be considered. The utilization of native-Chinese entrepreneurs as unit of observation represents an innovative methodological contribution based on ASIA-ISTAT archives. The exercise of explorative analysis based on data processing and spatial analysis will finally highlight business migration patterns, which represent new socio-economic challenges for Italian industrial district

    G-Index Numbers of the Production of Pollutions, the Linked Social Impact and Non Measurable Variations

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    Lñ€Âℱobiettivo del lavoro ĂƒÆ’Ă‚Âš la semplificazione della comunicazione dei dati ambientali attraverso lñ€Âℱuso di indicatori. Gli indicatori ambientali si classificano in base allo schema Pressione Stato Risposta (DPSIR). Nel lavoro ci si occupa di indicatori di impatto legati ad inquinanti il atmosferici (PM10). La strategia di ricerca seguita ĂƒÆ’Ă‚Âš basata sulla Teoria dei Numeri Indice generalizzati (g-IN) introdotta da Verrecchia (2003, 2005). Lñ€Âℱutilizzo dei g-IN in ambito ambientale ha il vantaggio di trattare i ñ€ÂƓmissing valuesñ€Â? e le variazioni non misurabili, oltre che considerare gli effetti sociali dellñ€Âℱinquinamento. Per le applicazioni ĂƒÆ’Ă‚Âš stata utilizzata una serie storica giornaliera di rilevazioni degli inquinanti atmosferici in provincia di Milano messa a disposizione dallñ€ÂℱAgenzia Regionale per la Protezione dellñ€ÂℱAmbiente (ARPA) della Lombardia

    Bilevel Comparative Regional Analysis - Performances in Structural Grid

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    Il metodo proposto mira ad analizzare il contesto regionale europeo (UE 15), in base agli indicatori introdotti nel Rapporto di Primavera 2004, disponibili a livello regionale, e usati a livello europeo per valutare i progressi compiuti dai diversi paesi ed in questo caso per evidenziare le best practises ed identificare gruppi regionali omogenei rispetto ai quali svolgere comparazioni. A tal fine si propone un nuovo metodo di analisi comparativa regionale i.e. Bilevel Comparative Regional Analysis - Performances in Structural Grid (BiCRA-PSG) volto a superare le problematiche di natura comparativa causate dall’eterogeneità delle unità statistiche considerate e alternativa rispetto alle insoddisfacenti proposte fino ad ora adottate.Regional Economic Activity, Comparative Analysis, European Regional policy, Factor Analysis, Cluster Analysis

    ESeC-Rubin Missing Value Interpretation for a Regional Bottom-Up Hierarchical Forecasting

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    in letteratura, per l’imputazione dei dati mancanti nelle serie storiche, si fa riferimento a statistiche applicate all’intera serie analizzata (e.g. media di tutti i termini della serie), ottenendo una costante d’imputazione generalmente adeguata per una specifica serie. Se le serie sono n (n -> infinito) Ăš impossibile trovare un’unica funzione per le n costanti di imputazione dei missing. Obiettivo del lavoro Ăš proporre un nuovo metodo di imputazione dei dati mancanti - ESeC-Rubin - per basi dati gerarchiche finalizzato alla modellistica temporale. In particolare, la ESeC-Rubin consente di ricostruire il dato mancante tenendo conto di una sequenza di metodi di imputazione e della naturale variabilitĂ  degli aggregati studiati. La metodologia proposta in questo lavoro trova ispirazione dalla teoria dei campioni dove non di rado si deve trovare la miglior soluzione possibile al problema del missing. In questo contesto la soluzione che si cerca di dare Ăš quella di ricostruire il dato mancante tenendo conto della naturale variabilitĂ  del fenomeno allo studio (Rubin 1987, 1996; Hergoz e Rubin, 1983; Rubin e Shenker, 1986). In effetti la letteratura in tal senso fornisce una gamma piuttosto articolata di strategie che possono di volta in volta essere utilizzate in quanto appare immediatamente evidente che la soluzione non puĂČ essere unica e generalizzata. Infine, si presenterĂ  una applicazione della ESeC-Rubin su dati socio-economici di fonte Eurostat. L’applicazione prodotta con SAS Forecast Server consente di comparare i modelli (selezionati in automatico) a partire dalla base dati osservata con missing values e differenti tipologie di imputazione.Missing Value, Index Number, CAGR Imputation, Stochastic Imputation, ESeC-Rubin Imputation, Regional Bottom-Up Hierarchical Forecasting

    Entry and Exit of Nonprofit Organizations

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    The latest census of Italian nonprofit organizations \u2013 compared with the previous one \u2013 showed a significant development of the nonprofit sector between 2001 and 2011. The number of organizations increased more than 28 % while the growth of employees (about 61 %) was even more impressive. These results notwithstanding, the mere comparison of aggregate census data does not give a true understanding of the dynamic of the sector. The entry and exit of organizations, as well as their migration between different sectors of activity, or geographical areas, can be analyzed properly only using firm-level panel data, but these data are rarely available so that only a few authors had a chance to use them. In this paper, we try to fill this gap using firm-level panel data for the first time in Italy. Our analysis tempers the optimism arising from aggregate data. We show that: a) part of the growth is determined by the emergence of already active organizations that were not detected a decade ago; b) because of low barriers, the entry of new nonprofit organizations is very relevant, but their net contribution to the growth of employment is quite small; c) opposite to what happened in other countries, the exit of nonprofit organizations is very significant, and d) organizations that were already active a decade ago gave the most important contribution to the growth of employment. We also investigate geographical trends, showing that the slower growth of the nonprofit sector in Southern Italy depends on the very high exit rate of the area, while the entry rate is more or less in line with the rest of the countr
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