On Labour Market Policies and Aggregate Unemployment Outflows

This paper is interested in the modelling of the relationship between active and passive labour market policies and the aggregate unemployment outflow rate. Our model is based on a matching function and includes a simple representation of the competition between various groups of job searchers. The empirical analysis uses Belgian data. Faced with variables that are often integrated of order 1 according to the usual tests but which cannot strictly speaking be integrated, we contribute to an important methodological debate by comparing the conclusions of a classical econometric analysis and a cointegration approach.     

Composite commodities, housing characteristics and the Hicksian surplus measures of welfare change

The purpose of this paper is to elaborate on previous research that deals with the implications of alternative housing concepts for the estimation of the welfare effects of housing programs. We compare one housing concept, which defines housing in terms of a composite good housing services with an alternative in which housing is treated as a bundle of attributes. We extend the analysis in the literature by concentrating on welfare measures that are applicable to a much broader class of government programs than those that have been discussed before. We focus in the Hicksian surplus measures which are particularly suited to handle structure in which constraints on quantity are impused. In the theoretical sections we rigorously show that the Hicksian surplus measures of welfare change based on the composite good housing services will be biased whenever a housing program imposes restrictions on the consumption of attributes. The direction of the bias depends on the nature of the program. Empirical work confirms the predictions of the theoretical analysis.     

A de Finetti-Kolmogoroff-Nagumo type integral representation theorem for generalized means on masses

We point out that the Consistency, Continuity and Associativity properties of an extended realvalued functionalm on masses are the basic notions to get a de Finetti-Kolmogoroff-Nagumo type integral representation ofm.

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Riassunto Come è noto il teorema di de Finetti-Kolmogoroff-Nagumo formisce una rappresentazione integrale di particolari funzionali reali, detti medie, definiti per funzioni di ripartizione che distribuiscono l'intera massa su un prefissato intervallo chiuso e limitato dell'asse reale.Nel lavoro [2] gli autori hanno esteso la nozionc di media, considerata ancora come funzionale reale, dalle funzioni di ripartizione alle masse (misure finitamente additive limitate e non negative). In questo modo, estendendo ad essa le usuali proprictà (internalità, associatività, etc.), sono riusciti a provare un teorema di rappresentazione integrale analogo a quello di de Finctti-Kolmogoroff-Nagumo per medie continue ed associative definite su opportuni insiemi di masse tight (cio prive di masse aderenti a – e+).In questo lavoro, naturale prosccuzione del preccedente, si prendono invecc in considerazione medic generalizzate (cioè medie che possono assumere valori reali oppure anche i valori – c+) e masse non neccssariamente tight. Si fa allora vedere che le nozioni di consistenza, continuità e associatività per un funzionale a valori nella retta compatta e definito sulle masse non nulle, sono condizioni caratteristiche per ottencre una sua rappresentazione integrale del tipo de Finctti-Kolmogoroff-Nagumo. Si prova inoltre che, a differenza della media ariumetica, le medic generalizzate continue ed associative possono assumere valori non reali solamente su opportune masse non tight.

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Work performed under the auspices of the National Group for Sthocastic Models and Mathematical Statistics (M.R.S.T. 40%) and G.N.A.F.A. of C.N.R.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.