Scene detection on user-generated content (UGC) aims to classify an audio recording that belongs to a specific scene such as busy street, office or supermarket rather than a sound such as car noise, computer keyboard or cash machine. The difficulty of scene content analysis on UGC lies in the lack of structure and acoustic variability of the audio. The i-vector system is state-of-the-art in Spe...

We propose a way to test the New Keynesian Phillips Curve (NKPC) without estimating the structural parameters governing the curve, i.e. price stickiness and firms’ backwardness. Using this strategy we can test the NKPC avoiding the identification problems related to the GMM approach. We find that it does not exist a combination of the structural parameters which is consistent with US data. This...

GEL methods which generalize and extend previous contributions are defined and analysed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are asymptotically equivalent to their efficient two-step GMM counterparts. The basis for GEL estimation is via a smoothed version of the moment indicators using kern...

Dynamic partial adjustment models of residential electricity demand account for the fact that households may not adjust electricity consumption immediately in response to changes in prices, income, and other relevant factors, because of behavioral habits or adjustment costs for the capital stock of appliances. However, forward-looking behavior is generally neglected. Expectations about future p...

The paper revisits the local determinants of crime using a spatial model distinguishing between resident and non-resident offenders. Employing data for German municipalities, the model is estimated by means of a spatial GMM approach. Focusing on resident offenders legal earnings opportunities and the expected gain from offenses are found to be important determinants of crime. Also the socio-eco...

I-vector based recognition is a well-established technique in state-of-the-art speaker and language recognition but its use in dialect and accent classification has received less attention. We represent an experimental study of i-vector based dialect classification, with a special focus on foreign accent detection from spoken Finnish. Using the CallFriend corpus, we first study how recognition ...

In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused lasso. We consider two approaches — penalized least squares (PLS) for firstdifferenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one both methods can correctly determine the ...

Following the present atmosphere of budgetary cuts in the OECD countries we analyze the effects of fiscal consolidation in the composition of government expenditures by functions. We modify a standard median voter demand model to incorporate a form of fiscal illusion based on the idea that voters-taxpayers may not be fully aware of the true composition of government expenditures because all typ...

Article history: Received 15 May 2007 Received in revised form 26 January 2009 Accepted 28 January 2009 Available online 6 February 2009 This paper uses an iterated GMM approach to estimate and test the consumption based habit persistence model of Campbell and Cochrane [Campbell, J.Y., Cochrane, J.H., 1999. By force of habit: A consumption-based explanation of aggregate stockmarket behavior. Jo...

When weak identification is a concern researchers frequently calculate confidence sets in two steps, first assessing the strength of identification and then, on the basis of this initial assessment, deciding whether to use an identification-robust confidence set. Unfortunately, two-step procedures of this sort can generate highly misleading confidence sets, and we demonstrate that two-step conf...