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Recent imperfect capital market theories predict the presence of asymmetries in the variation of small and large firms' risk over the economic cycle. Small firms with little collateral should be more strongly affected by tighter credit market conditions in a recession state than large, better collateralized ones. This paper adopts a f lexible econometric model to analyze these implications empirically. Consistent with theory, small firms display the highest degree of asymmetry in their risk across recession and expansion states, which translates into a higher sensitivity of their expected stock returns with respect to variables that measure credit market conditions.

We propose a comprehensive methodology to characterize the business cycle comovements across European economies and some industrialized countries, without imposing any given model but trying to 'leave the data speak'. We develop a novel method to show that there is no evidence of a 'European economy' that acts as an attractor to the other economies of the area. We show that the establishment of the Monetary Union has not significantly increased the level of comovements across Euro-area economies. Finally, we are able to explain an important proportion of the distances across their business cycles using macrovariables related to the structure of the economy, to the directions of trade, and to the size of the public sector. r

We set out a model to compute short-term forecasts of the euro area GDP growth in real-time. To allow for forecast evaluation, we construct a real-time data set that changes for each vintage date and includes the exact information that was available at the time of each forecast. With this data set, we show that our simple factor model algorithm, which uses a clear, easy-to-replicate methodology, is able to forecast the euro area GDP growth as well as professional forecasters who can combine the best forecasting tools with the possibility of incorporating their own judgement. In this context, we provide examples showing how data revisions and data availability a¤ect point forecasts and forecast uncertainty.Keywords: Business Cycles, Output Growth, Time Series. JEL Classi…cation: E32, C22, E27We th a n k th e e d ito r a n d th e tw o re fe re e s fo r e x tre m e ly va lu a b le c o m m e nts w h ich h ave g re a tly im p rove d th e c o nte nts o f o u r p a p e r. We a lso th a n k Fra n c is D ie b o ld , J a n J a c o b s, S im o n va n N o rd e n , K e n Wa llis a n d th e p a rtic ip a nts a t th e 5 th Wo rk sh o p o n Fo re c a stin g Te ch n iq u e s, a t th e 5 th C o llo q u iu m o n M o d e rn To o ls fo r B u sin e ss C y c le A n a ly sis, a n d a t th e inte rn a l se m in a r se rie s o f B a n c o d e E sp a ñ a , th e E u ro p e a n C e ntra l B a n k , C E M F I, th e U n ive rsity C a rlo s I I I, th e U n ive rsity o f A lic a nte a n d th e U n ive rsity o f N ava rra fo r h e lp fu l c o m m e nts a n d su g g e stio n s. We re c e ive d e x tre m e ly va lu a b le re se a rch a ssista n c e fro m C a m ilo U llo a . We a re a lso g ra te fu l to th e E u ro A re a U n it o f th e B a n k o f S p a in fo r a ll th e p re lim in a ry m e e tin g s th a t le a d to th is p a p e r. F in a lly, w e a re th a n k fu l to J u a n A y u so fo r h is c le ve r id e a c o n c e rn in g th e n a m e o f th e in d ic a to r. A ny re m a in in g e rro rs a re o u r ow n re sp o n sib ility. P a rt o f th e p a p e r w a s w ritte n w h e n th e …rst a u th o r w a s v isitin g th e B a n k o f S p a in . M a x im o C a m a ch o th a n k s th e …n a n c ia l su p p o rt o f th e p ro je c t S E J 2 0 0 6 -1 5 1 7 2 . T h e v ie w s in th is p a p e r a re th o se o f th e a u th o rs a n d d o n o t re p re se nt th e v ie w s o f th e B a n k o f S p a in o r th e E u ro S y ste m .