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Following the debate on the relationship between business and financial cycle rekindled in the last decade since the global financial crisis, we assess the ability of some financial indicators to track the Italian business cycle. We mostly use credit variables to detect the turning points and to estimate the probability of recession in real time. A dynamic factor model with Markov‐switching regimes is used to handle a large data set and to cope with the nonlinear evolution of the business cycle. The in‐sample results strongly support the capacity of credit variables to estimate the probability of recessions and the implied coincident indicator proves their ability to fit the business cycle. Also in real time the contribution of credit is not negligible compared to that of the industrial production, currently used for the conjunctural analysis.

We analyse the results of a survey conducted by the Bank of Italy in the spring of 2012 on Italian science and technology parks. First we describe the main features of science parks in Italy. Then we investigate whether they have been effective in improving the economic performance and innovative capacity of the firms located within them. We find a pronounced heterogeneity between science and technology parks, whose cooperation with public research institutions is characterized by physical proximity. Although the business situation of firms located in science and technology parks tends on average to be better than that of similar �non-park� firms, a difference-in-differences estimation shows that entering a science and technology park did not generally improve firms� business performance and their propensity to innovate compared with external counterparts.

Housing taxation is a main policy instrument shaping households choices about homeownership and renting as well as the evolution of the housing market. We study the effects of housing taxation in a model with search and matching frictions in the property market and a competitive rental market. We show a new transmission channel of a housing tax reform that works through a “shifting” of the tax burden on secondary homes from landlords to tenants through rental prices. Property taxation affects house prices not only through the change in the user cost but also via the impact on housing rental services, as measured by the rental prices. We calibrate the model in order to estimate the effects of the recent Italian housing market taxation reforms and the extent of property taxes capitalization in house prices. We show that property taxation on owner-occupied dwellings has a negative effect on property and rental prices, whereas taxes on secondary homes have qualitative opposite effects. The simultaneous increase of both these instruments may mitigate the dynamics of prices and rents as well as the change of the ratio between the share of owners and renters, determining a partial capitalization of taxation on prices.

Financial frictions have become fundamental for studying the business cycle and credit market dynamics. This work adds to the existing literature by introducing a search and matching scheme in the financial market into a cash in advance New Keynesian DSGE theoretical model. We provide an alternative explanation of the degree of incompleteness in the pass-through from policy rate to loan rates depending on credit market tightness, the search costs sustained by banks, and the relative powers of the agents in loan interest rate bargaining. The model is able to reproduce the countercyclical behaviour of the credit spread with respect to a positive technology shock. It also proposes a scenario in which a credit shock hits the economy. The model is estimated by using the Bayesian procedures. Finally, since there is still some disagreement about the theoretical mechanism by which the interest rate on loans is derived, we survey and compare these theoretical devices with that proposed by this paper.