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How large are government spending and tax multipliers? The fiscal proxy-SVAR literature provides heterogenous estimates, depending on which proxies - fiscal or non-fiscal - are used to identify fiscal shocks. We reconcile the existing estimates via a flexible vector autoregressive model that allows to achieve identification in presence of a number of structural shocks larger than that of the available instruments. Our two main findings are the following. First, the estimate of the tax multiplier is sensitive to the assumption of orthogonality between total factor productivity (non-fiscal proxy) and tax shocks. If this correlation is assumed to be zero, the tax multiplier is found to be around one. If such correlation is non-zero, as supported by our empirical evidence, we find a tax multiplier three times as large. Second, we find the spending multiplier to be robustly larger than one across different models that feature different sets of instruments. Our results are robust to the joint employment of different fiscal and non-fiscal instruments.

Macroeconomic uncertainty consists of three components: the unobservable, the heterogeneous and the “uncertain”. We are unaware of exactly when economic agents perceive uncertainty and which type of uncertainty interests them. This paper introduces and outlines a way of conducting large-scale data searches on the Web. We create the EURQ index of “economic uncertainty related queries” for both the USA and Italy. We show that the EURQ encapsulates agents’ need to gather more information during periods of uncertainty. This need either spontaneously arises in the case of macro-real and political uncertainty, or is induced by the media in the case of normative and financial uncertainty. This distinction is extremely important when trying to understand the immediate impact of fiscal policy uncertainty on economic variables, and how financial shocks can produce a significant short-term impact on economic activity. It is also helpful when trying to solve the identification and endogeneity issues encountered in the literature when assessing the role of uncertainty.

We provide novel evidence on the existence and the extent of intergenerational transmission of STEM (Science, Technology, Engineering and Mathematics) education using a recent large administrative dataset of Italian graduates obtained from the Almalaurea data. Parental influence on two STEM educational outcomes (high school and university degree completion) is strong and, net of student's time-invariant unobserved heterogeneity, proves to be stronger at the stage of the educational career closer to labour market entry. At this stage, the influence of fathers outweighs the one of mothers and is larger for sons than for daughters. The documented STEM intergenerational transmission is not driven by liberal profession of parents for most of STEM fields, while it is for some non-STEM fields (economic and legal studies), consistently with the presence of entry barriers in some professions.

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g Ï 1 structural shocks, where r Ï g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a "larger" SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the "multiple shocks" approach, where all structural shocks are of interest, and in the "partial shock" approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle fluctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.

The purpose of the present paper is to study how households form inflation expectations. Using a novel survey-base dataset of Italian households’ opinions of inflation we investigate two separate, but related, types of behavior: ‘inattentiveness’ and ‘anchoring’. The present analysis extends the existing literature by incorporating explicitly inflation targets and distinguishing between aggregate and disaggregate dynamics based on demographic groups. In addition, we extend the literature by considering both the short- and long-run dynamics as households update their inflation expectations while also accounting for their state-varying behavior. All these issues provide important insights into understanding actual inflation dynamics and the conduct of monetary policy.

This paper develops an asymptotic theory for integrated and near-integrated time series whose range is constrained in some ways. Such a framework arises when integration and cointegration analyses are applied to time series that are bounded either by construction or because they are subject to control. The asymptotic properties of some commonly used integration tests are discussed; the bounded unit root distribution is introduced to describe the limiting distribution of the sample first-order autoregressive coefficient of a random walk under range constraints. The theoretical results show that the presence of such constraints can lead to drastically different asymptotics. Because deviations from the standard unit root theory are measured through two noncentrality parameters that can be consistently estimated, simple measures of the impact of range constraints on the asymptotic distributions are obtained. Generalizations of standard unit root tests that are robust to the presence of range constraints are also provided. Finally, it is shown that the proposed asymptotic framework provides an adequate approximation to the finitesample properties of the unit root statistics under range constraints.

In this paper we use the unit root test at both individual company (Dickey-Fuller) and panel (Im-Pesaran-Shin) level, in order to provide some quantitative evidence of the univariate behaviour of Italian companies’ debt-ratio. If it is mean-reverting, then at least a share of companies are going to behave according to the trade-off model, whereas if it is non-stationary, then companies may behave according to pecking order theory. Individual company test results support the pecking order theory in the case of more than 80% of firms, while the panel test rejects the unit root null. These contradictory results can be explained by the heterogeneity of the firms which tends to characterise the entire panel. For this reason, we selected a number of sub-samples in which companies are supposed to follow either the pure trade-off or the pure pecking order model of behaviour. Results confirm that: a) heterogeneity may lead to a false rejection of the pecking order theory in panel unit root tests; b) both trade-off and pecking order theories contribute towards explaining the financial behaviour of Italian companies; c) the testing procedure we propose has the power to reject the pure pecking order model under the null hypothesis, but not the pure trade-off model.